Many regions of the planet have experienced an increase in fire activity in recent decades. Although such increases are consistent with warming and drying under continued climate change, the driving mechanisms remain uncertain. Here, we investigate the effects of increasing atmospheric carbon dioxide concentrations on future fire activity using seven Earth system models. Centered on the time of carbon dioxide doubling, the multi-model mean percent change in fire carbon emissions is 66.4 ± 38.8% (versus 1850 carbon dioxide concentrations, under fixed 1850 land-use conditions). A substantial increase is associated with enhanced vegetation growth due to carbon dioxide biogeochemical impacts at 60.1 ± 46.9%. In contrast, carbon dioxide radiative impacts, including warming and drying, yield a negligible response of fire carbon emissions at 1.7 ± 9.4%. Although model representation of fire processes remains uncertain, our results show the importance of vegetation dynamics to future increases in fire activity under increasing carbon dioxide, with potentially important policy implications.

The ability to anticipate marine habitat shifts responding to climate variability has high scientific and socioeconomic value. Here we quantify interannual-to-decadal predictability of habitat shifts by combining trait-based aerobic habitat constraints with a suite of initialized retrospective Earth System Model forecasts, for diverse marine ecotypes in the North American Large Marine Ecosystems. We find that aerobic habitat viability, defined by joint constraints of temperature and oxygen on organismal energy balance, is potentially predictable in the upper-600 m ocean, showing a substantial improvement over a simple persistence forecast. The skillful multiyear predictability is dominated by the oxygen component in most ecosystems, yielding higher predictability than previously estimated based on temperature alone. Notable predictability differences exist among ecotypes differing in temperature sensitivity of hypoxia vulnerability, especially along the northeast coast with predictability timescale ranging from 2 to 10 years. This tool will be critical in predicting marine habitat shifts in face of a changing climate.

This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, http://www.isimip.org, last access: 2 November 2023) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human, and managed systems to climate change, rising CH4 and CO2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6.

Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a “top 10” list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Pelagic tunicates (salps, pyrosomes) and fishes generate jelly falls and/or fecal pellets that sink roughly 10 times faster than bulk oceanic detritus, but their impacts on biogeochemical cycles in the ocean interior are poorly understood. Using a coupled physical-biogeochemical model, we find that fast-sinking detritus decreased global net primary production and surface export, but increased deep sequestration and transfer efficiency in much of the extratropics and upwelling zones. Fast-sinking detritus generally decreased total suboxic and hypoxic volumes, reducing a “large oxygen minimum zone (OMZ)” bias common in global biogeochemical models. Newly aerobic regions at OMZ edges exhibited reduced transfer efficiencies in contrast with global tendencies. Reductions in water column denitrification resulting from improved OMZs improved simulated nitrate deficits relative to phosphate. The carbon flux to the benthos increased by 11% with fast-sinking detritus from fishes and pelagic tunicates, yet simulated benthic fluxes remained on the lower end of observation-based estimates.

The California current system (CCS) supports a wide array of ecosystem services with hypoxia historically occurring in near-bottom waters. Limited open ocean data coverage hinders the mechanistic understanding of CCS oxygen variability. By comparing three different models with varying horizontal resolutions, we found that dissolved oxygen (DO) anomalies in the CCS are propagated from shallower coastal areas to the deeper open ocean, where they are advected at a density and velocity consistent with basin-scale circulation. Since DO decreases have been linked to water mass redistribution in the CCS, we conduct a water mass analysis on two of the models and on biogeochemical Argo floats that sampled multiple seasonal cycles. We found that high variability in biogeochemical variables (DO and nutrients) seen in regions of low variability of temperature and salinity could be linked to water mass mixing, as some of the water masses considered had higher gradients in biogeochemical variables compared to physical variables. Additional DO observations are needed, therefore, to further understand circulation changes in the CCS. We suggest that increased DO sampling north of 35˚N and near the shelf break would benefit model initialization and skill assessment, as well as allow for better assessment of the role of equatorial waters in driving DO in the northern CCS.

Every austral spring when Antarctic sea ice melts, favorable growing conditions lead to an intense phytoplankton bloom, which supports much of the local marine ecosystem. Recent studies have found that Antarctic sea ice is predictable several years in advance, suggesting that the spring bloom might exhibit similar predictability. Using a suite of perfect model predictability experiments, we find that November net primary production (NPP) is potentially predictable 7 to 10 years in advance in many Southern Ocean regions. Sea ice extent predictability peaks in late winter, followed by absorbed shortwave radiation and NPP with a 2 to 3 months lag. This seasonal progression of predictability supports our hypothesis that sea ice and light limitation control the inherent predictability of the spring bloom. Our results suggest skillful interannual predictions of NPP may be achievable, with implications for managing fisheries and the marine ecosystem, and guiding conservation policy in the Southern Ocean.

Projecting the effects of climate change on net reef calcium carbonate production is critical to understanding the future impacts on ecosystem function, but prior estimates have not included corals' natural adaptive capacity to such change. Here we estimate how the ability of symbionts to evolve tolerance to heat stress, or for coral hosts to shuffle to favourable symbionts, and their combination, may influence responses to the combined impacts of ocean warming and acidification under three representative concentration pathway (RCP) emissions scenarios (RCP2.6, RCP4.5 and RCP8.5). We show that symbiont evolution and shuffling, both individually and when combined, favours persistent positive net reef calcium carbonate production. However, our projections of future net calcium carbonate production (NCCP) under climate change vary both spatially and by RCP. For example, 19%–35% of modelled coral reefs are still projected to have net positive NCCP by 2050 if symbionts can evolve increased thermal tolerance, depending on the RCP. Without symbiont adaptive capacity, the number of coral reefs with positive NCCP drops to 9%–13% by 2050. Accounting for both symbiont evolution and shuffling, we project median positive NCPP of coral reefs will still occur under low greenhouse emissions (RCP2.6) in the Indian Ocean, and even under moderate emissions (RCP4.5) in the Pacific Ocean. However, adaptive capacity will be insufficient to halt the transition of coral reefs globally into erosion by 2050 under severe emissions scenarios (RCP8.5).

Deposition of mineral dust plays an important role in upper-ocean biogeochemical processes, particularly by delivering iron to iron-limited regions. Here we examine the impact of dynamically changing iron deposition on tropical Pacific Ocean biogeochemistry in fully coupled earth system model projections under several emissions scenarios. Projected end-of-21st-century increases in central tropical Pacific dust and iron deposition strengthen with increasing emissions/radiative forcing, and are aligned with projected soil moisture decreases in adjacent land areas and precipitation increases over the equatorial Pacific. Increased delivery of soluble iron results in a reduction in, and eastward contraction of, equatorial Pacific phytoplankton iron limitation and shifts primary production and particulate organic carbon flux projections relative to a high emissions projection (SSP5-8.5) wherein soluble iron deposition is prescribed as a static climatology. These results highlight modeling advances in representing coupled land-air-sea interactions to project basin-scale patterns of ocean biogeochemical change.

As ocean Carbon Dioxide Removal techniques are being considered, it is critical that they be evaluated against our scientific understanding of the global biological carbon pump. In a recent paper Nowicki et al. (2022, https://doi.org/10.1029/2021GB007083) provide an innovative and comprehensive breakdown of the different mechanistic pathways of carbon sequestration through the present-day biological pump but then speculate that “These results suggest that ocean carbon storage will weaken as the oceans stratify and the subtropical gyres expand due to anthropogenic climate change.” Essentially, the authors combine their steady state result that oligotrophic subtropical gyres have lower residence times than other areas with the climate change result of these areas increasing under climate warming and extrapolate—assuming “all else is equal”—that the overall ocean will suffer a reduction in carbon sequestration efficiency. Expressing global changes in carbon sequestered by the ocean's biological pump as the summation of local changes in the sequestered carbon, timescale of return to the surface, and biogeographical area, I discuss how all three terms are tightly coupled, and summarize decades of climate change modeling consistently indicating that the global scale physical sequestration response is an increase - in opposition of what one would infer from changes in subtropical area alone.

There is an urgent need for large ensemble climate models with high resolution and fidelity as nations consider local climate mitigation and adaptation efforts for energy efficiency and resource transitioning.

Stratospheric injections of sulfur dioxide from major volcanic eruptions perturb the Earth's global radiative balance and dominate variability in stratospheric sulfur loading. The atmospheric component of the GFDL Earth System Model (ESM4.1) uses a bulk aerosol scheme and previously prescribed the distribution of aerosol optical properties in the stratosphere. To quantify volcanic contributions to the stratospheric sulfur cycle and the resulting climate impact, we modified ESM4.1 to simulate stratospheric sulfate aerosols prognostically. Driven by explicit volcanic emissions of aerosol precursors and non-volcanic sources, we conduct ESM4.1 simulations from 1989 to 2014, with a focus on the Mt. Pinatubo eruption. We evaluate our interactive representation of the stratospheric sulfur cycle against data from Moderate Resolution Imaging Spectroradiometer, Multi-angle Imaging SpectroRadiometer, Advanced Very High Resolution Radiometer, High Resolution Infrared Radiation Sounder, and Stratospheric Aerosol and Gas Experiment II. To assess the key processes associated with volcanic aerosols, we performed a sensitivity analysis of sulfate burden from the Mt. Pinatubo eruption by varying injection heights, emission amount, and stratospheric sulfate's dry effective radius. We find that the simulated stratospheric sulfate mass burden and aerosol optical depth in the model are sensitive to these parameters, especially volcanic SO2 injection height, and the optimal combination of parameters depends on the metric we evaluate.

A historical dataset of river chemistry and discharge is presented for 140 monitoring sites along the US East Coast, the Gulf of Mexico, and the US West Coast from 1950 to 2022. The dataset, referred to here as River Chemistry for the U.S. Coast (RC4USCoast), is mostly derived from the Water Quality Database of the US Geological Survey (USGS) but also includes river discharge from the USGS's Surface-Water Monthly Statistics for the Nation and the U.S. Army Corps of Engineers. RC4USCoast provides monthly time series as well as long-term averaged monthly climatological patterns for 21 variables including alkalinity and dissolved inorganic carbon concentration. It is mainly intended as a data product for regional ocean biogeochemical models and carbonate chemistry studies in the US coastal regions. Here we present the method to derive RC4USCoast and briefly describe the rivers' carbonate chemistry patterns. The dataset is publicly available at https://doi.org/10.25921/9jfw-ph50 (Gomez et al., 2022).

Salpa thompsoni is an important grazer in the Southern Ocean. Their abundance in the western Antarctic Peninsula is highly variable, varying by up to 5000-fold inter-annually. Here, we use a particle-tracking model to simulate the potential dispersal of salp populations from a source location in the Antarctic Circumpolar Current (ACC) to the Palmer Long Term Ecological Research (PAL LTER) study area. Tracking simulations are run from 1998 to 2015, and compared against both a stationary salp population model simulated at the PAL LTER study area and observations from the PAL LTER program. The tracking simulation was able to recreate closely the long-term trend and the higher abundances at the slope stations. The higher abundances observed at slope stations are likely due to the advection of salp populations from a source location in the ACC, highlighting the significant role of water mass circulation in the distribution and abundance of Southern Ocean salp populations.

Accurately predicting future ocean acidification (OA) conditions is crucial for advancing OA research at regional and global scales, and guiding society's mitigation and adaptation efforts. This study presents a new model-data fusion product covering 10 global surface OA indicators based on 14 Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), along with three recent observational ocean carbon data products. The indicators include fugacity of carbon dioxide, pH on total scale, total hydrogen ion content, free hydrogen ion content, carbonate ion content, aragonite saturation state, calcite saturation state, Revelle Factor, total dissolved inorganic carbon content, and total alkalinity content. The evolution of these OA indicators is presented on a global surface ocean 1° × 1° grid as decadal averages every 10 years from preindustrial conditions (1750), through historical conditions (1850–2010), and to five future Shared Socioeconomic Pathways (2020–2100): SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. These OA trajectories represent an improvement over previous OA data products with respect to data quantity, spatial and temporal coverage, diversity of the underlying data and model simulations, and the provided SSPs. The generated data product offers a state-of-the-art research and management tool for the 21st century under the combined stressors of global climate change and ocean acidification.

Estimating global river solids, nitrogen (N), and phosphorus (P), in both quantity and composition, is necessary for understanding the development and persistence of many harmful algal blooms and hypoxic events. This requires a comprehensive freshwater model that can resolve intertwined algae, solid, and nutrient dynamics, yet previous global watershed models do not mechanistically resolve instream biogeochemical processes. Here we develop a global, spatially explicit, process-based, Freshwater Algae, Nutrient, and Solid cycling and Yields (FANSY) model and incorporate it within the Land Model LM3. The resulting model, LM3-FANSY, explicitly resolves interactions between algae, N, P, and solid dynamics in rivers and lakes at 1 degree spatial and 30 minute temporal resolution. Simulated solids, N, and P in multiple forms (particulate/dissolved, organic/inorganic) agree well with measurement-based yield (kg km−2 yr−1), load (kt yr−1), and concentration (mg l−1) estimates across world major rivers. Furthermore, simulated global river loads of suspended solid, N, and P in different forms to the coastal ocean are consistent with published ranges. River N loads are estimated to be approximately equally distributed among forms with particulate organic, dissolved organic, and dissolved inorganic N accounting for 37 %, 34 %, and 30 % respectively. For river P load estimates, particulate P, which includes both organic and sorbed inorganic forms, is the most abundant form (58 %), followed by dissolved inorganic and organic P (32 % and 10 %). Analyses of model results and sensitivity to components, parameters, and inputs suggest that the fidelity of simulated river nutrient loads and N : P ratios with observation-based estimates could be improved markedly with better global estimates of nutrient inputs to rivers, including soil and litter runoff, wastewater, and weathering. Sensitivity analyses further demonstrate the role of algal dynamics in controlling the ratios of inorganic and organic nutrient forms. LM3-FANSY can serve as a baseline for linking global terrestrial and ocean biogeochemistry in next generation Earth System Models aimed at understanding the effects of terrestrial perturbations on coastal eutrophication under unprecedented socioeconomic and climate changes, where novel conditions challenge empirical approaches. Continued model enhancements will focus on the inclusion of terrestrial P dynamics, freshwater carbon and alkalinity dynamics, and anthropogenic hydraulic controls.

Ocean alkalinity is critical to the uptake of atmospheric carbon in surface waters and provides buffering capacity towards the associated acidification. However, unlike dissolved inorganic carbon (DIC), alkalinity is not directly impacted by anthropogenic carbon emissions. Within the context of projections of future ocean carbon uptake and potential ecosystem impacts, especially through Coupled Model Intercomparison Projects (CMIPs), the representation of alkalinity and the main driver of its distribution in the ocean interior, the calcium carbonate cycle, have often been overlooked. Here we track the changes from CMIP5 to CMIP6 with respect to the Earth system model (ESM) representation of alkalinity and the carbonate pump which depletes the surface ocean in alkalinity through biological production of calcium carbonate and releases it at depth through export and dissolution. We report an improvement in the representation of alkalinity in CMIP6 ESMs relative to those in CMIP5, with CMIP6 ESMs simulating lower surface alkalinity concentrations, an increased meridional surface gradient and an enhanced global vertical gradient. This improvement can be explained in part by an increase in calcium carbonate (CaCO3) production for some ESMs, which redistributes alkalinity at the surface and strengthens its vertical gradient in the water column. We were able to constrain a particulate inorganic carbon (PIC) export estimate of 44–55 Tmol yr−1 at 100 m for the ESMs to match the observed vertical gradient of alkalinity. Reviewing the representation of the CaCO3 cycle across CMIP5/6, we find a substantial range of parameterizations. While all biogeochemical models currently represent pelagic calcification, they do so implicitly, and they do not represent benthic calcification. In addition, most models simulate marine calcite but not aragonite. In CMIP6, certain model groups have increased the complexity of simulated CaCO3 production, sinking, dissolution and sedimentation. However, this is insufficient to explain the overall improvement in the alkalinity representation, which is therefore likely a result of marine biogeochemistry model tuning or ad hoc parameterizations. Although modellers aim to balance the global alkalinity budget in ESMs in order to limit drift in ocean carbon uptake under pre-industrial conditions, varying assumptions related to the closure of the budget and/or the alkalinity initialization procedure have the potential to influence projections of future carbon uptake. For instance, in many models, carbonate production, dissolution and burial are independent of the seawater saturation state, and when considered, the range of sensitivities is substantial. As such, the future impact of ocean acidification on the carbonate pump, and in turn ocean carbon uptake, is potentially underestimated in current ESMs and is insufficiently constrained.

We present the development and evaluation of MOM6-COBALT-NWA12 version 1.0, a 1/12∘ model of ocean dynamics and biogeochemistry in the northwest Atlantic Ocean. This model is built using the new regional capabilities in the MOM6 ocean model and is coupled with the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) biogeochemical model and Sea Ice Simulator version-2 (SIS2) sea ice model. Our goal was to develop a model to provide information to support living-marine-resource applications across management time horizons from seasons to decades. To do this, we struck a balance between a broad, coastwide domain to simulate basin-scale variability and capture cross-boundary issues expected under climate change; a high enough spatial resolution to accurately simulate features like the Gulf Stream separation and advection of water masses through finer-scale coastal features; and the computational economy required to run the long simulations of multiple ensemble members that are needed to quantify prediction uncertainties and produce actionable information. We assess whether MOM6-COBALT-NWA12 is capable of supporting the intended applications by evaluating the model with three categories of metrics: basin-wide indicators of the model's performance, indicators of coastal ecosystem variability and the regional ocean features that drive it, and model run times and computational efficiency. Overall, both the basin-wide and the regional ecosystem-relevant indicators are simulated well by the model. Where notable model biases and errors are present in both types of indicator, they are mainly consistent with the challenges of accurately simulating the Gulf Stream separation, path, and variability: for example, the coastal ocean and shelf north of Cape Hatteras are too warm and salty and have minor biogeochemical biases. During model development, we identified a few model parameters that exerted a notable influence on the model solution, including the horizontal viscosity, mixed-layer restratification, and tidal self-attraction and loading, which we discuss briefly. The computational performance of the model is adequate to support running numerous long simulations, even with the inclusion of coupled biogeochemistry with 40 additional tracers. Overall, these results show that this first version of a regional MOM6 model for the northwest Atlantic Ocean is capable of efficiently and accurately simulating historical basin-wide and regional mean conditions and variability, laying the groundwork for future studies to analyze this variability in detail, develop and improve parameterizations and model components to better capture local ocean features, and develop predictions and projections of future conditions to support living-marine-resource applications across timescales.

For about 2 decades, oceanographers have been installing oxygen sensors on Argo profiling floats to be deployed throughout the world ocean, with the stated objective of better constraining trends and variability in the ocean's inventory of oxygen. Until now, measurements from these Argo-float-mounted oxygen sensors have been mainly used for localized process studies on air–sea oxygen exchange, upper-ocean primary production, biological pump efficiency, and oxygen minimum zone dynamics. Here, we present a new four-dimensional gridded product of ocean interior oxygen, derived via machine learning algorithms trained on dissolved oxygen observations from Argo-float-mounted sensors and discrete measurements from ship-based surveys and applied to temperature and salinity fields constructed from the global Argo array. The data product is called GOBAI-O2, which stands for Gridded Ocean Biogeochemistry from Artificial Intelligence – Oxygen (Sharp et al., 2022; https://doi.org/10.25921/z72m-yz67); it covers 86 % of the global ocean area on a 1∘ × 1∘ (latitude × longitude) grid, spans the years 2004–2022 with a monthly resolution, and extends from the ocean surface to a depth of 2 km on 58 levels. Two types of machine learning algorithms – random forest regressions and feed-forward neural networks – are used in the development of GOBAI-O2, and the performance of those algorithms is assessed using real observations and simulated observations from Earth system model output. Machine learning represents a relatively new method for gap filling ocean interior biogeochemical observations and should be explored along with statistical and interpolation-based techniques. GOBAI-O2 is evaluated through comparisons to the oxygen climatology from the World Ocean Atlas, the mapped oxygen product from the Global Ocean Data Analysis Project and to direct observations from large-scale hydrographic research cruises. Finally, potential uses for GOBAI-O2 are demonstrated by presenting average oxygen fields on isobaric and isopycnal surfaces, average oxygen fields across vertical–meridional sections, climatological seasonal cycles of oxygen averaged over different pressure layers, and globally integrated time series of oxygen. GOBAI-O2 indicates a declining trend in the oxygen inventory in the upper 2 km of the global ocean of 0.79 ± 0.04 % per decade between 2004 and 2022.

Motivated by a need for climate-informed living marine resource management, increased emphasis has been placed on regional end-to-end modeling frameworks designed to project climate impacts on marine ecosystems and evaluate the efficacy of potential management strategies under changing conditions. The ‘Future Seas’ project was initiated with a focus on three fisheries (Pacific sardine, swordfish, and albacore tuna) in the California Current System (CCS). This work leverages a suite of climate, ocean, ecosystem, and economic models to project physical, ecological, and socio-economic change, evaluate management strategies, and quantify uncertainty in model projections. Here we describe the components of the modeling framework, considerations underlying choices made in model development, engagement with stakeholders, and key physical, ecological, and socio-economic results to date, including projections to 2100. Our broad aims are to (i) synthesize a large body of climate and fisheries research that has been conducted, and continues, under the Future Seas umbrella, and (ii) provide insight and recommendations to those pursuing similar efforts for other applications and in other regions. In general, our results indicate that all three species will likely shift their distributions (predominantly poleward) in the future, which impacts accessibility to fishing fleets, spatial management, and quota allocation. For similar integrative climate-to-fisheries projections, we recommend attention is given to: recognizing potential biases arising from differences between the climate products used for ecological model fitting and those used for model projection; how sources of projection uncertainty are prioritized, incorporated, and communicated; and quantitatively linking scenarios – especially socio-economic scenarios – with climate and ecological projections.

1) Subseasonal to decadal ocean forecasting can make significant contributions to achieving effective management of living marine resources in a changing ocean. Most applications rely on indirect proxies, however, often measured at the ocean surface and lacking a direct mechanistic link to the dynamics of marine populations. 2) Here, we take advantage of three-dimensional, dynamical reconstructions and forecasts of ocean biogeochemistry based on a global Earth system model to hindcast and assess the capacity to anticipate fluctuations in the dynamics of bigeye tuna (Thunnus obesus Lowe) in the Pacific Ocean during the last six decades. We reconstructed spatial patterns in catch per unit effort (CPUE) through the combination of physiological indices capturing both habitat preferences and physiological tolerance limits in bigeye tuna. 3) Our analyses revealed a sequence of four distinct regimes characterized by changes in the zonal distribution and average CPUE of bigeye tuna in the Pacific Ocean. Habitat models accounting for basin-wide fluctuations in the thermal structure and oxygen concentration throughout the water column captured interannual fluctuations in CPUE and regime switches that models based solely on surface information were unable to reproduce. Decade-long forecast experiments further suggested that forecasts of three-dimensional biogeochemical information might enable anticipation of fluctuations in bigeye tuna several years ahead. 4) Synthesis and applications. Together, our results reveal the impact of variability of biogeochemical conditions in the ocean interior on the dynamics of bigeye tuna on the Pacific Ocean, raising concerns about the future impact of ocean warming and deoxygenation. The results also lend support to incorporating subsurface biogeochemical information into ecological forecasts to implement efficient dynamic management strategies and promote the sustainable use of marine living resources.

Ocean deoxygenation due to anthropogenic warming represents a major threat to marine ecosystems and fisheries. Challenges remain in simulating the modern observed changes in the dissolved oxygen (O2). Here, we present an analysis of upper ocean (0-700m) deoxygenation in recent decades from a suite of the Coupled Model Intercomparison Project phase 6 (CMIP6) ocean biogeochemical simulations. The physics and biogeochemical simulations include both ocean-only (the Ocean Model Intercomparison Project Phase 1 and 2, OMIP1 and OMIP2) and coupled Earth system (CMIP6 Historical) configurations. We examine simulated changes in the O2 inventory and ocean heat content (OHC) over the past 5 decades across models. The models simulate spatially divergent evolution of O2 trends over the past 5 decades. The trend (multi-model mean and spread) for upper ocean global O2 inventory for each of the MIP simulations over the past 5 decades is 0.03 ± 0.39×1014 [mol/decade] for OMIP1, −0.37 ± 0.15×1014 [mol/decade] for OMIP2, and −1.06 ± 0.68×1014 [mol/decade] for CMIP6 Historical, respectively. The trend in the upper ocean global O2 inventory for the latest observations based on the World Ocean Database 2018 is −0.98×1014 [mol/decade], in line with the CMIP6 Historical multi-model mean, though this recent observations-based trend estimate is weaker than previously reported trends. A comparison across ocean-only simulations from OMIP1 and OMIP2 suggests that differences in atmospheric forcing such as surface wind explain the simulated divergence across configurations in O2 inventory changes. Additionally, a comparison of coupled model simulations from the CMIP6 Historical configuration indicates that differences in background mean states due to differences in spin-up duration and equilibrium states result in substantial differences in the climate change response of O2. Finally, we discuss gaps and uncertainties in both ocean biogeochemical simulations and observations and explore possible future coordinated ocean biogeochemistry simulations to fill in gaps and unravel the mechanisms controlling the O2 changes.

In this study, we investigate the air temperature response to land-use and land-cover change (LULCC; cropland expansion and deforestation) using subgrid land model output generated by a set of CMIP6 model simulations. Our study is motivated by the fact that ongoing land-use activities are occurring at local scales, typically significantly smaller than the resolvable scale of a grid cell in Earth system models. It aims to explore the potential for a multimodel approach to better characterize LULCC local climatic effects. On an annual scale, the CMIP6 models are in general agreement that croplands are warmer than primary and secondary land (psl; mainly forests, grasslands, and bare ground) in the tropics and cooler in the mid–high latitudes, except for one model. The transition from warming to cooling occurs at approximately 40°N. Although the surface heating potential, which combines albedo and latent heat flux effects, can explain reasonably well the zonal mean latitudinal subgrid temperature variations between crop and psl tiles in the historical simulations, it does not provide a good prediction on subgrid temperature for other land tile configurations (crop vs forest; grass vs forest) under Shared Socioeconomic Pathway 5–8.5 (SSP5–8.5) forcing scenarios. A subset of simulations with the CESM2 model reveals that latitudinal subgrid temperature variation is positively related to variation in net surface shortwave radiation and negatively related to variation in the surface energy redistribution factor, with a dominant role from the latter south of 30°N. We suggest that this emergent relationship can be used to benchmark the performance of land surface parameterizations and for prediction of local temperature response to LULCC.

As a key biogeochemical pathway in the marine nitrogen cycle, nitrification (ammonia oxidation and nitrite oxidation) converts the most reduced form of nitrogen – ammonium–ammonia (NH+4–NH3) – into the oxidized species nitrite (NO−2) and nitrate (NO−3). In the ocean, these processes are mainly performed by ammoniaoxidizing archaea (AOA) and bacteria (AOB) and nitrite-oxidizing bacteria (NOB). By transforming nitrogen speciation and providing substrates for nitrogen removal, nitrification affects microbial community structure; marine productivity (including chemoautotrophic carbon fixation); and the production of a powerful greenhouse gas, nitrous oxide (N2O). Nitrification is hypothesized to be regulated by temperature, oxygen, light, substrate concentration, substrate flux, pH and other environmental factors. Although the number of field observations from various oceanic regions has increased considerably over the last few decades, a global synthesis is lacking, and understanding how environmental factors control nitrification remains elusive. Therefore, we have compiled a database of nitrification rates and nitrifier abundance in the global ocean from published literature and unpublished datasets. This database includes 2393 and 1006 measurements of ammonia oxidation and nitrite oxidation rates and 2242 and 631 quantifications of ammonia oxidizers and nitrite oxidizers, respectively. This community effort confirms and enhances our understanding of the spatial distribution of nitrification and nitrifiers and their corresponding drivers such as the important role of substrate concentration in controlling nitrification rates and nitrifier abundance. Some conundrums are also revealed, including the inconsistent observations of light limitation and high rates of nitrite oxidation reported from anoxic waters. This database can be used to constrain the distribution of marine nitrification, to evaluate and improve biogeochemical models of nitrification, and to quantify the impact of nitrification on ecosystem functions like marine productivity and N2O production. This database additionally sets a baseline for comparison with future observations and guides future exploration (e.g., measurements in the poorly sampled regions such as the Indian Ocean and method comparison and/or standardization). The database is publicly available at the Zenodo repository: https://doi.org/10.5281/zenodo.8355912 (Tang et al., 2023).

The framework of Representative Key Risks (RKRs) has been adopted by the Intergovernmental Panel on Climate Change Working Group II (WGII) to categorize, assess and communicate a wide range of regional and sectoral key risks from climate change. These are risks expected to become severe due to the potentially detrimental convergence of changing climate conditions with the exposure and vulnerability of human and natural systems. Other papers in this special issue treat each of eight RKRs holistically by assessing their current status and future evolution as a result of this convergence. However, in these papers, such assessment cannot always be organized according to a systematic gradation of climatic changes. Often the big-picture evolution of risk has to be extrapolated from either qualitative effects of “low”, “medium” and “high” warming, or limited/focused analysis of the consequences of particular mitigation choices (e.g., benefits of limiting warming to 1.5 or 2C), together with consideration of the socio-economic context and possible adaptation choices. In this study we offer a representation – as systematic as possible given current literature and assessments – of the future evolution of the hazard components of RKRs. We identify the relevant hazards for each RKR, based upon the WGII authors’ assessment, and we report on their current state and expected future changes in magnitude, intensity and/or frequency, linking these changes to Global Warming Levels (GWLs) to the extent possible. We draw on the assessment of changes in climatic impact-drivers relevant to RKRs described in the 6th Assessment Report by Working Group I supplemented when needed by more recent literature. For some of these quantities - like regional trends in oceanic and atmospheric temperature and precipitation, some heat and precipitation extremes, permafrost thaw and Northern Hemisphere snow cover - a strong and quantitative relationship with increasing GWLs has been identified. For others - like frequency and intensity of tropical cyclones and extra-tropical storms, and fire weather - that link can only be described qualitatively. For some processes - like the behavior of ice sheets, or changes in circulation dynamics - large uncertainties about the effects of different GWLs remain, and for a few others - like ocean pH and air pollution - the composition of the scenario of anthropogenic emissions is most relevant, rather than the warming reached. In almost all cases, however, the basic message remains that every small increment in CO2 concentration in the atmosphere and associated warming will bring changes in climate phenomena that will contribute to increasing risk of impacts on human and natural systems, in the absence of compensating changes in these systems’ exposure and vulnerability, and in the absence of effective adaptation. Our picture of the evolution of RKR-relevant climatic impact-drivers complements and enriches the treatment of RKRs in the other papers in at least two ways: by filling in their often only cursory or limited representation of the physical climate aspects driving impacts, and by providing a fuller representation of their future potential evolution, an important component – if never the only one – of the future evolution of risk severity.

Theory predicts fish community biomass to decline with increasing temperature due to higher metabolic losses resulting in less efficient energy transfer in warm-water food webs. However, whether these metabolic predictions explain observed macroecological patterns in fish community biomass is virtually unknown. Here, we test these predictions by examining the variation in demersal fish biomass across productive shelf regions.

Land–atmosphere (L–A) interactions encompass the co-evolution of the land surface and overlying planetary boundary layer, primarily during daylight hours. However, many studies have been conducted using monthly or entire-day mean time series due to the lack of subdaily data. It is unclear whether the inclusion of nighttime data alters the assessment of L–A coupling or obscures L–A interactive processes. To address this question, we generate monthly (M), entire-day mean (E), and daytime-only mean (D) data based on the ERA5 (5th European Centre for Medium-Range Weather Forecasts reanalysis) product and evaluate the strength of L–A coupling through two-legged metrics, which partition the impact of the land states on surface fluxes (the land leg) from the impact of surface fluxes on the atmospheric states (the atmospheric leg). Here we show that the spatial patterns of strong L–A coupling regions among the M-, D-, and E-based diagnoses can differ by more than 80 %. The signal loss from E- to M-based diagnoses is determined by the memory of local L–A states. The differences between E- and D-based diagnoses can be driven by physical mechanisms or averaging algorithms. To improve understanding of L–A interactions, we call attention to the urgent need for more high-frequency data from both simulations and observations for relevant diagnoses. Regarding model outputs, two approaches are proposed to resolve the storage dilemma for high-frequency data: (1) integration of L–A metrics within Earth system models, and (2) producing alternative daily datasets based on different averaging algorithms.

Historical precipitation and temperature trends and variations over global land regions are compared with simulations of two climate models focusing on grid points with substantial observational coverage from the early twentieth century. Potential mechanisms for the differences between modeled and observed trends are investigated using subsets of historical forcings, including ones using only anthropogenic greenhouse gases or aerosols, and simulations forced with the observed sea surface temperature and sea ice distribution. For century-scale (1915–2014) precipitation trends, underestimated increasing or unrealistic decreasing trends are found in the models over the extratropical Northern Hemisphere. The temporal evolution of key discrepancies between the observations and simulations indicates that 1) for averages over 15°–45°N, while there is not a significant trend in observations, both models simulate reduced precipitation from 1940 to 2014, and 2) for 45°–80°N observations suggest sizable precipitation increases while models do not show a significant increase, particularly during ∼1950–80. The timing of differences between models and observations suggests a key role for aerosols in these dry trend biases over the extratropical Northern Hemisphere. Additionally, 3) for 15°S–15°N the observed multidecadal decrease over tropical west Africa (1950–80) is only roughly captured by simulations forced with observed sea surface temperature; additionally, 4) in the all-forcing runs, the model with higher global climate sensitivity simulates increasing trends of temperature and precipitation over lands north of 45°N that are significantly stronger than the lower-sensitivity model and more consistent with the observed increases. Thus, underestimated greenhouse gas–induced warming—particularly in the lower sensitivity model—may be another important factor, besides aerosols, contributing to the modeled biases in precipitation trends.

Parameterizing incident solar radiation over complex topography regions in Earth system models (ESMs) remains a challenging task. In ESMs, downward solar radiative fluxes at the surface are typically computed using plane-parallel radiative transfer schemes, which do not explicitly account for the effects of a three-dimensional topography, such as shading and reflections. To improve the representation of these processes, we introduce and test a parameterization of radiation–topography interactions tailored to the Geophysical Fluid Dynamics Laboratory (GFDL) ESM land model. The approach presented here builds on an existing correction scheme for direct, diffuse, and reflected solar irradiance terms over three-dimensional terrain. Here we combine this correction with a novel hierarchical multivariate clustering algorithm that explicitly describes the spatially varying downward irradiance over mountainous terrain. Based on a high-resolution digital elevation model, this combined method first defines a set of sub-grid land units (“tiles”) by clustering together sites characterized by similar terrain–radiation interactions (e.g., areas with similar slope orientation, terrain, and sky view factors). Then, based on terrain parameters characteristic for each tile, correction terms are computed to account for the effects of local 3D topography on shortwave radiation over each land unit. We develop and test this procedure based on a set of Monte Carlo ray-tracing simulations approximating the true radiative transfer process over three-dimensional topography. Domains located in three distinct geographic regions (Alps, Andes, and Himalaya) are included in this study to allow for independent testing of the methodology over surfaces with differing topographic features. We find that accounting for the sub-grid spatial variability of solar irradiance originating from interactions with complex topography is important as these effects led to significant local differences with respect to the plane-parallel case, as well as with respect to grid-cell-scale average topographic corrections. We further quantify the importance of the topographic correction for a varying number of terrain clusters and for different radiation terms (direct, diffuse, and reflected radiative fluxes) in order to inform the application of this methodology in different ESMs with varying sub-grid tile structure. We find that even a limited number of sub-grid units such as 10 can lead to recovering more than 60 % of the spatial variability of solar irradiance over a mountainous area.

Global ocean oxygen loss is projected to persist in the future, but Earth system models (ESMs) have not yet provided a consistent picture of how it will influence the largest oxygen minimum zone (OMZ) in the tropical Pacific. We examine the change in the Pacific OMZ volume in an ensemble of ESMs from the CMIP6 archive, considering a broad range of oxygen (O2) thresholds relevant to biogeochemical cycles and ecosystems (5–160 µmol/kg). Despite OMZ biases in the historical period of the simulations, the ESM ensemble projections consistently fall into three regimes across ESMs: an expansion of low oxygenated waters (+0.8 [0.6, 1.0] × 1016 m3/century for O2 ≤ 120 µmol/kg, ESM median and interquartile range); a slight contraction of the OMZ core although more uncertain across ESMs (−0.1 [−0.5, 0.0] × 1016 m3/century for O2 ≤ 20 µmol/kg); and at the transition from contraction to expansion regimes, a spatial redistribution but near-zero change in the volume of hypoxic waters (0.0 [−0.3, +0.1] × 1016 m3/century for O2 ≤ 60 µmol/kg). Changes in circulation and biology dictate the shift from expansion to contraction. Specifically, reduced subtropical ventilation controls the expansion of low oxygenated waters, while a combination of circulation and biological changes explains the contraction of the core (likely changes in mixing, reduced intermediate ventilation and oxygen demand). Increased model complexity (e.g., ecosystem dynamics and equatorial circulation) likely stabilize the OMZ response, suggesting that future changes might lie in the lower bound of current projections. The expansion of low oxygenated waters which delimit the optimum habitat of numerous marine species would severely impact ecosystems and ecosystem services.

Sudden shifts in marine plankton communities in response to environmental changes are of special concern because of their low predictability and high potential impacts on ocean ecosystems. We explored how anthropogenic climate change influences the spatial extent and frequency of changepoints in plankton populations by comparing the behavior of a plankton community in a coupled Earth system model under pre-industrial, historical 20th century, and projected 21st century forcing. The ocean areas where surface ocean temperature, nutrient concentrations, and different plankton types exhibited changepoints expanded over time. In contrast, regional hotspots where changepoints occur frequently largely disappeared. Heterotrophy and larger organism sizes were associated with more changepoints. In the pre-industrial and 20th century, plankton changepoints were associated with shifts in physical fronts, and more often with changepoints for iron and silicate than for nitrate and phosphate. In the 21st century, climate change disrupts these interannual-variability-driven changepoint patterns. Together, our results suggest anthropogenic climate change may drive less frequent but more widespread changepoints simultaneously affecting several components of pelagic food webs.

The northeast United States Atlantis model (NEUSv2) is an end-to-end ecosystem model that can simulate biogeochemical, ecological, fishery, management, and socio-economic processes within marine ecosystems. As a major update to the original model, NEUSv2 includes changes to the model's functional group definitions and forcing data. NEUSv2 is the first Atlantis model to use a satellite-ocean-color-derived phytoplankton size class model that was tuned specifically for the region to force marine primary production. Additionally, physical ocean variables (currents, temperature, and salinity) were updated using a high-resolution global ocean reanalysis. Despite its coarse resolution, NEUSv2 was capable of reproducing the broad spatial patterns seen in the physical and biological forcing sources, with the exception of some circulation features. NEUSv2 produced plausible zooplankton and planktivore biomass, a stable lower trophic food web, and recent trends in zooplankton biomass. NEUSv2 meets calibration criteria for the persistence and long-term stability of functional group biomass. Given the success of this new Atlantis forcing approach, we detail the observations and challenges regarding spatial scale-related processes, data assimilation, and biological calibration. We also discuss possible tradeoffs with model scope, calibration, and the availability of feedback mechanisms. This NEUSv2 hindcast is well suited for exploring ecosystem-level sensitivity to lower trophic processes and for testing alternative biogeochemical forcing. Further developments will improve model performance for higher trophic levels.

Light-absorbing impurities (LAIs) deposited on snow surfaces can accelerate melt by increasing solar radiation absorption through snow darkening and grain metamorphism. To improve the predictive capability of the global impact of LAIs on the surface energy balance, we have developed a simple snow parameterization - Snow LAI Redistribution (SLAIR) to estimate the snow albedo based on the concentration of LAIs and grain size. The parameterization can be run as a standalone model constrained by temperature, snowfall, ablation, and aerosol deposition or be implemented into large scale models. The concentration of LAIs at the snow surface depends on aerosol deposition and vertical redistribution during melt. To represent the uncertainties associated with different melting regimes, two approaches were considered, one assuming all the meltwater is contributed from the top of the snowpack (“surface melt mode”) and one assuming each snow layer contributes the same fraction of the mass of the total melt (“uniform melt mode”). The parameterization is evaluated as a standalone model against publicly available data at the French Alps using observational inputs. The parameterization captured the temporal variations in grain size but not the detailed variabilities. For concentration of LAIs and visible albedo, both melting modes agree reasonably well with observations during the accumulation phase but only the surface melt model reproduced observations with good agreement. Overall, the simple snow parameterization can estimate the near-surface concentration of LAIs, grain size and visible albedo within a reasonable range. Further developments are required to minimize uncertainties, especially for relatively warm and humid regions.

Climate models project an intensification of the wintertime North Atlantic Ocean storm track, over its downstream region, by the end of this century. Previous studies have suggested that ocean–atmosphere coupling plays a key role in this intensification, but the precise role of the different components of the coupling has not been explored and quantified. In this paper, using a hierarchy of ocean coupling experiments, we isolate and quantify the respective roles of thermodynamic (changes in surface heat fluxes) and dynamic (changes in ocean heat flux convergence) ocean coupling in the projected intensification of North Atlantic transient eddy kinetic energy (TEKE). We show that dynamic coupling accounts for nearly all of the future TEKE strengthening as it overcomes the much smaller effect of surface heat flux changes to weaken the TEKE. We further show that by reducing the Arctic amplification in the North Atlantic, ocean heat flux convergence increases the meridional temperature gradient aloft, causing a larger eddy growth rate and resulting in the strengthening of North Atlantic TEKE. Our results stress the importance of better monitoring and investigating the changes in ocean heat transport, for improving climate change adaptation strategies.

Worldwide, warming ocean temperatures have contributed to extreme harmful algal bloom events and shifts in phytoplankton species composition. In 2016 in the Gulf of Maine (GOM), an unprecedented Pseudo-nitzschia bloom led to the first domoic-acid induced shellfishery closures in the region. Potential links between climate change, warming temperatures, and the GOM Pseudo-nitzschia assemblage, however, remain unexplored. In this study, a global climate change projection previously downscaled to 7-km resolution for the Northwest Atlantic was further refined with a 1–3-km resolution simulation of the GOM to investigate the effects of climate change on HAB dynamics. A 25-year time slice of projected conditions at the end of the 21st century (2073–2097) was compared to a 25-year hindcast of contemporary ocean conditions (1994–2018) and analyzed for changes to GOM inflows, transport, and Pseudo-nitzschia australis growth potential. On average, climate change is predicted to lead to increased temperatures, decreased salinity, and increased stratification in the GOM, with the largest changes occurring in the late summer. Inflows from the Scotian Shelf are projected to increase, and alongshore transport in the Eastern Maine Coastal Current is projected to intensify. Increasing ocean temperatures will likely make P. australis growth conditions less favorable in the southern and western GOM but improve P. australis growth conditions in the eastern GOM, including a later growing season in the fall, and a longer growing season in the spring. Combined, these changes suggest that P. australis blooms in the eastern GOM could intensify in the 21st century, and that the overall Pseudo-nitzschia species assemblage might shift to warmer-adapted species such as P. plurisecta or other Pseudo-nitzschia species that may be introduced.

Tiny phytoplankton are the base of ocean production and thus critical to carbon storage, carbon fluxes and living marine resources. Now, research suggests that the vertical migration of these organisms provides a previously under-recognized resiliency to climate warming.

Observations and climate models indicate that changes in the seasonal amplitude of sea surface carbon dioxide partial pressure (A-pCO2) are underway and driven primarily by anthropogenic carbon (Cant) accumulation in the ocean. This occurs because pCO2 is more responsive to seasonal changes in physics (including warming) and biology in an ocean that contains more Cant. A-pCO2 changes have the potential to alter annual ocean carbon uptake and contribute to the overall marine carbon cycle feedback. Using the GFDL ESM2M Large Ensemble and a novel analysis framework, we quantify the influence of Cant accumulation on pCO2 seasonal cycles and sea-air CO2 fluxes. Specifically, we reconstruct alternative evolutions of the contemporary ocean state in which the sensitivity of pCO2 to seasonal thermal and biophysical variation is fixed at preindustrial levels, however the background, mean-state pCO2 fully responds to anthropogenic forcing. We find near-global A-pCO2 increases of >100% by 2100, under RCP8.5 forcing, with rising Cant accounting for ∼100% of thermal and ∼50% of nonthermal pCO2 component amplitude changes. The other ∼50% of nonthermal pCO2 component changes are attributed to modeled changes in ocean physics and biology caused by climate change. Cant-induced A-pCO2 changes cause an 8.1 ± 0.4% (ensemble mean ± 1σ) increase in ocean carbon uptake by 2100. This is because greater wintertime wind speeds enhance the impact of wintertime pCO2 changes, which work to increase the ocean carbon sink. Thus, the seasonal ocean carbon cycle feedback works in opposition to the larger, mean-state feedback that reduces ocean carbon uptake by ∼60%.

The extension of seasonal to interannual prediction of the physical climate system to include the marine ecosystem has a great potential to inform marine resource management strategies. Along the east coast of Africa, recent findings suggest that skillful Earth system model (ESM)-based chlorophyll predictions may enable anticipation of fisheries fluctuations. The mechanisms underlying skillful chlorophyll predictions, however, were not identified, eroding confidence in potential adaptive management steps. This study demonstrates that skillful chlorophyll predictions up to two years in advance arise from the successful simulation of westward-propagating off-equatorial Rossby waves in the Indian ocean. Upwelling associated with these waves supplies nutrients to the surface layer for the large coastal areas by generating north- and southward propagating waves at the east African coast. Further analysis shows that the off-equatorial Rossby wave is initially excited by wind stress forcing caused by El Niño/Southern Oscillation-Indian Ocean teleconnections.

Ocean acidification is a consequence of the absorption of anthropogenic carbon emissions and it profoundly impacts marine life. Arctic regions are particularly vulnerable to rapid pH changes due to low ocean buffering capacities and high stratification. Here, an unsupervised machine learning methodology is applied to simulations of surface Arctic acidification from two state-of-the-art coupled climate models. We identify four sub-regions whose boundaries are influenced by present-day and projected sea ice patterns. The regional boundaries are consistent between the models and across lower (SSP2-4.5) and higher (SSP5-8.5) carbon emissions scenarios. Stronger trends toward corrosive surface waters in the central Arctic Ocean are driven by early summer warming in regions of annual ice cover and late summer freshening in regions of perennial ice cover. Sea surface salinity and total alkalinity reductions dominate the Arctic pH changes, highlighting the importance of objective sub-regional identification and subsequent analysis of surface water mass properties.

The El Niño-Southern Oscillation (ENSO) strongly influences phytoplankton in the tropical Pacific, with El Niño conditions suppressing productivity in the equatorial Pacific (EP) and placing nutritional stresses on marine ecosystems. The Geophysical Fluid Dynamics Laboratory's (GFDL) Earth System Model version 4.1 (ESM4.1) captures observed ENSO-chlorophyll patterns (r = 0.57) much better than GFDL's previous ESM2M (r = 0.23). Most notably, the observed post-El Niño “chlorophyll rebound” is substantially improved in ESM4.1 (r = 0.52). We find that an anomalous increase in iron propagation from western Pacific (WP) subsurface to the cold tongue via the equatorial undercurrent (EUC) and subsequent post-El Niño surfacing, unresolved in ESM2M, is the primary driver of chlorophyll rebound. We also find that this chlorophyll rebound is augmented by high post-El Niño dust-iron deposition anomalies in the eastern EP. This post-El Niño chlorophyll rebound provides a previously unrecognized source of marine ecosystem resilience independent from the La Niña that sometimes follows.

For over two decades, satellite ocean color missions have revealed spatio-temporal variations in marine chlorophyll. Seasonal cycles and interannual changes of the physical environment drive the nutrient and chlorophyll variations. In order to identify contributions of seasonal and interannual components on chlorophyll, the present study investigates total chlorophyll variance (TCV) of a 24 year records (September 1997 to December 2021) across satellite generations. First-order contributions of the seasonal cycle in the mid-latitude (25°–35°) oceans in the Northern and Southern Hemispheres explain 59.5% and 69.9% of TCV, respectively. In contrast, the contribution of seasonal cycle only explain 30.9% in the tropical oceans (20°N–20°S). Both seasonal cycle- and climate-driven variability (26.3%) explain 57.2% on TCV in the tropical oceans. A multiple linear regression model was forced by instantaneous and delayed effects of oceanic memory of eight climate indices based on sea surface temperature anomalies to reconstruct chlorophyll anomalies. Delayed climate effects generally boost the anomaly correlation coefficients (ACC) between the observed and reconstructed chlorophyll timeseries (ACC skills: 0.64 to 0.72 in the Indian Ocean, 0.74 to 0.82 in off-equatorial Northern Pacific, and 0.58 to 0.71 in the off-equatorial Southern Pacific). Such delayed climate effects provide a source of predicted chlorophyll ACC (ACC_predic) skills one season ahead in some ocean regions (ACC_predic skill: 0.63 in the overall tropical ocean, 0.67 in the tropical Pacific, and 0.60 in the Indian Ocean). The attribution of chlorophyll variability indicates promising avenues for improving marine ecosystem predictions with Earth system models by incorporating delayed climate effects.

The pelagic tunicates, gelatinous zooplankton that include salps, doliolids, and appendicularians, are filter feeding grazers thought to produce a significant amount of particulate organic carbon (POC) detritus. However, traditional sampling methods (i.e., nets), have historically underestimated their abundance, yielding an overall underappreciation of their global biomass and contribution to ocean biogeochemical cycles relative to crustacean zooplankton. As climate change is projected to decrease the average plankton size and POC export from traditional plankton food webs, the ecological and biogeochemical role of pelagic tunicates may increase; yet, pelagic tunicates were not resolved in the previous generation of global earth system climate projections. Here we present a global ocean study using a coupled physical-biogeochemical model to assess the impact of pelagic tunicates in the pelagic food web and biogeochemical cycling. We added two tunicate groups, a large salp/doliolid and a small appendicularian to the NOAA-GFDL Carbon, Ocean Biogeochemistry, and Lower Trophics version 2 (COBALTv2) model, which was originally formulated to represent carbon flows to crustacean zooplankton. The new GZ-COBALT simulation was able to simultaneously satisfy new pelagic tunicate biomass constraints and existing ecosystem constraints, including crustacean zooplankton observations. The model simulated a global tunicate biomass of 0.10 Pg C, annual tunicate production of 0.49 Pg C y-1 in the top 100 m, and annual tunicate detritus production of 0.98 Pg C y-1 in the top 100 m. Tunicate-mediated export flux was 0.71 Pg C y-1, representing 11% of the total export flux past 100 m. Overall export from the euphotic zone remained largely constant, with the GZ-COBALT pe-ratio only increasing 5.3% (from 0.112 to 0.118) compared to the COBALTv2 control. While the bulk of the tunicate-mediated export production resulted from the rerouting of phytoplankton- and mesozooplankton-mediated export, tunicates also shifted the overall balance of the upper oceans away from recycling and towards export. Our results suggest that pelagic tunicates play important trophic roles in both directly competing with microzooplankton and indirectly shunting carbon export away from the microbial loop.

Tropical forests contribute a major sink for anthropogenic carbon emissions essential to slowing down the buildup of atmospheric CO2 and buffering climate change impacts. However, the response of tropical forests to more frequent weather extremes and long-recovery disturbances like fires remains uncertain. Analyses of field data and ecological theory raise concerns about the possibility of the Amazon crossing a tipping point leading to catastrophic tropical forest loss. In contrast, climate models consistently project an enhanced tropical sink. Here, we show a heterogeneous response of Amazonian carbon stocks in GFDL-ESM4.1, an Earth System Model (ESM) featuring dynamic disturbances and height-structured tree–grass competition. Enhanced productivity due to CO2 fertilization promotes increases in forest biomass that, under low emission scenarios, last until the end of the century. Under high emissions, positive trends reverse after 2060, when simulated fires prompt forest loss that results in a 40% decline in tropical forest biomass by 2100. Projected fires occur under dry conditions associated with El Niño Southern Oscillation and the Atlantic Multidecadal Oscillation, a response observed under current climate conditions, but exacerbated by an overall decline in precipitation. Following the initial disturbance, grassland dominance promotes recurrent fires and tree competitive exclusion, which prevents forest recovery. EC-Earth3-Veg, an ESM with a dynamic vegetation model of similar complexity, projected comparable wildfire forest loss under high emissions but faster postfire recovery rates. Our results reveal the importance of complex nonlinear responses to assessing climate change impacts and the urgent need to research postfire recovery and its representation in ESMs.

North Pacific albacore (Thunnus alalunga) is a commercially important tuna species known to undertake extensive migratory movements between nearshore waters of the California Current and offshore environments in the central Pacific. However, these migration behaviors are highly variable, with some individuals traveling thousands of kilometers within a season, and others largely resident in the southern California Current throughout the year. In this study, we use data from 33 archival-tagged albacore (released between 2003 and 2011) to examine the movements, physiology and ecology of tuna following different migratory pathways. We used direct measurements of body temperature and ambient water temperature from internal archival tags to estimate energy intake via the Heat Increment of Feeding (HIF), the increased internal heat production associated with digestion of a meal. Our results indicate that HIF was variable in space and time, but it was highest for individuals foraging in the offshore North Pacific Transition Zone and southern California Current during spring and summer, and lowest in the Transition Zone in fall. None of the migratory strategies examined appeared to confer consistently higher energetic benefits than the others. Fish remaining resident in the southern California Current year-round incurred lower migration costs, and could access favorable foraging conditions off Baja California in spring and summer. In contrast, fish which undertook longer migrations had much higher energetic costs during periods of faster transit times, but were able to reach highly productive foraging areas in the central and western Pacific. HIF was generally higher in larger fish, and when ambient temperatures were cooler, but was not strongly correlated with other environmental covariates. Our analyses offer new avenues for studying the physiology of wild tuna populations, and can complement diet and isotopic studies to further understanding of fish ecology.

We test whether skillful 35-day probabilistic forecasts of estuarine sea surface temperature (SST) are possible and whether these forecasts could potentially be used to reduce the economic damages associated with extreme SST events. Using an ensemble of 35-day retrospective forecasts of atmospheric temperature and a simple model that predicts daily mean SST from past SST and forecast atmospheric temperature, we create an equivalent ensemble of retrospective SST forecasts. We compare these SST forecasts with reference forecasts of climatology and damped persistence and find that the SST forecasts are skillful for up to two weeks in the summer. Then, we post-process the forecasts using nonhomogeneous Gaussian regression and assess whether the resulting calibrated probabilistic forecasts are more accurate than the probability implied by the raw model ensemble. Finally, we use an idealized framework to assess whether these probabilistic forecasts can valuably inform decisions to take protective action to mitigate the effects of extreme temperatures and heatwaves. We find that the probabilistic forecasts provide value relative to a naive climatological forecast for 1-2 weeks of lead time, and the value is particularly high in cases where the cost of protection is small relative to the preventable losses suffered when a heatwave occurs. In most cases, the calibrated probabilistic forecasts are also more valuable than deterministic forecasts based on the ensemble mean and naive probabilistic forecasts based on damped persistence. Probabilistic SST forecasts could provide substantial value if applied to adaptively manage the rapid impacts of extreme SSTs, including managing the risks of catch-and-release mortality in fish and Vibrio bacteria in oysters.

Climate models of varying complexity have been used for decades to investigate the impact of mountains on the atmosphere and surface climate. Here, the impact of removing the continental topography on the present-day ocean climate is investigated using three different climate models spanning multiple generations. An idealized study is performed where all present-day land surface topography is removed and the equilibrium change in the oceanic mean state with and without the mountains is studied. When the mountains are removed, changes found in all three models include a weakening of the Atlantic meridional overturning circulation and associated SST cooling in the subpolar North Atlantic. The SSTs also warm in all the models in the western North Pacific Ocean associated with a northward shift of the atmospheric jet and the Kuroshio. In the ocean interior, the magnitude of the temperature and salinity response to removing the mountains is relatively small and the sign and magnitude of the changes generally vary among the models. These different interior ocean responses are likely related to differences in the mean state of the control integrations due to differences in resolution and associated subgrid-scale mixing parameterizations. Compared to the results from 4xCO2 simulations, the interior ocean temperature changes caused by mountain removal are relatively small; however, the oceanic circulation response and Northern Hemisphere near-surface temperature changes are of a similar magnitude to the response to such radiative forcing changes.

The Humboldt Upwelling System is of global interest due to its importance to fisheries, though the origin of its high productivity remains elusive. In regional physical-biogeochemical model simulations, the seasonal amplitude of mesozooplankton net production exceeds that of phytoplankton, indicating “seasonal trophic amplification.” An analytical approach identifies amplification to be driven by a seasonally varying trophic transfer efficiency due to mixed layer variations. The latter alters the vertical distribution of phytoplankton and thus the zooplankton and phytoplankton encounters, with lower encounters occurring in a deeper mixed layer where phytoplankton are diluted. In global model simulations, mixed layer depth appears to affect trophic transfer similarly in other productive regions. Our results highlight the importance of mixed layer depth for trophodynamics on a seasonal scale with potential significant implications, given mixed layer depth changes projected under climate change.

Climate change can drive shifts in the seasonality of marine productivity, with consequences for the marine food web. However, these alterations in phytoplankton bloom phenology (initiation and peak timing), and the underlying drivers, are not well understood. Here, using a 30-member Large Ensemble of climate change projections, we show earlier bloom initiation in most ocean regions, yet changes in bloom peak timing vary widely by region. Shifts in both initiation and peak timing are induced by a subtle decoupling between altered phytoplankton growth and zooplankton predation, with increased zooplankton predation (top-down control) playing an important role in altered bloom peak timing over much of the global ocean. Only in limited regions is light limitation a primary control for bloom initiation changes. In the extratropics, climate-change-induced phenological shifts will exceed background natural variability by the end of the twenty-first century, which may impact energy flow in the marine food webs.

The local climatic impacts of historical expansion of irrigation are substantial, but the distant impacts are poorly understood, and their governing mechanisms generally have not been rigorously analyzed. Our experiments with an earth-system model suggest that irrigation in the Middle East and South Asia may enhance rainfall in a large portion of the Sahel-Sudan Savanna (SSS) to an extent comparable and opposite to its suppression by other anthropogenic climate drivers during the last several decades. The enhancement arises through a reduction in the meridional gradient of moist static energy from the Sahara Desert to the tropical rainforests. An implication of this study is that remote irrigation is a possible factor affecting the risk of drought and famine and, thus, future water security in the SSS region.

We quantify the impacts of halogenated ozone-depleting substances (ODSs), greenhouse gases (GHGs), and short-lived ozone precursors on ozone changes between 1850 and 2014 using single-forcing perturbation simulations from several Earth system models with interactive chemistry participating in the Coupled Model Intercomparison Project Aerosol and Chemistry Model Intercomparison Project. We present the responses of ozone to individual forcings and an attribution of changes in ozone columns and vertically resolved stratospheric and tropospheric ozone to these forcings. We find that whilst substantial ODS-induced ozone loss dominates the stratospheric ozone changes since the 1970s, in agreement with previous studies, increases in tropospheric ozone due to increases in short-lived ozone precursors and methane since the 1950s make increasingly important contributions to total column ozone (TCO) changes. Increases in methane also lead to substantial extra-tropical stratospheric ozone increases. Impacts of nitrous oxide and carbon dioxide on stratospheric ozone are significant but their impacts on TCO are small overall due to several opposing factors and are also associated with large dynamical variability. The multi-model mean (MMM) results show a clear change in the stratospheric ozone trends after 2000 due to now declining ODSs, but the trends are generally not significantly positive, except in the extra-tropical upper stratosphere, due to relatively small changes in forcing over this period combined with large model uncertainty. Although the MMM ozone compares well with the observations, the inter-model differences are large primarily due to the large differences in the models' representation of ODS-induced ozone depletion.

We identify the local, vertical and lateral processes that cause bottom oxygen variation, and characterize timescales for each process using oxygen budget analysis based on a coupled physical-biogeochemical model for the coastal seas in east China. Local oxygen deficit often occurs in the summer season due to the faster local consumption than the vertical replenishment in seasonal timescale. Lateral transport of oxygen-rich ambient water replenishes local deficit of bottom dissolved oxygen. Competition between local deficit and lateral exchange determines seasonal hypoxia formation and sustainment. Short local consumption timescale is favorable for hypoxia formation, and transient hypoxia often forms when the local deficit and lateral exchange processes act on comparable timescales, such as the East China Sea in which the bottom hypoxia usually lasts for days. Extremely long lateral exchange timescale suggests that dissolved oxygen variation is predominantly controlled by local processes, and short local consumption timescale often causes increasingly severe seasonal hypoxia until the onset of the relaxation of local deficit, such as the bottom hypoxia in the Bohai Sea. Using these timescales to evaluate local deficit relative to vertical and lateral residence time and their variability is a convenient and potentially powerful general mechanistic framework to evaluate strategies to mitigate coastal hypoxia worldwide.

The coastal region in east China experiences massive anthropogenic eutrophication, and the bottom water off the Changjiang River Estuary in the East China Sea faces the threat of severe seasonal hypoxia. We find that projected future climate changes will work in parallel with anthropogenic eutrophication to exacerbate current hypoxia and increase shelf vulnerability to bottom hypoxia. We use a coupled physical-biogeochemical regional model to investigate the differences of shelf hydrography and oxygen dynamics between present and future projected states. Model results indicate that the Yellow Sea Cold Water Mass which plays essential roles in nekton migration and shellfish farming practically disappears by the end of the 21st century, and shelf vertical stratification strengthens by an average of 12.7%. Hypoxia off the Changjiang River Estuary is exacerbated with increased (by one month) hypoxia duration, lower dissolved oxygen minima, and significant lateral (202%) and vertical (60%) expansions of hypoxic water. Reduced oxygen solubility, and accelerated oxygen consumption under increased primary production and rising water temperature contribute 42% and 58%, respectively, of bottom dissolved oxygen decrease in the East China Sea. Model results also show increased vertical diffusion of oxygen, despite vertical stratification strengthening, due to increased surface-bottom oxygen concentration gradient associated with increased oxygen release in surface water and exacerbated oxygen consumption in subsurface water.

Near-term climate forcers (NTCFs), including aerosols and chemically reactive gases such as tropospheric ozone and methane, offer a potential way to mitigate climate change and improve air quality—so called 'win-win' mitigation policies. Prior studies support improved air quality under NTCF mitigation, but with conflicting climate impacts that range from a significant reduction in the rate of global warming to only a modest impact. Here, we use state-of-the-art chemistry-climate model simulations conducted as part of the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP) to quantify the 21st-century impact of NTCF reductions, using a realistic future emission scenario with a consistent air quality policy. Non-methane NTCF (NMNTCF; aerosols and ozone precursors) mitigation improves air quality, but leads to significant increases in global mean precipitation of 1.3% by mid-century and 1.4% by end-of-the-century, and corresponding surface warming of 0.23 and 0.21 K. NTCF (all-NTCF; including methane) mitigation further improves air quality, with larger reductions of up to 45% for ozone pollution, while offsetting half of the wetting by mid-century (0.7% increase) and all the wetting by end-of-the-century (non-significant 0.1% increase) and leading to surface cooling of −0.15 K by mid-century and −0.50 K by end-of-the-century. This suggests that methane mitigation offsets warming induced from reductions in NMNTCFs, while also leading to net improvements in air quality.

In this study we present projected changes in the Eastern Bering Sea shelf (EBS) biophysical processes in response to climate forcing scenarios from the Coupled Model Intercomparison Phase 6 (CMIP6). These changes are obtained by dynamical downscaling using a Bering Sea regional model. Surface atmospheric and ocean boundary forcing from three Earth System Models (ESMs) in CMIP6, and a low and a high emission scenario of Shared Socioeconomic Pathway (SSP126 and SSP585) of each of the ESMs are considered. Ensemble mean results suggest that, contrary to an anticipated increase in ocean stratification under warming, diminishing ice cover in response to climate forcing and resultant reduced surface freshening weakens EBS stratification in the melt season. Modeled ensemble mean phytoplankton and zooplankton biomass on the EBS exhibits subsurface maxima during the growing season; the amplitude of these maxima decreases with warming, along with a reduction in primary productivity and oxygen concentration over much of the EBS water column. Phenology of both phytoplankton and zooplankton biomass on the EBS shifts earlier, leading to an increase (decrease) in biomass averaged between April–July (August–November), while annually averaged biomass decreases under warming. Projected changes of primary and secondary plankton biomass at the end of the 21st century are not well separated between the SSP126 and SSP585 scenario in light of the large across model spread under each scenario. The projected ensemble mean warming amplitude of the EBS summer bottom temperature is largely unchanged between results forced by the Coupled Model Intercomparison Phase 5 Representative Concentration Pathway 8.5 (CMIP5 RCP8.5) and CMIP6 SSP585 scenarios. Likewise, the reduction rate of annual mean phytoplankton and large zooplankton biomass are comparable between RCP8.5 and SSP585 projections, even though the absolute amplitudes of biomass are sensitive to modeling parameters such as the solar irradiance attenuation curve. Hence, within the Bering Sea dynamical downscaling framework, projected long-term warming trends in EBS bottom temperature and plankton biomass reduction rates are robust responses to climate forcing.

Efforts to manage living marine resources (LMRs) under climate change need projections of future ocean conditions, yet most global climate models (GCMs) poorly represent critical coastal habitats. GCM utility for LMR applications will increase with higher spatial resolution but obstacles including computational and data storage costs, obstinate regional biases, and formulations prioritizing global robustness over regional skill will persist. Downscaling can help address GCM limitations, but significant improvements are needed to robustly support LMR science and management. We synthesize past ocean downscaling efforts to suggest a protocol to achieve this goal. The protocol emphasizes LMR-driven design to ensure delivery of decision-relevant information. It prioritizes ensembles of downscaled projections spanning the range of ocean futures with durations long enough to capture climate change signals. This demands judicious resolution refinement, with pragmatic consideration for LMR-essential ocean features superseding theoretical investigation. Statistical downscaling can complement dynamical approaches in building these ensembles. Inconsistent use of bias correction indicates a need for objective best practices. Application of the suggested protocol should yield regional ocean projections that, with effective dissemination and translation to decision-relevant analytics, can robustly support LMR science and management under climate change.

Climate change impacts on marine life in the world ocean are expected to accelerate over the 21st century, affecting the structure and functioning of food webs. We analyzed a key aspect of this issue, focusing on the impact of changes in biomass flow within marine food webs and the resulting effects on ecosystem biomass and production. We used a modeling framework based on a parsimonious quasi-physical representation of biomass flow through the food web, to explore the future of marine consumer biomass and production at the global scale over the 21st century. Biomass flow is determined by three climate-related factors: primary production entering the food web, trophic transfer efficiency describing losses in biomass transfers from one trophic level (TL) to the next, and flow kinetic measuring the speed of biomass transfers within the food web. Using climate projections of three earth system models, we calculated biomass and production at each TL on a 1° latitude ×1° longitude grid of the global ocean under two greenhouse gas emission scenarios. We show that the alterations of the trophic functioning of marine ecosystems, mainly driven by faster and less efficient biomass transfers and decreasing primary production, would lead to a projected decline in total consumer biomass by 18.5% by 2090–2099 relative to 1986–2005 under the “no mitigation policy” scenario. The projected decrease in transfer efficiency is expected to amplify impacts at higher TLs, leading to a 21.3% decrease in abundance of predators and thus to a change in the overall trophic structure of marine ecosystems. Marine animal production is also projected to decline but to a lesser extent than biomass. Our study highlights that the temporal and spatial projected changes in biomass and production would imply direct repercussions on the future of world fisheries and beyond all services provided by Ocean.

Transfer efficiency is the proportion of energy passed between nodes in food webs. It is an emergent, unitless property that is difficult to measure, and responds dynamically to environmental and ecosystem changes. Because the consequences of changes in transfer efficiency compound through ecosystems, slight variations can have large effects on food availability for top predators. Here, we review the processes controlling transfer efficiency, approaches to estimate it, and known variations across ocean biomes. Both process-level analysis and observed macroscale variations suggest that ecosystem-scale transfer efficiency is highly variable, impacted by fishing, and will decline with climate change. It is important that we more fully resolve the processes controlling transfer efficiency in models to effectively anticipate changes in marine ecosystems and fisheries resources.

The region around the main Hawaiian Islands (MHI) is characterized by a permanent thermocline, and numerous processes have been proposed to facilitate phytoplankton blooms in this oligotrophic province. Here, we use a coupled physical-biogeochemical model of the MHI to elucidate some of the different dynamics behind phytoplankton blooms. The model permits submesoscale processes and is integrated for the years 2010–2017 embedded in a physical state-estimate reanalysis using nearly 50 million observations. Model results exhibit good agreement between simulated values and observations at Station ALOHA for physical and biogeochemical parameters. The overall levels and the amplitude of the seasonal cycles are well captured for many variables. We show that variations in net primary production are mainly driven by domain-wide seasonal cycles of light and nitrogen fixers, respectively, as well as short-lived, stochastic bloom events resulting from the formation of eddies to the west of the island of Hawaii. Furthermore, sporadic wind- and current-driven upwelling is resulting in ephemeral enhancements of nearshore phytoplankton blooms mainly on the northeastern side of the islands.

Parties to the Paris Agreement agreed to holding global average temperature increases “well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C above pre-industrial levels”. Monitoring the contributions of human-induced climate forcings to warming so far is key to understanding progress towards these goals. Here we use climate model simulations from the Detection and Attribution Model Intercomparison Project, as well as regularized optimal fingerprinting, to show that anthropogenic forcings caused 0.9 to 1.3 °C of warming in global mean near-surface air temperature in 2010–2019 relative to 1850–1900, compared with an observed warming of 1.1 °C. Greenhouse gases and aerosols contributed changes of 1.2 to 1.9 °C and −0.7 to −0.1 °C, respectively, and natural forcings contributed negligibly. These results demonstrate the substantial human influence on climate so far and the urgency of action needed to meet the Paris Agreement goals.

Inter‐annual to decadal variability in the strength of the land and ocean carbon sinks impede accurate predictions of year‐to‐year atmospheric carbon dioxide (CO2) growth rate. Such information is crucial to verify the effectiveness of fossil fuel emissions reduction measures. Using a multi‐model framework comprising prediction systems initialized by the observed state of the physical climate, we find a predictive skill for the global ocean carbon sink of up to 6 years for some models. Longer regional predictability horizons are found across single models. On land, a predictive skill of up to 2 years is primarily maintained in the tropics and extra‐tropics enabled by the initialization of the physical climate. We further show that anomalies of atmospheric CO2 growth rate inferred from natural variations of the land and ocean carbon sinks are predictable at lead time of 2 years and the skill is limited by the land carbon sink predictability horizon.

Representing biological nitrogen fixation (BNF) is an important challenge for coupled carbon (C) and nitrogen (N) land models. Initial representations of BNF in land models applied simplified phenomenological relationships. More recent representations of BNF are mechanistic and include the dynamic response of symbiotic BNF to N limitation of plant growth. However, they generally do not include the competitive dynamics between N-fixing and non-fixing plants, which is a key ecological mechanism that determines ecosystem-scale symbiotic BNF. Furthermore, asymbiotic BNF is generally not included in land models. Here, we present LM4.1-BNF, a novel representation of BNF (asymbiotic and symbiotic) and an updated representation of N cycling in the Geophysical Fluid Dynamics Laboratory Land Model 4.1 (LM4.1). LM4.1-BNF incorporates a mechanistic representation of asymbiotic BNF by soil microbes, a representation of the competitive dynamics between N-fixing and non-fixing plants, and distinct asymbiotic and symbiotic BNF temperature responses derived from corresponding observations. LM4.1-BNF makes reasonable estimations of major carbon (C) and N pools and fluxes and their temporal dynamics, in comparison to the previous version of LM4.1 with N cycling (LM3-SNAP) and to previous representations of BNF in land models generally (phenomenological representations and those without competitive dynamics between N-fixing and non-fixing plants and/or asymbiotic BNF) at a temperate forest site. LM4.1-BNF effectively reproduces asymbiotic BNF rate (13 kgNha−1yr−1) in comparison to observations (11 kgNha−1yr−1). LM4.1-BNF effectively reproduces the temporal dynamics of symbiotic BNF rate: LM4.1-BNF simulates a symbiotic BNF pulse in early succession that reaches 73 kgNha−1yr−1 at 15 years and then declines to ∼0 kgNha−1yr−1 at 300 years, similarly to observed symbiotic BNF, which reaches 75 kgNha−1yr−1 at 17 years and then declines to ∼0 kgNha−1yr−1 in late successional forests. As such, LM4.1-BNF can be applied to project the dynamic response of vegetation to N limitation of plant growth and the degree to which this will constrain the terrestrial C sink under elevated atmospheric CO2 concentration and other global change factors.

Enhanced riverine delivery of terrestrial nitrogen (N) has polluted many freshwater and coastal ecosystems, degrading drinking water and marine resources. An emerging view suggests a contribution of land N memory effects—impacts of antecedent dry conditions on land N accumulation that disproportionately increase subsequent river N loads. To date, however, such effects have only been explored for several relatively small rivers covering a few episodes. Here we introduce an index for quantifying land N memory effects and assess their prevalence using regional observations and global terrestrial-freshwater ecosystem model outputs. Model analyses imply that land N memory effects are globally prevalent but vary widely in strength. Strong effects reflect large soil dissolved inorganic N (DIN) surpluses by the end of dry years. During the subsequent wetter years, the surpluses are augmented by soil net mineralization pulses, which outpace plant uptake and soil denitrification, resulting in disproportionately increased soil leaching and eventual river loads. These mechanisms are most prominent in areas with high hydroclimate variability, warm climates, and ecosystem disturbances. In 48 of the 118 basins analyzed, strong memory effects produce 43% (21%–88%) higher DIN loads following drought years than following average years. Such a marked influence supports close consideration of prevalent land N memory effects in water-pollution management efforts.

Consecutive hot periods without nighttime heat relief significantly increase mortality and morbidity rates. Using the Geophysical Fluid Dynamics Laboratory land model coupled with a newly developed and validated urban canopy model, changes in three types of summertime hot extremes, that is, independent hot days, independent hot nights, and compound hot events (CHEs), in the 21st century are quantified in China. Results indicate that all three types of hot extremes become more frequent, and CHEs are projected to be the dominant type at the end of this century under the representative concentration pathway 8.5 scenario. Furthermore, compared to the rural land, the urban land experiences even stronger increases in CHEs in terms of frequency, duration, and intensity. These faster increases of CHEs in urban areas highlight the urgency of developing and implementing mitigation and adaptation strategies to combat the adverse health effects of global warming and urban heat islands.

Human activities such as fossil fuel combustion, land-use change, nitrogen (N) fertilizer use, emission of livestock, and waste excretion accelerate the transformation of reactive N and its impact on the marine environment. This study elucidates that anthropogenic N fluxes (ANFs) from atmospheric and river deposition exacerbate Arctic warming and sea ice loss via physical–biological feedback. The impact of physical–biological feedback is quantified through a suite of experiments using a coupled climate–ocean–biogeochemical model (GFDL-CM2.1-TOPAZ) by prescribing the preindustrial and contemporary amounts of riverine and atmospheric N fluxes into the Arctic Ocean. The experiment forced by ANFs represents the increase in ocean N inventory and chlorophyll concentrations in present and projected future Arctic Ocean relative to the experiment forced by preindustrial N flux inputs. The enhanced chlorophyll concentrations by ANFs reinforce shortwave attenuation in the upper ocean, generating additional warming in the Arctic Ocean. The strongest responses are simulated in the Eurasian shelf seas (Kara, Barents, and Laptev Seas; 65°–90°N, 20°–160°E) due to increased N fluxes, where the annual mean surface temperature increase by 12% and the annual mean sea ice concentration decrease by 17% relative to the future projection, forced by preindustrial N inputs.

Over the past century, human activities have resulted in substantial global changes that threaten the stability and functionality of coastal habitats. One of these impacts was through nutrient pollution of river runoffs, which have triggered harmful algal blooms and caused low-oxygen conditions in many coastal regions. However, it is challenging for models to simulate coastal impacts of increasing river nutrient loads, especially on a global scale and over a long period of time. Here we take advantage of some recent modeling advances to provide a global perspective on coastal ecosystem responses to increasing river nitrogen loads over the half-century between 1961 and 2010. Overall, we show that the global coastal ocean accumulated more nitrogen over time as river nitrogen loads increased. This caused the primary production of the global coastal system (i.e., the conversion of inorganic to organic materials through photosynthesis) to increase as well. However, we found that the sensitivity of each coastal ecosystem to comparable changes in nitrogen loads varied considerably. This variability was to a large extent related to two factors: the rate of exchange between coastal waters and the adjacent ocean waters, and whether nutrients are limited for phytoplankton to conduct photosynthesis in that system.

Incorporating species’ ability to adaptively respond to climate change is critical for robustly predicting persistence. One such example could be the adaptive role of algal symbionts in setting coral thermal tolerance under global warming and ocean acidification. Using a global ecological and evolutionary model of competing branching and mounding coral morphotypes, we show symbiont shuffling (towards taxa with increased heat tolerance) was more effective than symbiont evolution in delaying coral-cover declines, but stronger warming rates (high emissions scenarios) outpace the ability of these adaptive processes and limit coral persistence. Acidification has a small impact on reef degradation rates relative to warming. Global patterns in coral reef vulnerability to climate are sensitive to the interaction of warming rate and adaptive capacity and cannot be predicted by either factor alone. Overall, our results show how models of spatially resolved adaptive mechanisms can inform conservation decisions.

Copepods are among the most abundant marine metazoans and form a key link between marine primary producers, higher trophic levels, and carbon sequestration pathways. Climate change is projected to change surface ocean temperature by up to 4°C in the North Atlantic with many associated changes including slowing of the overturning circulation, areas of regional freshening, and increased salinity and reductions in nutrients available in the euphotic zone over the next century. These changes will lead to a restructuring of phytoplankton and zooplankton communities with cascading effects throughout the food web. Here we employ observations of copepods, projected changes in ocean climate, and species distribution models to show how climate change may affect the distribution of copepod species in the North Atlantic. On average species move northeast at a rate of 14.1 km decade−1. Species turnover in copepod communities will range from 5% to 75% with the highest turnover rates concentrated in regions of pronounced temperature increase and decrease. The changes in species range vary according to copepod traits with the largest effects found to occur in the cooling, freshening area in the subpolar North Atlantic south of Greenland and in an area of significant warming along the Scotian shelf. Large diapausing copepods (>2.5 mm) which are higher in lipids and a crucial food source for whales, may have an advantage in the cooling waters due to their life‐history strategy that facilitates their survival in the arctic environment. Carnivorous copepods show a basin wide increase in species richness and show significant habitat area increases when their distribution moves poleward while herbivores see significant habitat area losses. The trait‐specific effects highlight the complex consequences of climate change for the marine food web.

Typically, the surface of the ocean releases oxygen to the atmosphere during summer and takes it up during winter. This cycle is driven by circulation, biology (photosynthesis and respiration), and the seasonal cycle in water temperature, which changes the solubility of oxygen in surface water. We have used measurements of two atmospheric tracers, one which tracks oxygen and one which tracks heat, to estimate the amount of oxygen taken up or released by a change in ocean heat content. By looking at ocean models and atmospheric observations of the two atmospheric tracers, we find that the oxygen exchange between the ocean and atmosphere in the Southern Hemisphere is more responsive to changes in heat content than in the Northern Hemisphere. These hemispheric metrics are useful tests of how ocean models simulate some biological and physical processes.

Hydrogen (H2) has been proposed as an alternative energy carrier to reduce the carbon footprint and associated radiative forcing of the current energy system. Here, we describe the representation of H2 in the GFDL-AM4.1 model including updated emission inventories and improved representation of H2 soil removal, the dominant sink of H2. The model best captures the overall distribution of surface H2, including regional contrasts between climate zones, when vd(H2) is modulated by soil moisture, temperature, and soil carbon content. We estimate that the soil removal of H2 increases with warming (2–4% per K), with large uncertainties stemming from different regional response of soil moisture and soil carbon. We estimate that H2 causes an indirect radiative forcing of 0.84 mW m−2/(Tg(H2)yr−1) or 0.13 mW m−2 ppbv−1, primarily due to increasing CH4 lifetime and stratospheric water vapor production.

Patterns of population renewal in marine fishes are often irregular and lead to volatile fluctuations in abundance that challenge management and conservation efforts. Here, we examine the relationship between life‐history strategies and recruitment variability in exploited marine fish species using a macroecological approach.

Given the ecological and economic importance of eastern boundary upwelling systems like the California Current System (CCS), their evolution under climate change is of considerable interest for resource management. However, the spatial resolution of global earth system models (ESMs) is typically too coarse to properly resolve coastal winds and upwelling dynamics that are key to structuring these ecosystems. Here we use a high-resolution (0.1°) regional ocean circulation model coupled with a biogeochemical model to dynamically downscale ESMs and produce climate projections for the CCS under the high emission scenario, Representative Concentration Pathway 8.5. To capture model uncertainty in the projections, we downscale three ESMs: GFDL-ESM2M, HadGEM2-ES, and IPSL-CM5A-MR, which span the CMIP5 range for future changes in both the mean and variance of physical and biogeochemical CCS properties. The forcing of the regional ocean model is constructed with a “time-varying delta” method, which removes the mean bias of the ESM forcing and resolves the full transient ocean response from 1980 to 2100. We found that all models agree in the direction of the future change in offshore waters: an intensification of upwelling favorable winds in the northern CCS, an overall surface warming, and an enrichment of nitrate and corresponding decrease in dissolved oxygen below the surface mixed layer. However, differences in projections of these properties arise in the coastal region, producing different responses of the future biogeochemical variables. Two of the models display an increase of surface chlorophyll in the northern CCS, consistent with a combination of higher nitrate content in source waters and an intensification of upwelling favorable winds. All three models display a decrease of chlorophyll in the southern CCS, which appears to be driven by decreased upwelling favorable winds and enhanced stratification, and, for the HadGEM2-ES forced run, decreased nitrate content in upwelling source waters in nearshore regions. While trends in the downscaled models reflect those in the ESMs that force them, the ESM and downscaled solutions differ more for biogeochemical than for physical variables.

Fishes are the dominant vertebrates in the ocean, yet we know little of their contribution to carbon export flux at regional to global scales. We synthesize the existing information on fish-based carbon flux in coastal and pelagic waters, identify gaps and challenges in measuring this flux and approaches to address them, and recommend research priorities. Based on our synthesis of passive (fecal pellet sinking) and active (migratory) flux of fishes, we estimated that fishes contribute an average (± standard deviation) of about 16.1% (± 13%) to total carbon flux out of the euphotic zone. Using the mean value of model-generated global carbon flux estimates, this equates to an annual flux of 1.5 ± 1.2 Pg C yr−1. High variability in estimations of the fish-based contribution to total carbon flux among previous field studies and reported here highlight significant methodological variations and observational gaps in our present knowledge. Community-adopted methodological standards, improved and more frequent measurements of biomass and passive and active fluxes of fishes, and stronger linkages between observations and models will decrease uncertainty, increase our confidence in the estimation of fish-based carbon flux, and enable identification of controlling factors to account for spatial and temporal variability. Better constraints on this key component of the biological pump will provide a baseline for understanding how ongoing climate change and harvest will affect the role fishes play in carbon flux.

The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.

Projections of climate change impacts on marine ecosystems have revealed long-term declines in global marine animal biomass and unevenly distributed impacts on fisheries. Here we apply an enhanced suite of global marine ecosystem models from the Fisheries and Marine Ecosystem Model Intercomparison Project (Fish-MIP), forced by new-generation Earth system model outputs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6), to provide insights into how projected climate change will affect future ocean ecosystems. Compared with the previous generation CMIP5-forced Fish-MIP ensemble, the new ensemble ecosystem simulations show a greater decline in mean global ocean animal biomass under both strong-mitigation and high-emissions scenarios due to elevated warming, despite greater uncertainty in net primary production in the high-emissions scenario. Regional shifts in the direction of biomass changes highlight the continued and urgent need to reduce uncertainty in the projected responses of marine ecosystems to climate change to help support adaptation planning.

Understanding how fish food webs emerge from planktonic and benthic energy pathways that sustain them is an important challenge for predicting fisheries production under climate change and quantifying the role of fish in carbon and nutrient cycling. We examine if a trait-based fish community model using the fish traits of maximum body weight and vertical habitat strategy can meet this challenge by globally representing fish food web diversity.

July 2019 saw record-breaking wildfires burning 3,600 km2 in Alaska. The GFDL Earth system model indicates a threefold increased risk of Alaska’s extreme fires during recent decades due to primarily anthropogenic ignition and secondarily climate-induced biofuel abundance.

ROMS, a high-resolution regional ocean model, was used to study how climate change may affect the northwest Atlantic Ocean. A control (CTRL) simulation was conducted for the recent past (1976-2005), and simulations with additional forcing at the surface and lateral boundaries, obtained from three different global climate models (GCMs) using the RCP8.5 scenario, were conducted to represent the future (2070-2099). The climate change response was obtained from the difference between the CTRL and each of the three future simulations. All three ROMS simulations indicated large increases in sea surface temperatures (SSTs) over most of the domain except off the eastern US seaboard due to weakening of the Gulf Stream. There are also substantial inter-model differences in the response, including a southward shift of the Gulf Stream in one simulation and a slight northward shift in the other two, with corresponding changes in eddy activity. The depth of maximum warming varied among the three simulations, resulting in differences in the bottom temperature response in coastal regions, including the Gulf of Maine and the west Florida Shelf. The surface salinity decreased (increased) in the northern (southern) part of the domain in all three experiments, but in one, the freshening extended much further south in ROMS than in the GCM that provided the large-scale forcing, associated with changes in the well resolved coastal currents. Thus, while high resolution allows for a better representation of currents and bathymetry, the response to climate change can vary considerably depending on the large-scale forcing.

It is important to understand how future environmental policies will impact both climate change and air pollution. Although targeting near-term climate forcers (NTCFs), defined here as aerosols, tropospheric ozone, and precursor gases, should improve air quality, NTCF reductions will also impact climate. Prior assessments of the impact of NTCF mitigation on air quality and climate have been limited. This is related to the idealized nature of some prior studies, simplified treatment of aerosols and chemically reactive gases, as well as a lack of a sufficiently large number of models to quantify model diversity and robust responses. Here, we quantify the 2015–2055 climate and air quality effects of non-methane NTCFs using nine state-of-the-art chemistry–climate model simulations conducted for the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). Simulations are driven by two future scenarios featuring similar increases in greenhouse gases (GHGs) but with “weak” (SSP3-7.0) versus “strong” (SSP3-7.0-lowNTCF) levels of air quality control measures. As SSP3-7.0 lacks climate policy and has the highest levels of NTCFs, our results (e.g., surface warming) represent an upper bound. Unsurprisingly, we find significant improvements in air quality under NTCF mitigation (strong versus weak air quality controls). Surface fine particulate matter (PM2.5) and ozone (O3) decrease by −2.2±0.32 µg m−3 and −4.6±0.88 ppb, respectively (changes quoted here are for the entire 2015–2055 time period; uncertainty represents the 95 % confidence interval), over global land surfaces, with larger reductions in some regions including south and southeast Asia. Non-methane NTCF mitigation, however, leads to additional climate change due to the removal of aerosol which causes a net warming effect, including global mean surface temperature and precipitation increases of 0.25±0.12 K and 0.03±0.012 mm d−1, respectively. Similarly, increases in extreme weather indices, including the hottest and wettest days, also occur. Regionally, the largest warming and wetting occurs over Asia, including central and north Asia (0.66±0.20 K and 0.03±0.02 mm d−1), south Asia (0.47±0.16 K and 0.17±0.09 mm d−1), and east Asia (0.46±0.20 K and 0.15±0.06 mm d−1). Relatively large warming and wetting of the Arctic also occur at 0.59±0.36 K and 0.04±0.02 mm d−1, respectively. Similar surface warming occurs in model simulations with aerosol-only mitigation, implying weak cooling due to ozone reductions. Our findings suggest that future policies that aggressively target non-methane NTCF reductions will improve air quality but will lead to additional surface warming, particularly in Asia and the Arctic. Policies that address other NTCFs including methane, as well as carbon dioxide emissions, must also be adopted to meet climate mitigation goals.

Theory and observations suggest that low frequency variation in marine plankton populations, or red noise, may arise through cumulative integration of white noise atmospheric forcing by the ocean and its amplification within food webs. Here, we revisit evidence for the integration of stochastic atmospheric variations by comparing the power spectra of time series of atmospheric and oceanographic conditions to the population dynamics of 150 plankton taxa at Station L4 in the Western English Channel. The power spectra of oceanographic conditions (sea surface temperature, surface nitrate) are redder than those of atmospheric forcing (surface wind stress, net heat fluxes) at Station L4. However, plankton populations have power spectral slopes across trophic levels and body sizes that are redder than atmospheric forcing but whiter than oceanographic conditions. While zooplankton have redder spectral slopes than phytoplankton, there is no significant relationship between power spectral slope and body size or generation length. Using a predator-prey model, we show that the whitening of plankton time series relative to oceanographic conditions arises from noisy plankton bloom dynamics in this strongly seasonal system. The model indicates that, for typical predator-prey interactions, where the predator is on average 10 times longer than the prey, grazing leads to a modest reddening of phytoplankton variability by their larger and longer lived zooplankton consumers. Our findings suggest that, beyond extrinsic forcing by the environment, predator-prey interactions play a role in influencing the power spectra of time series of plankton populations.

The Southern Ocean south of 30° S represents only one-third of the total ocean area, yet absorbs half of the total ocean anthropogenic carbon and over two-thirds of ocean anthropogenic heat. In the past, the Southern Ocean has also been one of the most sparsely measured regions of the global ocean. Here we use pre-2005 ocean shipboard measurements alongside novel observations from autonomous floats with biogeochemical sensors to calculate changes in Southern Ocean temperature, salinity, pH and concentrations of nitrate, dissolved inorganic carbon and oxygen over two decades. We find local warming of over 3 °C, salinification of over 0.2 psu near the Antarctic coast, and isopycnals are found to deepen between 65° and 40° S. We find deoxygenation along the Antarctic coast, but reduced deoxygenation and nitrate concentrations where isopycnals deepen farther north. The forced response of the Earth system model ESM2M does not reproduce the observed patterns. Accounting for meltwater and poleward-intensifying winds in ESM2M improves reproduction of the observed large-scale changes, demonstrating the importance of recent changes in wind and meltwater. Future Southern Ocean biogeochemical changes are likely to be influenced by the relative strength of meltwater input and poleward-intensifying winds. The combined effect could lead to increased Southern Ocean deoxygenation and nutrient accumulation, starving the global ocean of nutrients sooner than otherwise expected.

Ocean acidity extreme events are short-term periods of relatively high [H+] concentrations. The uptake of anthropogenic CO2 emissions by the ocean is expected to lead to more frequent and intense ocean acidity extreme events, not only due to changes in the long-term mean but also due to changes in short-term variability. Here, we use daily mean output from a five-member ensemble simulation of a comprehensive Earth system model under low- and high-CO2-emission scenarios to quantify historical and future changes in ocean acidity extreme events. When defining extremes relative to a fixed preindustrial baseline, the projected increase in mean [H+] causes the entire surface ocean to reach a near-permanent acidity extreme state by 2030 under both the low- and high-CO2-emission scenarios. When defining extremes relative to a shifting baseline (i.e., neglecting the changes in mean [H+]), ocean acidity extremes are also projected to increase because of the simulated increase in [H+] variability; e.g., the number of days with extremely high surface [H+] conditions is projected to increase by a factor of 14 by the end of the 21st century under the high-CO2-emission scenario relative to preindustrial levels. Furthermore, the duration of individual extreme events is projected to triple, and the maximal intensity and the volume extent in the upper 200 m are projected to quintuple. Similar changes are projected in the thermocline. Under the low-emission scenario, the increases in ocean acidity extreme-event characteristics are substantially reduced. At the surface, the increases in [H+] variability are mainly driven by increases in [H+] seasonality, whereas changes in thermocline [H+] variability are more influenced by interannual variability. Increases in [H+] variability arise predominantly from increases in the sensitivity of [H+] to variations in its drivers (i.e., carbon, alkalinity, and temperature) due to the increase in oceanic anthropogenic carbon. The projected increase in [H+] variability and extremes may enhance the risk of detrimental impacts on marine organisms, especially for those that are adapted to a more stable environment.

We document the development and simulation characteristics of the next generation modeling system for seasonal to decadal prediction and projection at the Geophysical Fluid Dynamics Laboratory (GFDL). SPEAR (Seamless System for Prediction and EArth System Research) is built from component models recently developed at GFDL ‐ the AM4 atmosphere model, MOM6 ocean code, LM4 land model and SIS2 sea ice model. The SPEAR models are specifically designed with attributes needed for a prediction model for seasonal to decadal time scales, including the ability to run large ensembles of simulations with available computational resources. For computational speed SPEAR uses a coarse ocean resolution of approximately 1.0o (with tropical refinement). SPEAR can use differing atmospheric horizontal resolutions ranging from 1o to 0.25o. The higher atmospheric resolution facilitates improved simulation of regional climate and extremes. SPEAR is built from the same components as the GFDL CM4 and ESM 4 models, but with design choices geared toward seasonal to multidecadal physical climate prediction and projection. We document simulation characteristics for the time‐mean climate, aspects of internal variability, and the response to both idealized and realistic radiative forcing change. We describe in greater detail one focus of the model development process that was motivated by the importance of the Southern Ocean to the global climate system. We present sensitivity tests that document the influence of the Antarctic surface heat budget on Southern Ocean ventilation and deep global ocean circulation. These findings were also useful in the development processes for the GFDL CM4 and ESM 4 models.

We compare equilibrium climate sensitivity (ECS) estimates from pairs of long (≥800‐year) control and abruptly quadrupled CO2 simulations with shorter (150‐ and 300‐year) coupled atmosphere‐ocean simulations and slab ocean models (SOMs). Consistent with previous work, ECS estimates from shorter coupled simulations based on annual averages for years 1–150 underestimate those from SOM (−8% ± 13%) and long (−14% ± 8%) simulations. Analysis of only years 21–150 improved agreement with SOM (−2% ± 14%) and long (−8% ± 10%) estimates. Use of pentadal averages for years 51–150 results in improved agreement with long simulations (−4% ± 11%). While ECS estimates from current generation U.S. models based on SOM and coupled annual averages of years 1–150 range from 2.6°C to 5.3°C, estimates based longer simulations of the same models range from 3.2°C to 7.0°C. Such variations between methods argues for caution in comparison and interpretation of ECS estimates across models.

We describe the baseline coupled model configuration and simulation characteristics of GFDL's Earth System Model Version 4.1 (ESM4.1), which builds on component and coupled model developments at GFDL over 2013–2018 for coupled carbon‐chemistry‐climate simulation contributing to the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's CM4.0 development effort that focuses on ocean resolution for physical climate, ESM4.1 focuses on comprehensiveness of Earth system interactions. ESM4.1 features doubled horizontal resolution of both atmosphere (2° to 1°) and ocean (1° to 0.5°) relative to GFDL's previous‐generation coupled ESM2‐carbon and CM3‐chemistry models. ESM4.1 brings together key representational advances in CM4.0 dynamics and physics along with those in aerosols and their precursor emissions, land ecosystem vegetation and canopy competition, and multiday fire; ocean ecological and biogeochemical interactions, comprehensive land‐atmosphere‐ocean cycling of CO2, dust and iron, and interactive ocean‐atmosphere nitrogen cycling are described in detail across this volume of JAMES and presented here in terms of the overall coupling and resulting fidelity. ESM4.1 provides much improved fidelity in CO2 and chemistry over ESM2 and CM3, captures most of CM4.0's baseline simulations characteristics, and notably improves on CM4.0 in (1) Southern Ocean mode and intermediate water ventilation, (2) Southern Ocean aerosols, and (3) reduced spurious ocean heat uptake. ESM4.1 has reduced transient and equilibrium climate sensitivity compared to CM4.0. Fidelity concerns include (1) moderate degradation in sea surface temperature biases, (2) degradation in aerosols in some regions, and (3) strong centennial scale climate modulation by Southern Ocean convection.

Simulation of coupled carbon‐climate requires representation of ocean carbon cycling, but the computational burden of simulating the dozens of prognostic tracers in state‐of‐the‐art biogeochemistry ecosystem models can be prohibitive. We describe a six‐tracer biogeochemistry module of steady‐state phytoplankton and zooplankton dynamics in Biogeochemistry with Light, Iron, Nutrients and Gas (BLING version 2) with particular emphasis on enhancements relative to the previous version and evaluate its implementation in Geophysical Fluid Dynamics Laboratory's (GFDL) fourth‐generation climate model (CM4.0) with ¼° ocean. Major geographical and vertical patterns in chlorophyll, phosphorus, alkalinity, inorganic and organic carbon, and oxygen are well represented. Major biases in BLINGv2 include overly intensified production in high‐productivity regions at the expense of productivity in the oligotrophic oceans, overly zonal structure in tropical phosphorus, and intensified hypoxia in the eastern ocean basins as is typical in climate models. Overall, while BLINGv2 structural limitations prevent sophisticated application to plankton physiology, ecology, or biodiversity, its ability to represent major organic, inorganic, and solubility pumps makes it suitable for many coupled carbon‐climate and biogeochemistry studies including eddy interactions in the ocean interior. We further overview the biogeochemistry and circulation mechanisms that shape carbon uptake over the historical period. As an initial analysis of model historical and idealized response, we show that CM4.0 takes up slightly more anthropogenic carbon than previous models in part due to enhanced ventilation in the absence of an eddy parameterization. The CM4.0 biogeochemistry response to CO2 doubling highlights a mix of large declines and moderate increases consistent with previous models.

Climate variations can have profound impacts on marine ecosystems and the socio-economic systems that may depend upon them. Temperature, pH, oxygen (O2) and net primary production (NPP) are commonly considered to be important marine ecosystem drivers, but the potential predictability of these drivers is largely unknown. Here, we use a comprehensive Earth system model within a perfect modelling framework to show that all four ecosystem drivers are potentially predictable on global scales and at the surface up to 3 years in advance. However, there are distinct regional differences in the potential predictability of these drivers. Maximum potential predictability (> 10 years) is found at the surface for temperature and O2 in the Southern Ocean and for temperature, O2 and pH in the North Atlantic. This is tied to ocean overturning structures with memory or inertia with enhanced predictability in winter. Additionally, these four drivers are highly potentially predictable in the Arctic Ocean at surface. In contrast, minimum predictability is simulated for NPP (< 1 years) in the Southern Ocean. Potential predictability for temperature, O2 and pH increases with depth to more than 10 years below the thermocline, except in the tropical Pacific and Indian Ocean, where predictability is also three to five years in the thermocline. This study indicating multi-year (at surface) and decadal (subsurface) potential predictability for multiple ecosystem drivers is intended as a foundation to foster broader community efforts in developing new predictions of marine ecosystem drivers.

It is well established that the ocean is currently losing dissolved oxygen (O2) in response to ocean warming, but the long‐term, equilibrium response of O2 to a warmer climate is neither well quantified nor understood. Here, we use idealized multi‐millennial global warming simulations with a comprehensive Earth system model to show that the equilibrium response in ocean O2 differs fundamentally from the ongoing transient response. After physical equilibration of the model (>4000 yr) under a two‐times preindustrial CO2 scenario, the deep ocean is better ventilated and oxygenated compared to preindustrial conditions, even though the deep ocean is substantially warmer. The recovery and overshoot of deep convection in the Weddell Sea and especially the Ross Sea after ~720 yr causes a strong increase in deep ocean O2 that overcompensates the solubility‐driven decrease in O2. In contrast, O2 in most of the upper tropical ocean is substantially depleted owing to the warming‐induced O2 decrease dominating over changes in ventilation and biology. Our results emphasize the millennial‐scale impact of global warming on marine life, with some impacts emerging many centuries or even millennia after atmospheric CO2 has stabilized.

The coastal ecosystem of the Gulf of Alaska (GOA) is especially vulnerable to the effects of ocean acidification and climate change that can only be understood within the context of the natural variability of physical and chemical conditions. Controlled by its complex bathymetry, iron enriched freshwater discharge, and wind and solar radiation, the GOA is a highly dynamic system that exhibits large inorganic carbon variability from subseasonal to interannual timescales. This variability is poorly understood due to the lack of observations in this expansive and remote region. To improve our conceptual understanding of the system, we developed a new model set-up for the GOA that couples the three-dimensional Regional Oceanic Model System (ROMS), the Carbon, Ocean Biogeochemistry and Lower Trophic (COBALT) ecosystem model, and a high resolution terrestrial hydrological model. Here, we evaluate the model on seasonal to interannual timescales using the best available inorganic carbon observations. The model was particularly successful in reproducing observed aragonite oversaturation and undersaturation of near-bottom water in May and September, respectively. The largest deficiency of the model is perhaps its inability to adequately simulate spring time surface inorganic carbon chemistry, as it overestimates surface dissolved inorganic carbon, which translates into an underestimation of the surface aragonite saturation state at this time. We also use the model to describe the seasonal cycle and drivers of inorganic carbon parameters along the Seward Line transect in under-sampled months. As such, model output suggests that a majority of the near-bottom water along the Seward Line is seasonally under-saturated with regard to aragonite between June and January, as a result of upwelling and remineralization. Such an extensive period of reoccurring aragonite undersaturation may be harmful to CO2 sensitive organisms. Furthermore, the influence of freshwater not only decreases aragonite saturation state in coastal surface waters in summer and fall, but simultaneously also decreases surface pCO2, thereby decoupling the aragonite saturation state from pCO2. The full seasonal cycle and geographic extent of the GOA region is undersampled, and our model results give new and important insights for months of the year and areas that lack in situ inorganic carbon observations.

We describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Atmosphere Model version 4.1 (AM4.1), which builds on developments at GFDL over 2013–2018 for coupled carbon‐chemistry‐climate simulation as part of the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's AM4.0 development effort, which focused on physical and aerosol interactions and which is used as the atmospheric component of CM4.0, AM4.1 focuses on comprehensiveness of Earth system interactions. Key features of this model include doubled horizontal resolution of the atmosphere (~200 to ~100 km) with revised dynamics and physics from GFDL's previous‐generation AM3 atmospheric chemistry‐climate model. AM4.1 features improved representation of atmospheric chemical composition, including aerosol and aerosol precursor emissions, key land‐atmosphere interactions, comprehensive land‐atmosphere‐ocean cycling of dust and iron, and interactive ocean‐atmosphere cycling of reactive nitrogen. AM4.1 provides vast improvements in fidelity over AM3, captures most of AM4.0's baseline simulations characteristics, and notably improves on AM4.0 in the representation of aerosols over the Southern Ocean, India, and China—even with its interactive chemistry representation—and in its manifestation of sudden stratospheric warmings in the coldest months. Distributions of reactive nitrogen and sulfur species, carbon monoxide, and ozone are all substantially improved over AM3. Fidelity concerns include degradation of upper atmosphere equatorial winds and of aerosols in some regions.

Human land use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth's surface, with consequences for climate and other ecosystem services. In the future, land use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Climate Research Program Coupled Model Intercomparison Project (CMIP6), the international community has developed the next generation of advanced Earth system models (ESMs) to estimate the combined effects of human activities (e.g., land use and fossil fuel emissions) on the carbon–climate system. A new set of historical data based on the History of the Global Environment database (HYDE), and multiple alternative scenarios of the future (2015–2100) from Integrated Assessment Model (IAM) teams, is required as input for these models. With most ESM simulations for CMIP6 now completed, it is important to document the land use patterns used by those simulations. Here we present results from the Land-Use Harmonization 2 (LUH2) project, which smoothly connects updated historical reconstructions of land use with eight new future projections in the format required for ESMs. The harmonization strategy estimates the fractional land use patterns, underlying land use transitions, key agricultural management information, and resulting secondary lands annually, while minimizing the differences between the end of the historical reconstruction and IAM initial conditions and preserving changes depicted by the IAMs in the future. The new approach builds on a similar effort from CMIP5 and is now provided at higher resolution (0.25∘×0.25∘) over a longer time domain (850–2100, with extensions to 2300) with more detail (including multiple crop and pasture types and associated management practices) using more input datasets (including Landsat remote sensing data) and updated algorithms (wood harvest and shifting cultivation); it is assessed via a new diagnostic package. The new LUH2 products contain > 50 times the information content of the datasets used in CMIP5 and are designed to enable new and improved estimates of the combined effects of land use on the global carbon–climate system.

Land-use change affects both the quality and quantity of soil organic carbon (SOC) and leads to changes in ecosystem functions such as productivity and environmental regulation. Future changes in SOC are, however, highly uncertain owing to its heterogeneity and complexity. In this study, we analyzed the outputs of simulations of SOC stock by Earth system models (ESMs), most of which are participants in the Land-Use Model Intercomparison Project. Using a common protocol and the same forcing data, the ESMs simulated SOC distribution patterns and their changes during historical (1850–2014) and future (2015–2100) periods. Total SOC stock increased in many simulations over the historical period (30 ± 67 Pg C) and under future climate and land-use conditions (48 ± 32 Pg C for ssp126 and 49 ± 58 Pg C for ssp370). Land-use experiments indicated that changes in SOC attributable to land-use scenarios were modest at the global scale, in comparison with climatic and rising CO2 impacts, but they were notable in several regions. Future net soil carbon sequestration rates estimated by the ESMs were roughly 0.4‰ yr−1 (0.6 Pg C yr−1). Although there were considerable inter-model differences, the rates are still remarkable in terms of their potential for mitigation of global warming. The disparate results among ESMs imply that key parameters that control processes such as SOC residence time need to be better constrained and that more comprehensive representation of land management impacts on soils remain critical for understanding the long-term potential of soils to sequester carbon.

Anthropogenic climate change leads to ocean warming, acidification, deoxygenation and reductions in near-surface nutrient concentrations, all of which are expected to affect marine ecosystems. Here we assess projections of these drivers of environmental change over the twenty-first century from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) that were forced under the CMIP6 Shared Socioeconomic Pathways (SSPs). Projections are compared to those from the previous generation (CMIP5) forced under the Representative Concentration Pathways (RCPs). 10 CMIP5 and 13 CMIP6 models are used in the two multi-model ensembles. Under the high-emission scenario SSP5–8.5, the model mean change (2080–2099 mean values relative to 1870–1899) in sea surface temperature, surface pH, subsurface (100–600 m) oxygen concentration and euphotic (0–100 m) nitrate concentration is +3.48 ± 0.78 °C, −0.44 ± 0.005, −13.27 ± 5.28 mmol m−3 and −1.07 ± 0.45 mmol m−3, respectively. Under the low-emission, high-mitigation scenario SSP1–2.6, the corresponding changes are +1.42 ± 0.32 °C, −0.16 ± 0.002, −6.36 ± 2.92 mmol m−3 and −0.53 ± 0.23 mmol m−3. Projected exposure of the marine ecosystem to these drivers of ocean change depends largely on the extent of future emissions, consistent with previous studies. The Earth system models in CMIP6 generally project greater surface warming, acidification, deoxygenation and euphotic nitrate reductions than those from CMIP5 under comparable radiative forcing, with no reduction in inter-model uncertainties. Under the high-emission CMIP5 scenario RCP8.5, the corresponding changes in sea surface temperature, surface pH, subsurface oxygen and euphotic nitrate concentration are +3.04 ± 0.62 °C, −0.38 ± 0.005, −9.51 ± 2.13 mmol m−3 and −0.66 ± 0.49 mmol m−3, respectively. The greater surface acidification in CMIP6 is primarily a consequence of the SSPs having higher associated atmospheric CO2 concentrations than their RCP analogues. The increased projected warming results from a general increase in the climate sensitivity of CMIP6 models relative to those of CMIP5. This enhanced warming results in greater increases in upper ocean stratification in CMIP6 projections, which contributes to greater reductions in euphotic nitrate and subsurface oxygen ventilation.

Reducing surface ozone to meet the European Union’s target for human health has proven challenging despite stringent controls on ozone precursor emissions over recent decades. The most extreme ozone pollution episodes are linked to heatwaves and droughts, which are increasing in frequency and intensity over Europe, with severe impacts on natural and human systems. Here, we use observations and Earth system model simulations for the period 1960–2018 to show that ecosystem–atmosphere interactions, especially reduced ozone removal by water-stressed vegetation, exacerbate ozone air pollution over Europe. These vegetation feedbacks worsen peak ozone episodes during European mega-droughts, such as the 2003 event, offsetting much of the air quality improvements gained from regional emissions controls. As the frequency of hot and dry summers is expected to increase over the coming decades, this climate penalty could be severe and therefore needs to be considered when designing clean air policy in the European Union.

Among marine organisms, gelatinous zooplankton (GZ; cnidarians, ctenophores, and pelagic tunicates) are unique in their energetic efficiency, as the gelatinous body plan allows them to process and assimilate high proportions of oceanic carbon. Upon death, their body shape facilitates rapid sinking through the water column, resulting in carcass depositions on the seafloor (“jelly‐falls”). GZ are thought to be important components of the biological pump, but their overall contribution to global carbon fluxes remains unknown. Using a data‐driven, three‐dimensional, carbon cycle model resolved to a 1° global grid, with a Monte Carlo uncertainty analysis, we estimate that GZ consumed 7.9–13 Pg C y−1 in phytoplankton and zooplankton, resulting in a net production of 3.9–5.8 Pg C y−1 in the upper ocean (top 200 m), with the largest fluxes from pelagic tunicates. Non‐predation mortality (carcasses) comprised 25% of GZ production, and combined with the much greater fecal matter flux, total GZ particulate organic carbon (POC) export at 100 m was 1.6–5.2 Pg C y−1, equivalent to 32–40% of the global POC export. The fast sinking GZ export resulted in a high transfer efficiency (Teff) of 38–62% to 1,000 m and 25–40% to the seafloor. Finally, jelly‐falls at depths >50 m are likely unaccounted for in current POC flux estimates and could increase benthic POC flux by 8–35%. The significant magnitude of and distinct sinking properties of GZ fluxes support a critical yet underrecognized role of GZ carcasses and fecal matter to the biological pump and air‐sea carbon balance.

Tropical forests are a key determinant of the functioning of the Earth system, but remain a major source of uncertainty in carbon cycle models and climate change projections. In this study, we present an updated land model (LM3PPA‐TV) to improve the representation of tropical forest structure and dynamics in Earth system models (ESMs). The development and parameterization of LM3PPA‐TV drew on extensive datasets on tropical tree traits and long‐term field censuses from Barro Colorado Island (BCI), Panama. The model defines a new plant functional type (PFT) based on the characteristics of shade‐tolerant, tropical tree species, implements a new growth allocation scheme based on realistic tree allometries, incorporates hydraulic constraints on biomass accumulation, and features a new compartment for tree branches and branch fall dynamics. Simulation experiments reproduced observed diurnal and seasonal patterns in stand‐level carbon and water fluxes, as well as mean canopy and understory tree growth rates, tree size distributions, and stand‐level biomass on BCI. Simulations at multiple sites captured considerable variation in biomass and size structure across the tropical forest biome, including observed responses to precipitation and temperature. Model experiments suggested a major role of water limitation in controlling geographical variation forest biomass and structure. However, the failure to simulate tropical forests under extreme conditions and the systematic underestimation of forest biomass in Paleotropical locations highlighted the need to incorporate variation in hydraulic traits and multiple PFTs that capture the distinct floristic composition across tropical domains. The continued pressure on tropical forests from global change demands models which are able to simulate alternative successional pathways and their pace to recovery. LM3PPA‐TV provides a tool to investigate geographic variation in tropical forests and a benchmark to continue improving the representation of tropical forests dynamics and their carbon storage potential in ESMs.

We assess the effective radiative forcing due to ozone‐depleting substances using models participating in the Aerosols and Chemistry and Radiative Forcing Model Intercomparison Projects (AerChemMIP, RFMIP). A large intermodel spread in this globally averaged quantity necessitates an “emergent constraint” approach whereby we link the radiative forcing to ozone declines measured and simulated during 1979–2000, excluding two volcanically perturbed periods. During this period, ozone‐depleting substances were increasing, and several merged satellite‐based climatologies document the ensuing decline of total‐column ozone. Using these analyses, we find an effective radiative forcing of −0.05 to 0.13 W m−2. Our best estimate (0.04 W m−2) is on the edge of the “likely” range given by the Fifth Assessment Report of IPCC of 0.03 to 0.33 W m−2 but is in better agreement with two other literature results.

The imprint of anthropogenic activities on the marine nitrogen (N) cycle remains challenging to represent in global models, in part because of uncertainties regarding the source of marine N to the atmosphere. While N inputs of terrestrial origin present a truly external perturbation, a significant fraction of N deposition over the ocean arises from oceanic ammonia (NH3) outgassing that is subsequently deposited in other ocean regions. Here, we describe advances in the Geophysical Fluid Dynamics Laboratory's (GFDL) Earth System Model 4 (ESM4.1) aimed at improving the representation of the exchange of N between atmosphere and ocean and its response to changes in ocean acidity and N deposition. We find that the simulated present‐day NH3 outgassing (3.1 TgN yr−1) is 7% lower than under preindustrial conditions, which reflects the compensating effects of increasing CO2 (−16%) and N enrichment of ocean waters (+9%). This change is spatially heterogeneous, with decreases in the open ocean (−13%) and increases in coastal regions (+15%) dominated by coastal N enrichment. The ocean outgassing of ammonia is shown to increase the transport of N from N‐rich to N‐poor ocean regions, where carbon export at 100 m increases by 0.5%. The implications of the strong response of NH3 ocean outgassing to CO2 for the budget of NH3 in the remote marine atmosphere and its imprint in ice cores are discussed.

Global climate change is expected to impact ocean ecosystems through increases in temperature, decreases in pH and oxygen, increased stratification, with subsequent declines in primary productivity. These impacts propagate through the food chain leading to amplified effects on secondary producers and higher trophic levels. Similarly, climate change may disproportionately affect different species, with impacts depending on their ecological niche. To investigate how global environmental change will alter fish assemblages and productivity, we used a spatially explicit mechanistic model of the three main fish functional types reflected in fisheries catches (FEISTY) coupled to an Earth system model (GFDL-ESM2M) to make projections out to 2100. We additionally explored the sensitivity of projections to uncertainties in widely used metabolic allometries and their temperature dependence. When integrated globally, the biomass and production of all types of fish decreased under a high emissions scenario (RCP 8.5) compared to mean contemporary conditions. Projections also revealed strong increases in the ratio of pelagic zooplankton production to benthic production, a dominant driver of the abundance of large pelagic fish vs. demersal fish under historical conditions. Increases in this ratio led to a “pelagification” of ecosystems exemplified by shifts from benthic-based food webs toward pelagic-based ones. The resulting pelagic systems, however, were dominated by forage fish, as large pelagic fish suffered from increasing metabolic demands in a warming ocean and from declines in zooplankton productivity that were amplified at higher trophic levels. Patterns of relative change between functional types were robust to uncertainty in metabolic allometries and temperature dependence, though projections of the large pelagic fish had the greatest uncertainty. The same accumulation of trophic impacts that underlies the amplification of productivity trends at higher trophic levels propagates to the projection spread, creating an acutely uncertain future for the ocean’s largest predatory fish.

Dust emission is initiated when surface wind velocities exceed the threshold of wind erosion. Most dust models used constant threshold values globally. Here we use satellite products to characterize the frequency of dust events and surface properties. By matching this frequency derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products with surface winds, we are able to retrieve a climatological monthly global distribution of wind erosion threshold (Vthreshold) over dry and sparsely-vegetated surface. This monthly two-dimensional threshold velocity is then implemented into the Geophysical Fluid Dynamics Laboratory coupled land-atmosphere model (AM4.0/LM4.0). It is found that the climatology of dust optical depth (DOD) and total aerosol optical depth, surface PM10 dust concentrations, and seasonal cycle of DOD are better captured over the dust belt (i.e. North Africa and the Middle East) by simulations with the new wind erosion threshold than those using the default globally constant threshold. The most significant improvement is the frequency distribution of dust events, which is generally ignored in model evaluation. By using monthly rather than annual mean Vthreshold, all comparisons with observations are further improved. The monthly global threshold of wind erosion can be retrieved under different spatial resolutions to match the resolution of dust models and thus can help improve the simulations of dust climatology and seasonal cycle as well as dust forecasting.

Most present forecast systems for estuaries predict conditions for only a few days into the future. However, there are many reasons to expect that skillful estuarine forecasts are possible for longer time periods, including increasingly skillful extended atmospheric forecasts, the potential for lasting impacts of atmospheric forcing on estuarine conditions, and the predictability of tidal cycles. In this study, we test whether skillful estuarine forecasts are possible for up to 35 days into the future by combining an estuarine model of Chesapeake Bay with 35‐day atmospheric forecasts from an operational weather model. When compared with both a hindcast simulation from the same estuarine model and with observations, the estuarine forecasts for surface water temperature are skillful up to about two weeks into the future, and the forecasts for bottom temperature, surface and bottom salinity, and density stratification are skillful for all or the majority of the forecast period. Bottom oxygen forecasts are skillful when compared to the model hindcast, but not when compared with observations. We also find that skill for all variables in the estuary can be improved by taking the mean of multiple estuarine forecasts driven by an ensemble of atmospheric forecasts. Finally, we examine the forecasts in detail using two case studies of extreme events, and we discuss opportunities for improving the forecast skill.

The combined effects of climate change and other human-induced stressors have severely degraded marine ecosystems worldwide and pose an unprecedented threat to humanity1. There is an urgent need to understand current and future rates of change while attempting to mitigate impact. We argue that the Galapagos Islands, once the inspiration for the ground-breaking theory of evolution by means of natural selection, now in the Anthropocene can serve as a natural laboratory to study co-evolutionary processes between humans and the species we interact with as climate change pushes ecosystems and dependent communities further away from historical baselines.

Anthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to the climate system (noise). Here we use Large Ensemble (LE) experiments from four Earth system models (ESMs) with multiple emissions scenarios to estimate Time of Emergence (ToE) and partition projection uncertainty for anthropogenic signals in five biogeochemically important upper-ocean variables. We find ToEs are robust across ESMs for sea surface temperature and the invasion of anthropogenic carbon; emergence time scales are 20–30 yr. For the biological carbon pump, and sea surface chlorophyll and salinity, emergence time scales are longer (50+ yr), less robust across the ESMs, and more sensitive to the forcing scenario considered. We find internal variability uncertainty, and model differences in the internal variability uncertainty, can be consequential sources of uncertainty for projecting regional changes in ocean biogeochemistry over the coming decades. In combining structural, scenario, and internal variability uncertainty, this study represents the most comprehensive characterization of biogeochemical emergence time scales and uncertainty to date. Our findings delineate critical spatial and duration requirements for marine observing systems to robustly detect anthropogenic change.

Purpose of Review: The changes or updates in ocean biogeochemistry component have been mapped between CMIP5 and CMIP6 model versions, and an assessment made of how far these have led to improvements in the simulated mean state of marine biogeochemical models within the current generation of Earth system models (ESMs). Recent Findings: The representation of marine biogeochemistry has progressed within the current generation of Earth system models. However, it remains difficult to identify which model updates are responsible for a given improvement. In addition, the full potential of marine biogeochemistry in terms of Earth system interactions and climate feedback remains poorly examined in the current generation of Earth system models. Summary: Increasing availability of ocean biogeochemical data, as well as an improved understanding of the underlying processes, allows advances in the marine biogeochemical components of the current generation of ESMs. The present study scrutinizes the extent to which marine biogeochemistry components of ESMs have progressed between the 5th and the 6th phases of the Coupled Model Intercomparison Project (CMIP).

We analyse historical (1850–2014) atmospheric hydroxyl (OH) and methane lifetime data from Coupled Model Intercomparison Project Phase 6 (CMIP6)/Aerosols and Chemistry Model Intercomparison Project (AerChemMIP) simulations. Tropospheric OH changed little from 1850 up to around 1980, then increased by around 9 % up to 2014, with an associated reduction in methane lifetime. The model-derived OH trends from 1980 to 2005 are broadly consistent with trends estimated by several studies that infer OH from inversions of methyl chloroform and associated measurements; most inversion studies indicate decreases in OH since 2005. However, the model results fall within observational uncertainty ranges. The upward trend in modelled OH since 1980 was mainly driven by changes in anthropogenic near-term climate forcer emissions (increases in anthropogenic nitrogen oxides and decreases in CO). Increases in halocarbon emissions since 1950 have made a small contribution to the increase in OH, whilst increases in aerosol-related emissions have slightly reduced OH. Halocarbon emissions have dramatically reduced the stratospheric methane lifetime by about 15 %–40 %; most previous studies assumed a fixed stratospheric lifetime. Whilst the main driver of atmospheric methane increases since 1850 is emissions of methane itself, increased ozone precursor emissions have significantly modulated (in general reduced) methane trends. Halocarbon and aerosol emissions are found to have relatively small contributions to methane trends. These experiments do not isolate the effects of climate change on OH and methane evolution; however, we calculate residual terms that are due to the combined effects of climate change and non-linear interactions between drivers. These residual terms indicate that non-linear interactions are important and differ between the two methodologies we use for quantifying OH and methane drivers. All these factors need to be considered in order to fully explain OH and methane trends since 1850; these factors will also be important for future trends.

This contribution describes the ocean biogeochemical component of the Geophysical Fluid Dynamics Laboratory's Earth System Model 4.1 (GFDL‐ESM4.1), assesses GFDL‐ESM4.1's capacity to capture observed ocean biogeochemical patterns, and documents its response to increasing atmospheric CO2. Notable differences relative to the previous generation of GFDL ESM's include enhanced resolution of plankton food web dynamics, refined particle remineralization, and a larger number of exchanges of nutrients across Earth system components. During model spin‐up, the carbon drift rapidly fell below the 10 Pg C per century equilibration criterion established by the Coupled Climate‐Carbon Cycle Model Intercomparison Project (C4MIP). Simulations robustly captured large‐scale observed nutrient distributions, plankton dynamics, and characteristics of the biological pump. The model overexpressed phosphate limitation and open ocean hypoxia in some areas but still yielded realistic surface and deep carbon system properties, including cumulative carbon uptake since preindustrial times and over the last decades that is consistent with observation‐based estimates. The model's response to the direct and radiative effects of a 200% atmospheric CO2 increase from preindustrial conditions (i.e., years 101–120 of a 1% CO2 yr−1 simulation) included (a) a weakened, shoaling organic carbon pump leading to a 38% reduction in the sinking flux at 2,000 m; (b) a two‐thirds reduction in the calcium carbonate pump that nonetheless generated only weak calcite compensation on century time‐scales; and, in contrast to previous GFDL ESMs, (c) a moderate reduction in global net primary production that was amplified at higher trophic levels. We conclude with a discussion of model limitations and priority developments.

Aim To address the uncertainty associated with climate‐driven biogeographical changes in commercial fisheries species through an ensemble species distribution modelling (SDM) approach. Location Northeast US Continental Shelf Large Marine Ecosystem (NEUS‐LME). Methods We combined an ensemble SDM platform (BIOMOD 2) and a high‐resolution global climate model (NOAA GFDL CM2.6) to quantify spatiotemporal changes in habitat of two commercially important species in the Northeast US Continental Shelf Large Marine Ecosystem (NEUS‐LME); American lobster (Homarus americanus); and sea scallop (Placopecten magellanicus). An ensemble SDM was calibrated using multi‐decadal fisheries‐independent surveys (1984–2016). Statistically weighted species‐specific ensemble SDM outputs were combined with 80 years of projected bottom temperature and salinity changes in response to a high greenhouse gas emissions scenario (an annual 1% increase in atmospheric CO2). Results Statistically significant changes (p < .05) in habitat suitability for both species were found over a large portion of the study area. Sea scallop undergoes a northward shift over the study period, while American lobster moves further offshore. The ensemble projections showed that several management zones were identified with increases and decreases in species‐specific habitat. Uncertainty due to variations in ensemble member models was also found in the direction of change within each management zone. Main conclusions This study provides ensemble estimates of climate‐driven changes and associated uncertainties in the biogeography of two economically important species in the United States. Projected climate change in the NEUS‐LME will pose management challenges, and our ensemble projections provide useful information for climate‐ready management of commercial fisheries.

Poor air quality is currently responsible for large impacts on human health across the world. In addition, the air pollutants ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5) are also radiatively active in the atmosphere and can influence Earth's climate. It is important to understand the effect of air quality and climate mitigation measures over the historical period and in different future scenarios to ascertain any impacts from air pollutants on both climate and human health. The Coupled Model Intercomparison Project Phase 6 (CMIP6) presents an opportunity to analyse the change in air pollutants simulated by the current generation of climate and Earth system models that include a representation of chemistry and aerosols (particulate matter). The shared socio-economic pathways (SSPs) used within CMIP6 encompass a wide range of trajectories in precursor emissions and climate change, allowing for an improved analysis of future changes to air pollutants. Firstly, we conduct an evaluation of the available CMIP6 models against surface observations of O3 and PM2.5. CMIP6 models consistently overestimate observed surface O3 concentrations across most regions and in most seasons by up to 16 ppb, with a large diversity in simulated values over Northern Hemisphere continental regions. Conversely, observed surface PM2.5 concentrations are consistently underestimated in CMIP6 models by up to 10 µg m−3, particularly for the Northern Hemisphere winter months, with the largest model diversity near natural emission source regions. The biases in CMIP6 models when compared to observations of O3 and PM2.5 are similar to those found in previous studies. Over the historical period (1850–2014) large increases in both surface O3 and PM2.5 are simulated by the CMIP6 models across all regions, particularly over the mid to late 20th century, when anthropogenic emissions increase markedly. Large regional historical changes are simulated for both pollutants across East and South Asia with an annual mean increase of up to 40 ppb for O3 and 12 µg m−3 for PM2.5. In future scenarios containing strong air quality and climate mitigation measures (ssp126), annual mean concentrations of air pollutants are substantially reduced across all regions by up to 15 ppb for O3 and 12 µg m−3 for PM2.5. However, for scenarios that encompass weak action on mitigating climate and reducing air pollutant emissions (ssp370), annual mean increases in both surface O3 (up 10 ppb) and PM2.5 (up to 8 µg m−3) are simulated across most regions, although, for regions like North America and Europe small reductions in PM2.5 are simulated due to the regional reduction in precursor emissions in this scenario. A comparison of simulated regional changes in both surface O3 and PM2.5 from individual CMIP6 models highlights important regional differences due to the simulated interaction of aerosols, chemistry, climate and natural emission sources within models. The projection of regional air pollutant concentrations from the latest climate and Earth system models used within CMIP6 shows that the particular future trajectory of climate and air quality mitigation measures could have important consequences for regional air quality, human health and near-term climate. Differences between individual models emphasise the importance of understanding how future Earth system feedbacks influence natural emission sources, e.g. response of biogenic emissions under climate change.

Marine microbes form the base of ocean food webs and drive ocean biogeochemical cycling. Yet little is known about the ability of microbial populations to adapt as they are advected through changing conditions. Here, we investigated the interplay between physical and biological timescales using a model of adaptation and an eddy-resolving ocean circulation climate model. Two criteria were identified that relate the timing and nature of adaptation to the ratio of physical to biological timescales. Genetic adaptation was impeded in highly variable regimes by nongenetic modifications but was promoted in more stable environments. An evolutionary trade-off emerged where greater short-term nongenetic transgenerational effects (low-γ strategy) enabled rapid responses to environmental fluctuations but delayed genetic adaptation, while fewer short-term transgenerational effects (high-γ strategy) allowed faster genetic adaptation but inhibited short-term responses. Our results demonstrate that the selective pressures for organisms within a single water mass vary based on differences in generation timescales resulting in different evolutionary strategies being favored. Organisms that experience more variable environments should favor a low-γ strategy. Furthermore, faster cell division rates should be a key factor in genetic adaptation in a changing ocean. Understanding and quantifying the relationship between evolutionary and physical timescales is critical for robust predictions of future microbial dynamics.

GFDL's new CM4.0 climate model has high transient and equilibrium climate sensitivities near the middle of the upper half of CMIP5 models. The CMIP5 models have been criticized for excessive sensitivity based on observations of present‐day warming and heat uptake and estimates of radiative forcing. An ensemble of historical simulations with CM4.0 produces warming and heat uptake that are consistent with these observations under forcing that is at the middle of the assessed distribution. Energy budget‐based methods for estimating sensitivities based on these quantities underestimate CM4.0's sensitivities when applied to its historical simulations. However, we argue using a simple attribution procedure that CM4.0's warming evolution indicates excessive transient sensitivity to greenhouse gases. This excessive sensitivity is offset prior to recent decades by excessive response to aerosol and land use changes.

We document the configuration and emergent simulation features from the Geophysical Fluid Dynamics Laboratory (GFDL) OM4.0 ocean/sea‐ice model. OM4 serves as the ocean/sea‐ice component for the GFDL climate and Earth system models. It is also used for climate science research and is contributing to the Coupled Model Intercomparison Project version 6 Ocean Model Intercomparison Project (CMIP6/OMIP). The ocean component of OM4 uses version 6 of the Modular Ocean Model (MOM6) and the sea‐ice component uses version 2 of the Sea Ice Simulator (SIS2), which have identical horizontal grid layouts (Arakawa C‐grid). We follow the Coordinated Ocean‐sea ice Reference Experiments (CORE) protocol to assess simulation quality across a broad suite of climate relevant features. We present results from two versions differing by horizontal grid spacing and physical parameterizations: OM4p5 has nominal 0.5° spacing and includes mesoscale eddy parameterizations and OM4p25 has nominal 0.25° spacing with no mesoscale eddy parameterization. MOM6 makes use of a vertical Lagrangian‐remap algorithm that enables general vertical coordinates. We show that use of a hybrid depth‐isopycnal coordinate reduces the mid‐depth ocean warming drift commonly found in pure z* vertical coordinate ocean models. To test the need for the mesoscale eddy parameterization used in OM4p5, we examine the results from a simulation that removes the eddy parameterization. The water mass structure and model drift are physically degraded relative to OM4p5, thus supporting the key role for a mesoscale closure at this resolution.

Substantial interannual variability in marine fish recruitment (i.e., the number of young fish entering a fishery each year) has been hypothesized to be related to whether the timing of fish spawning matches that of seasonal plankton blooms. Environmental processes that control the phenology of blooms, such as stratification, may differ from those that influence fish spawning, such as temperature‐linked reproductive maturation. These different controlling mechanisms could cause the timing of these events to diverge under climate change with negative consequences for fisheries. We use an earth system model to examine the impact of a high‐emissions, climate‐warming scenario (RCP8.5) on the future spawning time of two classes of temperate, epipelagic fishes: “geographic spawners” whose spawning grounds are defined by fixed geographic features (e.g., rivers, estuaries, reefs) and “environmental spawners” whose spawning grounds move responding to variations in environmental properties, such as temperature. By the century's end, our results indicate that projections of increased stratification cause spring and summer phytoplankton blooms to start 16 days earlier on average (±0.05 days SE) at latitudes >40°N. The temperature‐linked phenology of geographic spawners changes at a rate twice as fast as phytoplankton, causing these fishes to spawn before the bloom starts across >85% of this region. “Extreme events,” defined here as seasonal mismatches >30 days that could lead to fish recruitment failure, increase 10‐fold for geographic spawners in many areas under the RCP8.5 scenario. Mismatches between environmental spawners and phytoplankton were smaller and less widespread, although sizable mismatches still emerged in some regions. This indicates that range shifts undertaken by environmental spawners may increase the resiliency of fishes to climate change impacts associated with phenological mismatches, potentially buffering against declines in larval fish survival, recruitment, and fisheries. Our model results are supported by empirical evidence from ecosystems with multidecadal observations of both fish and phytoplankton phenology.

Warming‐driven expansion of the oxygen minimum zone (OMZ) in the equatorial Pacific would bring very low oxygen waters closer to the ocean surface and possibly impact global carbon/nutrient cycles and local ecosystems. Global coarse Earth System Models (ESMs) show, however, disparate trends that poorly constrain these future changes in the upper OMZ. Using an ESM with a high‐resolution ocean (1/10°), we show that a realistic representation of the Equatorial Undercurrent (EUC) dynamics is crucial to represent the upper OMZ structure and its temporal variability. We demonstrate that coarser ESMs commonly misrepresent the EUC, leading to an unrealistic “tilt” of the OMZ (e.g., shallowing toward the east) and an exaggerated sensitivity to EUC changes overwhelming other important processes like diffusion and biology. This shortcoming compromises the ability to reproduce the OMZ variability and could explain the disparate trends in ESMs projections.

The tropical Pacific is a major natural source of CO2 to the atmosphere and contributor to global air‐sea carbon flux variability. High time‐resolution wind and CO2 measurements from equatorial Pacific moorings reveal the primary factor controlling mooring‐observed flux variability to be near‐surface wind variability, above CO2 variability, in this region over the last 10 years. The analysis product winds used most widely in previous calculations of basin‐scale carbon flux are compared with mooring winds and found to exhibit significant differences in mean, variability, and trend. Earth system model calculations are in basic agreement with the mooring results and used to estimate effects of wind uncertainty on our knowledge of regional air‐sea carbon exchange. Results show that NCEP1 and NCEP2 winds contain biases large enough to obscure the interannual variability of CO2 flux (RMSE ≈ σ) and cause spurious 25‐year (1992–2016) trend components in equatorial Pacific carbon flux of 0.038–0.039 and 0.016–0.021 Pg C yr−1 per decade, respectively. These spurious trends act to reduce by up to 50% the 25‐year trend in equatorial Pacific carbon flux simulated by the Earth system model under increasing atmospheric CO2 concentration. The Cross‐Calibrated‐Multi‐Platform wind product tracks observed variability of equatorial Pacific wind better (interannual RMSE ≈ 0.4σ) than the NCEP reanalyses when site sampled at mooring locations yet still causes a spurious regional trend (0.03 Pg C yr−1 per decade) that masks 40% of the simulated 25‐year trend in carbon flux. The mooring observations are fundamental to identifying the limitations of current wind products to characterizing long‐term trends and understanding air‐sea carbon exchange.

Recent observations have revealed significant fluctuations in near-shore hypoxia in the California Current Ecosystem (CCE). These fluctuations have been linked to changes in the biogeochemical properties (e.g. oxygen and nutrient contents) of the oceanic source waters of the California Current upwelling, and projections suggest the potential for decreased oxygen and increased nutrients in the source water under climate change. We examine both the separate and combined influences of these projected changes through a sequence of perturbation experiments using a regional coupled ocean dynamics/biogeochemistry (BGC) model of the CCE. The direct effect of a projected decline in source water oxygen is to expand the hypoxic area by in winter to in summer. This exceeds the impact of a nitrate enrichment of source waters, which expands the hypoxic area by to via stimulation of nearshore Net Primary Productivity (NPP), increased organic matter export, and subsequent enhanced remineralization and dissolved oxygen (DO) consumption at depth. The combined effect of these perturbations consistently surpasses the sum of the individual impacts, leading to to more hypoxic area. The combined biogeochemical impact greatly exceeds the response resulting from a strengthening in upwelling-favorable winds ( in hypoxic area) or the decreased oxygen solubility associated with a ocean warming (). These results emphasize the importance of improved constraints on dynamic biogeochemical changes projected along the boundaries of shelf ecosystems. While such changes are often viewed as secondary impacts of climate change relative to local warming or stratification changes, they may prove dominant drivers of coastal ecosystem change.

Many studies have been conducted on the effects of dust on rainfall in the Sahel, and generally show that African dust weakens the West African Monsoon, drying the region. This drying is often assumed to produce a positive dust‐precipitation feedback by reducing vegetation cover for the region. We directly test this relationship for the first time by using a model that explicitly simulates vegetation growth and its impact on dust emission. There are several competing effects of dust that affect plant growth: changes to rainfall, downwelling solar radiation, surface temperature, and resultant changes in surface fluxes. Our model finds that the combined effect of these processes decreases vegetation cover and productivity of the Sahel and West Africa. We determine this by comparing experiments with radiatively active dust to experiments with radiatively invisible dust. In modern conditions, the dust radiative effect decreases leaf area by 12%, productivity by 14%, and increases bare soil area by 3% across the Sahel, and by much higher amounts locally. Experiments where the vegetation experiences preindustrial rather than modern CO2 levels show that without stomatal closure, the reductions would be approximately 20‐40% stronger. In preindustrial conditions the vegetation response is weaker, despite the dust‐induced rainfall and temperature anomalies being similar. We interpret this as the vegetation being less susceptible to drought in a less evaporative climate. These vegetation responses to dust are evidence of a dust‐vegetation feedback loop whose strength varies with the mean state of the climate, and which may grow stronger in the future.

A quantification of carbon fluxes in the coastal ocean and across its boundaries, specifically the air-sea, land-to-coastal-ocean and coastal-to-open-ocean interfaces, is important for assessing the current state and projecting future trends in ocean carbon uptake and coastal ocean acidification, but is currently a missing component of global carbon budgeting. This synthesis reviews recent progress in characterizing these carbon fluxes with focus on the North American coastal ocean. Several observing networks and high-resolution regional models are now available. Recent efforts have focused primarily on quantifying net air-sea exchange of carbon dioxide (CO2). Some studies have estimated other key fluxes, such as the exchange of organic and inorganic carbon between shelves and the open ocean. Available estimates of air-sea CO2 flux, informed by more than a decade of observations, indicate that the North American margins act as a net sink for atmospheric CO2. This net uptake is driven primarily by the high-latitude regions. The estimated magnitude of the net flux is 160±80TgC/y for the North American Exclusive Economic Zone, a number that is not well constrained. The increasing concentration of inorganic carbon in coastal and open-ocean waters leads to ocean acidification. As a result conditions favouring dissolution of calcium carbonate occur regularly in subsurface coastal waters in the Arctic, which are naturally prone to low pH, and the North Pacific, where upwelling of deep, carbon-rich waters has intensified and, in combination with the uptake of anthropogenic carbon, leads to low seawater pH and aragonite saturation states during the upwelling season. Expanded monitoring and extension of existing model capabilities are required to provide more reliable coastal carbon budgets, projections of future states of the coastal ocean, and quantification of anthropogenic carbon contributions.

We describe GFDL's CM4.0 physical climate model, with emphasis on those aspects that may be of particular importance to users of this model and its simulations. The model is built with the AM4.0/LM4.0 atmosphere/land model and OM4.0 ocean model. Topics include the rationale for key choices made in the model formulation, the stability as well as drift of the pre‐industrial control simulation, and comparison of key aspects of the historical simulations with observations from recent decades. Notable achievements include the relatively small biases in seasonal spatial patterns of top‐of‐atmosphere fluxes, surface temperature, and precipitation; reduced double Intertropical Convergence Zone bias; dramatically improved representation of ocean boundary currents; a high quality simulation of climatological Arctic sea ice extent and its recent decline; and excellent simulation of the El Niño‐Southern Oscillation spectrum and structure. Areas of concern include inadequate deep convection in the Nordic Seas; an inaccurate Antarctic sea ice simulation; precipitation and wind composites still affected by the equatorial cold tongue bias; muted variability in the Atlantic Meridional Overturning Circulation; strong 100 year quasi‐periodicity in Southern Ocean ventilation; and a lack of historical warming before 1990 and too rapid warming thereafter due to high climate sensitivity and strong aerosol forcing, in contrast to the observational record. Overall, CM4.0 scores very well in its fidelity against observations compared to the Coupled Model Intercomparison Project Phase 5 generation in terms of both mean state and modes of variability and should prove a valuable new addition for analysis across a broad array of applications.

The skill of monthly sea surface temperature (SST) anomaly predictions for large marine ecosystems (LMEs) in coastal regions of the United States and Canada is assessed using simulations from the climate models in the North American Multimodel Ensemble (NMME). The forecasts based on the full ensemble are generally more skillful than predictions from even the best single model. The improvement in skill is particularly noteworthy for probability forecasts that categorize SST anomalies into upper (warm) and lower (cold) terciles. The ensemble provides a better estimate of the full range of forecast values than any individual model, thereby correcting for the systematic over-confidence (under-dispersion) of predictions from an individual model. Probability forecasts, including tercile predictions from the NMME, are used frequently in seasonal forecasts for atmospheric variables and may have many uses in marine resource management.

The California Current System (CCS) is a biologically productive Eastern Boundary Upwelling System that experiences considerable environmental variability on seasonal and interannual timescales. Given that this variability drives changes in ecologically and economically important living marine resources, predictive skill for regional oceanographic conditions is highly desirable. Here, we assess the skill of seasonal sea surface temperature (SST) forecasts in the CCS using output from Global Climate Forecast Systems in the North American Multi-Model Ensemble (NMME), and describe mechanisms that underlie SST predictability. A simple persistence forecast provides considerable skill for lead times up to ~4 months, while skill above persistence is mostly confined to forecasts of late winter/spring and derives primarily from predictable evolution of ENSO-related variability. Specifically, anomalously weak (strong) equatorward winds are skillfully forecast during El Niño (La Niña) events, and drive negative (positive) upwelling anomalies and consequently warm (cold) temperature anomalies. This mechanism prevails during moderate to strong ENSO events, while years of ENSO-neutral conditions are not associated with significant forecast skill in the wind or significant skill above persistence in SST. We find also a strong latitudinal gradient in predictability within the CCS; SST forecast skill is highest off the Washington/Oregon coast and lowest off southern California, consistent with variable wind forcing being the dominant driver of SST predictability. These findings have direct implications for regional downscaling of seasonal forecasts and for short-term management of living marine resources.

Throughout 2014-2016, the California Current System (CCS) was characterized by large and persistent sea surface temperature anomalies (SSTa), which were accompanied by widespread ecological and socioeconomic consequences that have been documented extensively in the scientific literature and in the popular press. This marine heatwave and others have resulted in a heightened awareness of their potential impacts and prompted questions about if and when they may be predictable. Here, we use output from an ensemble of global climate forecast systems to document which aspects of the 2014-2016 CCS heatwave were predictable and how forecast skill, or lack thereof, relates to mechanisms driving the heatwave’s evolution. We focus on four prominent SSTa changes within the 2014-2016 period: (i) the initial onset of anomalous warming in early 2014, (ii) a second rapid SSTa increase in late 2014, (iii) a sharp reduction and subsequent return of warm SSTa in mid-2015, and (iv) another anomalous warming event in early 2016. Models exhibited clear forecast skill for the first and last of these fluctuations, but not the two in the middle. Taken together with the state of knowledge on the dominant forcing mechanisms of this heatwave, our results suggest that CCS SSTa forecast skill derives from predictable evolution of pre-existing SSTa to the west (as in early 2014) and the south (as in early 2016), while the inability of models to forecast wind-driven SSTa in late 2014 and mid-2015 is consistent with the lack of a moderate or strong El Niño or La Niña event preceding those periods. The multi-model mean forecast consistently outperformed a damped persistence forecast, especially during the period of largest SSTa, and skillful CCS forecasts were generally associated with accurate representation of large-scale dynamics. Additionally, a large forecast ensemble (85 members) indicated elevated probabilities for observed SSTa extremes even when ensemble mean forecasts exhibited limited skill. Our results suggest that different types or aspects of marine heat waves are more or less predictable depending on the forcing mechanisms at play, and events that are consistent with predictable ocean responses could inform ecosystem-based management of the ocean.

Nitrogen (N) pollution is shaped by multiple processes, the combined effects of which remain uncertain, particularly in the tropics. We use a global land biosphere model to analyze historical terrestrial-freshwater N budgets, considering the effects of anthropogenic N inputs, atmospheric CO2, land use, and climate. We estimate that globally, land currently sequesters 11 (10–13)% of annual N inputs. Some river basins, however, sequester >50% of their N inputs, buffering coastal waters against eutrophication and society against greenhouse gas-induced warming. Other basins, releasing >25% more than they receive, are mostly located in the tropics, where recent deforestation, agricultural intensification, and/or exports of land N storage can create large N pollution sources. The tropics produce 56 ± 6% of global land N pollution despite covering only 34% of global land area and receiving far lower amounts of fertilizers than the extratropics. Tropical land use should thus be thoroughly considered in managing global N pollution.

More than half of the world’s population now live in cities, which are known to be heat islands. While daytime urban heat islands (UHIs) are traditionally thought to be the consequence of less evaporative cooling in cities, recent work sparks new debate, showing that geographic variations of daytime UHI intensity were largely explained by variations in the efficiency with which urban and rural areas convect heat from the land surface to the lower atmosphere. Here, we reconcile this debate by demonstrating that the difference between the recent finding and the traditional paradigm can be explained by the difference in the attribution methods. Using a new attribution method, we find that spatial variations of daytime UHI intensity are more controlled by variations in the capacity of urban and rural areas to evaporate water, suggesting that strategies enhancing the evaporation capability such as green infrastructure are effective ways to mitigate urban heat.

The response of ozone (O3) dry deposition to ecosystem‐atmosphere interactions is poorly understood but is central to determining the potential for extreme pollution events under current and future climate conditions. Using observations and an interactive dry deposition scheme within two dynamic vegetation land models (GFDL LM3.0/LM4.0) driven by observation‐based meteorological forcings over 1948‐2014, we investigate the factors controlling seasonal and interannual variability (IAV) in O3 deposition velocities (Vd,O3). Stomatal activity in this scheme is determined mechanistically, depending on phenology, soil moisture, vapor pressure deficit, and CO2 concentration. Soil moisture plays a key role in modulating the observed and simulated Vd,O3 seasonal changes over evergreen forests in Mediterranean Europe, South Asia, and the Amazon. Analysis of multi‐year observations at forest sites in Europe and North America reveals drought stress to reduce Vd,O3 by ~50%. Both LM3.0 and LM4.0 capture the observed Vd,O3 decreases due to drought; however, IAV is weaker by a factor of two in LM3.0 coupled to atmospheric models, particularly in regions with large precipitation biases. IAV in summertime Vd,O3 to forests, driven primarily by the stomatal pathway, is largest (15‐35%) in semi‐arid regions of western Europe, eastern North America, and northeastern China. Monthly mean Vd,O3 for the highest year is two to four times that of the lowest, with significant implications for surface O3 variability and extreme events. Using Vd,O3 from LM4.0 in an atmospheric chemistry model improves the simulation of surface O3 abundance and spatial variability (reduces mean biases by ~10 ppb) relative to the widely‐used Wesely scheme.

Exchanges between coastal and oceanic waters shape both coastal ecosystem processes and signatures that they impart on global biogeochemical cycles. The time‐scales of these exchanges, however, are poorly represented in current‐generation, coarse‐grid climate models. Here we provide a novel global perspective on coastal residence time (CRT) and its spatio‐temporal variability using a new age tracer implemented in global ocean models. Simulated CRTs range widely from several days in narrow boundary currents to multiple years on broader shelves and in semi‐enclosed seas, in agreement with available observations. Overall, CRT is better characterized in high‐resolution models (1/8° and 1/4°) than the coarser (1° and 1/2°) versions. This is in large part because coastal and open ocean grid cells are more directly connected in coarse models, prone to erroneous coastal flushing and an underestimated CRT. Additionally, we find that geometric enclosure of a coastal system places an important constraint on CRT.

While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.

Ocean calcium carbonate (CaCO3) production and preservation play a key role in the global carbon cycle. Coastal and continental shelf (neritic) environments account for more than half of global CaCO3 accumulation. Previous neritic CaCO3 budgets have been limited in both spatial resolution and ability to project responses to environmental change. Here, a 1° spatially explicit budget for neritic CaCO3 accumulation is developed. Globally gridded satellite and benthic community area data are used to estimate community CaCO3 production. Accumulation rates (PgC yr−1) of four neritic environments are calculated: coral reefs/banks (0.084), seagrass-dominated embayments (0.043), and carbonate rich (0.037) and poor (0.0002) shelves. This analysis refines previous neritic CaCO3 accumulation estimates (~0.16) and shows almost all coastal carbonate accumulation occurs in the tropics, >50% of coral reef accumulation occurs in the Western Pacific Ocean, and 80% of coral reef, 63% of carbonate shelf, and 58% of bay accumulation occur within three global carbonate hot spots: the Western Pacific Ocean, Eastern Indian Ocean, and Caribbean Sea. These algorithms are amenable for incorporation into Earth System Models that represent open ocean pelagic CaCO3 production and deep-sea preservation and assess impacts and feedbacks of environmental change.

Climate variations have a profound impact on marine ecosystems and the communities that depend upon them. Anticipating ecosystem shifts using global Earth system models (ESMs) could enable communities to adapt to climate fluctuations and contribute to long-term ecosystem resilience. We show that newly developed ESM-based marine biogeochemical predictions can skillfully predict satellite-derived seasonal to multiannual chlorophyll fluctuations in many regions. Prediction skill arises primarily from successfully simulating the chlorophyll response to the El Niño–Southern Oscillation and capturing the winter reemergence of subsurface nutrient anomalies in the extratropics, which subsequently affect spring and summer chlorophyll concentrations. Further investigations suggest that interannual fish-catch variations in selected large marine ecosystems can be anticipated from predicted chlorophyll and sea surface temperature anomalies. This result, together with high predictability for other marine-resource–relevant biogeochemical properties (e.g., oxygen, primary production), suggests a role for ESM-based marine biogeochemical predictions in dynamic marine resource management efforts.

Large-scale spatial heterogeneity in fisheries production is predominantly controlled by the availability of zooplankton and benthic organisms, which have a complex relationship with primary production. To investigate how cross-ecosystem differences in these drivers determine fish assemblages and productivity, we constructed a spatially explicit mechanistic model of three fish functional types: forage, large pelagic, and demersal fishes. The model is based on allometric scaling principles, includes basic life cycle transitions, and has trophic interactions between the fishes and with their pelagic and benthic food resources. The model was applied to the global ocean, with plankton food web estimates and ocean conditions from a high-resolution earth system model. Further, a simple representation of fishing was included, and led to moderate matches with total, large pelagic, and demersal catches, including re-creation of observed variations in fish catch spanning two orders of magnitude. Our results highlight several ecologically meaningful model sensitivities. First, coexistence between forage and large pelagic fish in productive regions occurred when forage fish survival is promoted via both favorable metabolic allometry and enhanced predator avoidance in adult forage fish. Second, the prominence of demersal fish is highly sensitive to the efficiency of energy transfer to benthic invertebrates. Third, the latitudinal distribution of the total catch is modulated by the temperature dependence of metabolic rates, with increased sensitivity pushing fish biomass toward the poles. Fourth, forage fish biomass is suppressed by strong top-down controls on temperate and subpolar shelves, where mixed assemblages of large pelagic and demersal fishes exerted high predation rates. Last, spatial differences in the dominance of large pelagics vs. demersals is strongly related to the ratio of pelagic zooplankton production to benthic production. We discuss the potential linkages between model misfits and unresolved processes including movement, spawning phenology, seabird and marine mammal predators, and socioeconomically driven fishing pressure, which are identified as priorities for future model development. Ultimately, the model and analyses herein are intended as a baseline for a robust, mechanistic tool to understand, quantify, and predict global fish biomass and yield, now and in a future dominated by climate change and improved fishing technology.

The ocean is the main source of thermal inertia in the climate system. Ocean heat uptake during recent decades has been quantified using ocean temperature measurements. However, these estimates all use the same imperfect ocean dataset and share additional uncertainty due to sparse coverage, especially before 2007. Here, we provide an independent estimate by using measurements of atmospheric oxygen (O2) and carbon dioxide (CO2) – levels of which increase as the ocean warms and releases gases – as a whole ocean thermometer. We show that the ocean gained 1.29 ± 0.79 × 1022 Joules of heat per year between 1991 and 2016, equivalent to a planetary energy imbalance of 0.80 ± 0.49 W watts per square metre of Earth’s surface. We also find that the ocean-warming effect that led to the outgassing of O2 and CO2 can be isolated from the direct effects of anthropogenic emissions and CO2 sinks. Our result – which relies on high-precision O2 atmospheric measurements dating back to 1991 – leverages an integrative Earth system approach and provides much needed independent confirmation of heat uptake estimated from ocean data.

Subseasonal to seasonal forecasts have the potential to be a useful tool for managing estuarine fisheries and water quality, and with increasing skill at forecasting conditions at these time scales in the atmosphere and open ocean, skillful forecasts of estuarine salinity, temperature, and biogeochemistry may be possible. In this study, we use a machine learning model to assess the predictability of column minimum dissolved oxygen in Chesapeake Bay at a monthly time scale. Compared to previous models for dissolved oxygen and hypoxia, our model has the advantages of resolving spatial variability and fitting more flexible relationships between dissolved oxygen and the predictor variables. Using a concise set of predictors with established relationships with dissolved oxygen, we find that dissolved oxygen in a given month can be skillfully predicted with knowledge of stratification and mean temperature during the same month. Furthermore, the predictions generated by the model are consistent with expectations from prior knowledge and basic physics. The model reveals that accurate knowledge or skillful forecasts of the vertical density gradient is the key to successful prediction of dissolved oxygen, and prediction skill disappears if stratification is only known at the beginning of the forecast. The lost skill cannot be recovered by replacing stratification as a predictor with variables that have a lagged correlation with stratification (such as river discharge); however, skill is obtainable in many cases if stratification can be forecast with an error of less than about 1 kg m−3. Thus, future research on hypoxia forecasting should focus on understanding and forecasting variations in stratification over subseasonal time scales (between about two weeks and two months).

The attribution of anthropogenically forced trends in the climate system requires an understanding of when and how such signals emerge from natural variability. We applied time-of-emergence diagnostics to a large ensemble of an Earth system model, which provides both a conceptual framework for interpreting the detectability of anthropogenic impacts in the ocean carbon cycle and observational sampling strategies required to achieve detection. We found emergence timescales that ranged from less than a decade to more than a century, a consequence of the time lag between the chemical and radiative impacts of rising atmospheric CO2 on the ocean. Processes sensitive to carbonate chemical changes emerge rapidly, such as the impacts of acidification on the calcium carbonate pump (10 years for the globally integrated signal and 9–18 years for regionally integrated signals) and the invasion flux of anthropogenic CO2 into the ocean (14 years globally and 13–26 years regionally). Processes sensitive to the ocean’s physical state, such as the soft-tissue pump, which depends on nutrients supplied through circulation, emerge decades later (23 years globally and 27–85 years regionally).

Net primary production (NPP) by microscopic phytoplankton underpins nearly all marine life, yet global NPP estimates differ substantially. Among satellite-based estimates, variation has been attributed to differing assumptions about the relationships between photosynthesis and sea surface temperature (SST). Maximum chlorophyll (Chl)–specific rates of carbon fixation in the water column (PB opt) increase monotonically with SST in some satellite algorithms, whereas others peak at intermediate values. Understanding and constraining such relationships is challenged by the many direct and indirect relationships between temperature and phytoplankton. In this article, the emergent PB opt-SST relationship was diagnosed in a global biogeochemical simulation and compared with widely used satellite NPP algorithms. The simulated PB opt-SST relationship for the aggregated phytoplankton community was highly significant (r 2= 0.83) and increased monotonically with temperature. The PB opt-SST relationships for small and large phytoplankton, however, were distinct and weaker than the aggregate relationship (r 2 = 0.52 and 0.36, respectively). For small phytoplankton, the inhibitory effect of nutrient limitation in warmer, more stratified waters was moderated by efficient nutrient scavenging. This, combined with photoacclimation and the stimulatory effect of warming on maximum growth produced steep PB opt increases with SST. For large phytoplankton, the need for higher Chl:C in productive regions (because of package effects) and the onset of severe nutrient limitation in warm, stratified regions decreased PB opt relative to small phytoplankton, though PB opt still increased modestly with SST. The PB opt-SST relationships for both small and large phytoplankton overestimated PB opt in nutrient-poor regions and underestimated it in nutrient-rich regions. This bias was greatly reduced in the aggregate relationship because the increased prominence of low-PB opt large phytoplankton in nutrient-rich environments tempered PB opt increases. Results support a strong, monotonically increasing PB opt-SST relationship but emphasize the role of the size structure of the phytoplankton community in shaping the emergent relationship. The implications of these results are discussed in relation to efforts to improve satellite NPP algorithms and partition NPP by phytoplankton size.

Variations in weather and climate create and interact with ocean fluctuations occurring over days to decades. In some cases these fluctuations are local. In others they stretch across ocean basins. Marine organisms respond to environmental changes in diverse and sometimes dramatic ways. Over the past century natural ocean fluctuations have been augmented by a variety of anthropogenic drivers. The ocean has absorbed vast amounts of carbon dioxide, excess heat arising from the accumulation of greenhouse gases, nutrients from fertilizers, and other pollutants. While this has moderated climate change and pollution impacts on terrestrial systems, it has had diverse consequences for the ocean. This chapter provides a brief overview of ocean changes of particular relevance for marine life, including ocean acidification, warming, melting ice, shifting ocean productivity baselines, deoxygenation, coastal development, and pollution. We highlight contributions from the Nereus Program, and attempt to provide a broad context for the more detailed discussion of select topics in other chapters in this section. Anthropogenic ocean changes pose a considerable challenge to sustaining marine resources. Continued advances in understanding and predicting ocean changes, such as those described herein, are essential for meeting this challenge.

Accurate projections of the terrestrial carbon (C) sink are critical to understanding the future global C cycle and setting CO2 emission reduction goals. Current earth system models (ESMs) and dynamic global vegetation models (DGVMs) with coupled carbon‐nitrogen cycles project that future terrestrial C sequestration will be limited by nitrogen (N) availability, but the magnitude of N limitation remains a critical uncertainty. Plants use multiple symbiotic nutrient acquisition strategies to mitigate N limitation, but current DGVMs omit these mechanisms. Fully coupling N‐acquiring plant‐microbe symbioses to soil organic matter (SOM) cycling within a DGVM for the first time, we show that increases in N acquisition via SOM decomposition and atmospheric N2 fixation could support long‐term enhancement of terrestrial C sequestration at global scales under elevated CO2. The model reproduced elevated CO2 responses from two experiments (Duke and Oak Ridge) representing contrasting N acquisition strategies. N release from enhanced SOM decomposition supported vegetation growth at Duke, while inorganic N depletion limited growth at Oak Ridge. Global simulations reproduced spatial patterns of N‐acquiring symbioses from a novel niche‐based map of mycorrhizal fungi. Under a 100 ppm increase in CO2 concentrations, shifts in N acquisition pathways facilitated 200 Pg C of terrestrial C sequestration over 100 years compared to 50 Pg C for a scenario with static N acquisition pathways. Our results suggest that N acquisition strategies are important determinants of terrestrial C sequestration potential under elevated CO2, and that nitrogen‐enabled DGVMs that omit symbiotic N acquisition may underestimate future terrestrial C uptake.

Results from a range of Earth System and climate models of various resolution run under high‐CO2 emission scenarios challenge the paradigm that seafloor CaCO3 dissolution will grow in extent and intensify as ocean acidification develops over the next century. Under the “business as usual”, RCP8.5 scenario, CaCO3 dissolution increases in some areas of the deep ocean, such as the eastern central Pacific Ocean, but is projected to decrease in the Northern Pacific and abyssal Atlantic Ocean by the year 2100. The flux of CaCO3 to the seafloor and bottom‐current speeds, both of which are expected to decrease globally through the 21st century, govern changes in benthic CaCO3 dissolution rates over 53 and 31% of the dissolving seafloor, respectively. Below the calcite compensation depth (CCD), a reduced CaCO3 flux to the CaCO3‐free seabed modulates the amount of CaCO3 material dissolved at the sediment‐water interface. Slower bottom‐water circulation leads to thicker diffusive boundary layers above the sediment bed and a consequent stronger transport barrier to CaCO3 dissolution. While all investigated models predict a weakening of bottom current speeds over most of the seafloor by the end of the 21st century, strong discrepancies exist in the magnitude of the predicted speeds. Overall, the poor performance of most models in reproducing modern bottom‐water velocities and CaCO3 rain rates coupled with the existence of large disparities in predicted bottom‐water chemistry across models, hampers our ability to robustly estimate the magnitude and temporal evolution of anthropogenic CaCO3 dissolution rates and the associated anthropogenic CO2 neutralization.

Seasonal to interannual predictions of ecosystem dynamics have the potential to improve the management of living marine resources. Prediction of oceanic net primary production (NPP), the foundation of marine food webs and the biological carbon pump, is particularly promising, with recent analysis suggesting that ecosystem feedback processes may lead to higher predictability of NPP at interannual scales than for physical variables like sea surface temperature (SST). Here, we assessed the potential predictability of oceanic NPP and SST across seasonal to interannual lead times using reduced dimension, linear dynamical spatio-temporal models (rDSTM). This approach combines empirical orthogonal function (EOF) analysis with vector autoregressive (VAR) modeling to simplify the analysis of spatio-temporal data. The rDSTMs were fitted to monthly NPP and SST anomalies derived from 20 years of remote sensing data (1997-2017), considering two alternative algorithms commonly used to estimate NPP (VGPM and Eppley-VGPM) and optimally analyzed SST fields (AVHRR OISST). The local decay of anomalies provided high predictability up to three months, and subsequent interactions with remote forcing significantly extended predictability beyond the initial anomaly decay. Indeed, interactions among spatial modes associated with the propagation of major climate modes, particularly the El Niño-Southern Oscillation (ENSO), extended the predictability horizon above one year in some regions. Patterns of enhanced NPP predictability matched the location of oligotrophic gyres and transition regions between ocean biomes, where fluctuations in biome boundaries generate large biogeochemical perturbations that leave lasting imprints on NPP. In these areas, the predictability horizon for NPP was longer than for SST, although SST was more predictable over large areas of the equatorial and northeast Pacific. Our results support the potential for extending seasonal to interannual physical climate predictions to predict ocean productivity.

Ocean surface winds determine energy, material and momentum fluxes through the air-sea interface. Accounting for wind variability in time and space is thus essential to reliably analyze and simulate ocean circulation and the dynamics of marine ecosystems. Here, we present an assessment of surface winds from three widely used atmospheric reanalysis products (NCEP/NCAR, ERA-Interim and JRA-55) and their corresponding ocean forcing data sets (CORE v2.1, DFS v5.2 and JRA55-do), which include corrections for use in ocean simulations. We compared wind patterns most relevant to ocean circulation (surface wind stress, its curl and estimates of induced vertical upwelling velocity) across global and regional scales, with added emphasis on the main Eastern Boundary Upwelling Ecosystems (EBUEs). All products provided consistent large-scale patterns in surface winds and wind stress, although agreement was reduced for indices involving the calculation of spatial derivatives, like wind stress curl and Ekman pumping. Fidelity with respect to a reference reanalysis based on blended satellite and buoy observations (CCMP v2.0) improved in more recent, higher resolution products like JRA-55 and ERA-Interim. Adjustments applied when deriving ocean forcing data sets from atmospheric reanalysis robustly improved wind speed and wind stress vectors, but degraded wind stress curl (and implied Ekman upwelling) in two of the three ocean forcing products considered (DFS v5.2 and CORE v2.1). At regional scales, we found significant inconsistencies in equatorial and polar regions, as well as in coastal areas. In EBUEs, upwelling favorable winds were weaker in atmospheric reanalysis products and ocean forcing data sets than estimates based on CCMP v2.0 and QuikSCAT. All reanalysis products featured lower amplitude seasonal cycles and contrasting patterns of low frequency variability within each EBUE, including the presence of sudden changes in mean upwelling only for some products. Taken together, our results highlight the importance of incorporating uncertainties in wind forcing into ocean simulation experiments and retrospective analysis, and of correcting reanalysis products for ocean forcing data sets. Despite the continued improvement in the quality of wind data sets, prevailing limitations in reanalysis models demonstrate the need to confirm global products against regional measurements whenever possible and improve correction strategies across multiple ocean-relevant wind properties.

The supply of nitrogen is a primary limiting factor for the productivity of the Northeast United States (NEUS) continental shelf. In this study, a 12‐year (1996‐2007) retrospective physical‐biogeochemical simulation over the Northwest Atlantic (NWA) was used to analyze the mean and seasonal NEUS shelf nitrogen budget, including the connections between shelf subregions: the Gulf of Maine/Georges Bank (GoM/GB) and the Mid‐Atlantic Bight (MAB). The model captures the primary mean and seasonal patterns of shelf circulation, nitrate, and plankton dynamics. Results confirm aspects of previous nitrogen budget analyses, including the dominance of offshore nitrogen influxes into the GoM/GB and the prominent role of riverine influxes and sedimentary denitrification in the MAB. However, detailed spatiotemporal analysis of nitrogen fluxes highlights the importance of dispersed inflows of shallow to intermediate depth waters (0‐75m), which can at times exceed the deep nitrogen influx emphasized in previous studies. A seasonal analysis shows a pronounced shift from the net import of nitrogen to the GoM/GB region during late fall and winter, to the net export of nitrogen from the region in the spring and early summer. The MAB, in contrast, consistently exports nitrogen to offshore waters. The prominence of the 0‐75m nitrogen supply has implications for the roles of Labrador Slope Water (LSW) and Atlantic Temperate Slope Water (ATSW) on the NEUS ecosystems, as ATSW has greater nitrate concentrations than LSW at depth, but often less at the surface. Results suggest the need for further study of shallow to intermediate depth inflows beyond those from the Scotian Shelf, particularly during the fall/winter of net nitrogen inflow.

Meltwater from the Antarctic Ice Sheet is projected to cause up to one metre of sea-level rise by 2100 under the highest greenhouse gas concentration trajectory (RCP8.5) considered by the Intergovernmental Panel on Climate Change (IPCC). However, the effects of meltwater from the ice sheets and ice shelves of Antarctica are not included in the widely used CMIP5 climate models, which introduces bias into IPCC climate projections. Here we assess a large ensemble simulation of the CMIP5 model ‘GFDL ESM2M’ that accounts for RCP8.5-projected Antarctic Ice Sheet meltwater. We find that, relative to the standard RCP8.5 scenario, accounting for meltwater delays the exceedance of the maximum global-mean atmospheric warming targets of 1.5 and 2 degrees Celsius by more than a decade, enhances drying of the Southern Hemisphere and reduces drying of the Northern Hemisphere, increases the formation of Antarctic sea ice (consistent with recent observations of increasing Antarctic sea-ice area) and warms the subsurface ocean around the Antarctic coast. Moreover, the meltwater-induced subsurface ocean warming could lead to further ice-sheet and ice-shelf melting through a positive feedback mechanism, highlighting the importance of including meltwater effects in simulations of future climate.

The continual growth in the availability, detail, and wealth of environmental data provides an invaluable asset to improve the characterization of land heterogeneity in Earth System models – a persistent challenge in macroscale models. However, due to the nature of these data (volume and complexity) and the computational constraints of macroscale models, until now these data have been underutilized for global applications. As a proof of concept, this study explores over a 1/4 degree (~ 25 km) grid cell in southeastern California how to effectively and efficiently harness these data in Earth System models. First, a novel hierarchical multivariate clustering approach (HMC) is used to summarize the high dimensional environmental data space into hydrologically interconnected representative clusters (i.e., tiles). These tiles and their associated properties are then used to parameterize the sub-grid heterogeneity of the Geophysical Fluid Dynamics Laboratory (GFDL) LM4-HB land model. To assess how this data-driven approach to assemble the model tiles impacts the simulated water, energy, and carbon cycles, model experiments are run using a series of different tile configurations assembled by HMC. The results over the 1/4 degree macroscale grid cell and the underlying 30-meter fine-scale grid in southeastern California show that: 1) the observed similarity over the landscape makes it possible to robustly account for the role of multi-scale heterogeneity in the macroscale states and fluxes with around 300 sub-grid land model tiles; 2) assembling the sub-grid tiles from observed data, at times, leads to noticeable differences in the macroscale water, energy, and carbon cycles; for example, explicit subsurface interactions between the tiles leads to a dampening of macroscale extremes; 3) connecting the fine-scale grid to the model tiles via HMC enables circumventing the classic scale discrepancies between the macroscale and field-scale estimates; this has potentially significant implications for the evaluation and application of Earth System models.

Global observations show that the ocean lost approximately 2% of its oxygen inventory over the past five decades1,2,3, with important implications for marine ecosystems4,5. The rate of change varies regionally, with northwest Atlantic coastal waters showing a long-term drop6,7 that vastly outpaces the global and North Atlantic basin mean deoxygenation rates5,8. However, past work has been unable to differentiate the role of large-scale climate forcing from that of local processes. Here, we use hydrographic evidence to show that a Labrador Current retreat is playing a key role in the deoxygenation on the northwest Atlantic shelf. A high-resolution global coupled climate–biogeochemistry model9 reproduces the observed decline of saturation oxygen concentrations in the region, driven by a retreat of the equatorward-flowing Labrador Current and an associated shift towards more oxygen-poor subtropical waters on the shelf. The dynamical changes underlying the shift in shelf water properties are correlated with a slowdown in the simulated Atlantic Meridional Overturning Circulation (AMOC)10. Our results provide strong evidence that a major, centennial-scale change of the Labrador Current is underway, and highlight the potential for ocean dynamics to impact coastal deoxygenation over the coming century.

https://carbon2018.globalchange.gov/

Subsurface coherent eddies are well-known features of ocean circulation, but the sparsity of observations prevents an assessment of their importance for biogeochemistry. Here, we use a global eddying (0.1° ) ocean-biogeochemical model to carry out a census of subsurface coherent eddies originating from eastern boundary upwelling systems (EBUS), and quantify their biogeochemical effects as they propagate westward into the subtropical gyres. While most eddies exist for a few months, moving over distances of 100s of km, a small fraction (< 5%) of long-lived eddies propagates over distances greater than 1000km, carrying the oxygen-poor and nutrient-rich signature of EBUS into the gyre interiors. In the Pacific, transport by subsurface coherent eddies accounts for roughly 10% of the offshore transport of oxygen and nutrients in pycnocline waters. This "leakage" of subsurface waters can be a significant fraction of the transport by nutrient-rich poleward undercurrents, and may contribute to the well-known reduction of productivity by eddies in EBUS. Furthermore, at the density layer of their cores, eddies decrease climatological oxygen locally by close to 10%, thereby expanding oxygen minimum zones. Finally, eddies represent low-oxygen extreme events in otherwise oxygenated waters, increasing the area of hypoxic waters by several percent and producing dramatic short-term changes that may play an important ecological role. Capturing these non-local effects in global climate models, which typically include non-eddying oceans, would require dedicated parameterizations.

To gain understanding and predict how jellyfish populations will respond to anthropogenic changes, we first need to understand the factors that influence the distribution and abundance of current and historical populations. Hence, we have developed the first bioenergetic-based population model for the ubiquitous jellyfish Aurelia spp. that incorporates both benthic and pelagic life history stages. This model tracks cohorts of both life stages with temperature- and/or consumption-driven relationships for growth, reproduction and mortality. We present herein an initial model application to test hypotheses for the environmental factors that control the onset of strobilation and inter-annual variability in bloom timing and magnitude in Gulf of Mexico jellyfish populations between 1982 and 2007. To recreate the autumnal blooms of Aurelia spp. in the Gulf of Mexico, strobilation must commence while zooplankton biomass is increasing after the annual minimum. Under this scenario, the model simulated seasonal and inter-annual variability of Aurelia spp. biomass that corresponded well with observations. Markedly larger blooms in anomalously warm, high zooplankton autumns resulted from enhanced ephyrae production compounded by enhanced medusa growth under these conditions. This model confirms the importance of the polyp-to-ephyrae transition in regulating jellyfish bloom magnitude and provides a mechanistic model framework which can examine how future jellyfish populations might respond to climate change.

https://carbon2018.globalchange.gov/

Mountain snowpack in the western United States provides a natural reservoir for cold season precipitation; variations in snowpack influence warm season water supply, wildfire risk, ecology, and industries like agriculture dependent on snow and downstream water availability. Efforts to understand snowpack variability have predominantly been focused on either weekly (weather) or decadal to centennial (climate variability and change) timescales. We focus on a timescale between these ranges by demonstrating that a global climate model suite can provide snowpack predictions 8 months in advance. The predictions from climate models outperform statistical methods from observations alone. Our results show that seasonal hydroclimate predictions are possible and highlight areas for future prediction system improvements.

Oceanic heat uptake (OHU) is a significant source of uncertainty in both the transient and equilibrium responses to increasing the planetary radiative forcing. OHU differs among climate models and is related in part to their representation of vertical and lateral mixing. This study examines the role of ocean model formulation – specifically the choice of vertical coordinate and strength of background diapycnal diffusivity (Kd) – in the millennial-scale near-equilibrium climate response to a quadrupling of atmospheric CO2. Using two fully-coupled Earth System Models (ESMs) with nearly identical atmosphere, land, sea ice, and biogeochemical components, it is possible to independently configure their ocean model components with different formulations and produce similar near-equilibrium climate responses. The SST responses are similar between the two models (r2 = 0.75, global average ∼ 4.3 °C) despite their initial pre-industrial climate mean states differing by 0.4 °C globally. The surface and interior responses of temperature and salinity are also similar between the two models. However, the Atlantic Meridional Overturning Circulation (AMOC) responses are different between the two models, and the associated differences in ventilation and deep water formation have an impact on the accumulation of dissolved inorganic carbon in the ocean interior. A parameter sensitivity analysis demonstrates that increasing the amount of Kd produces very different near-equilibrium climate responses within a given model. These results suggest that the impact of the ocean vertical coordinate on the climate response is small relative to the representation of sub-gridscale mixing.

Icebergs and glacial meltwater have been observed to significantly affect chlorophyll concentrations, primary production and particle export locally, yet the quantitative influence of glacial iron on the carbon cycle of the Southern Ocean remains unknown. We analyse the impact of icebergs and glacial meltwater on the Southern Ocean carbon cycle in a global Earth System Model. We consider several simulations spanning low and high bounds of current estimates of glacial iron concentration. We find that a high glacial iron input produces the best agreement with observed iron and chlorophyll distributions. These high glacial iron input results indicate that about 30% of the Southern Ocean particle export production, i.e., the flux of particulate organic matter through the 100 m depth level, is driven by glacial iron sources. This export production is associated with an uptake of 0.14 Pg carbon per year, which reduces carbon outgassing in the Southern Ocean by 30%.

The spread of coastal hypoxia is a pressing global problem, largely caused by substantial nitrogen (N) exports from river basins to the coastal ocean. Most previous process‐based modeling studies for investigating basin management strategies to reduce river N exports focused on the impacts of different farming practices or land use, used watershed models that simplified many mechanisms that critically affect the state of N storage in land, were limited mainly to fairly small basins, and did not span multiple climate regimes. Here we use a process‐based land‐river model to simulate historical (1999–2010) river flows and nitrate‐N exports throughout the entire drainage network of South Korea (100,210 km2), which encompasses varying climate, land use, and hydrogeological characteristics. Based on projections by using multiple scenarios of N input reductions and climates, we explore the impacts of various ecosystem factors (i.e., N storage in basins, climate and its variability, anthropogenic N inputs, and basin location) on river nitrate‐N exports. Our findings have fundamental implications for reducing coastal hypoxia: (1) a small reduction of N inputs in basins, including intensively utilized human land use, can have a greater improvement on water quality; (2) heightening climate variability may not increase long‐term mean river N exports yet can significantly mask N input reduction effects by producing N export extremes associated with recurring coastal hypoxia; and (3) N exports to the coastal ocean can be most efficiently reduced by decreasing N inputs in subbasins, which are receiving high anthropogenic N inputs and are close to the coast.

Estuaries are productive and ecologically important ecosystems, incorporating environmental drivers from watersheds, rivers, and the coastal ocean. Climate change has potential to modify the physical properties of estuaries, with impacts on resident organisms. However, projections from general circulation models (GCMs) are generally too coarse to resolve important estuarine processes. Here, we statistically downscaled near-surface air temperature and precipitation projections to the scale of the Chesapeake Bay watershed and estuary. These variables were linked to Susquehanna River streamflow using a water balance model and finally to spatially resolved Chesapeake Bay surface temperature and salinity using statistical model trees. The low computational cost of this approach allowed rapid assessment of projected changes from four GCMs spanning a range of potential futures under a high CO2 emission scenario, for four different downscaling methods. Choice of GCM contributed strongly to the spread in projections, but choice of downscaling method was also influential in the warmest models. Models projected a ~2–5.5 °C increase in surface water temperatures in the Chesapeake Bay by the end of the century. Projections of salinity were more uncertain and spatially complex. Models showing increases in winter-spring streamflow generated freshening in the Upper Bay and tributaries, while models with decreased streamflow produced salinity increases. Changes to the Chesapeake Bay environment have implications for fish and invertebrate habitats, as well as migration, spawning phenology, recruitment, and occurrence of pathogens. Our results underline a potentially expanded role of statistical downscaling to complement dynamical approaches in assessing climate change impacts in dynamically challenging estuaries.

The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.

The Paris Agreement has initiated a scientific debate on the role that carbon removal – or net negative emissions – might play in achieving less than 1.5 K of global mean surface warming by 2100. Here, we probe the sensitivity of a comprehensive Earth system model (GFDL-ESM2M) to three different atmospheric CO2 concentration pathways, two of which arrive at 1.5 K of warming in 2100 by very different pathways. We run five ensemble members of each of these simulations: (1) a standard Representative Concentration Pathway (RCP4.5) scenario, which produces 2 K of surface warming by 2100 in our model; (2) a stabilization pathway in which atmospheric CO2 concentration never exceeds 440 ppm and the global mean temperature rise is approximately 1.5 K by 2100; and (3) an overshoot pathway that passes through 2 K of warming at mid-century, before ramping down atmospheric CO2 concentrations, as if using carbon removal, to end at 1.5 K of warming at 2100. Although the global mean surface temperature change in response to the overshoot pathway is similar to the stabilization pathway in 2100, this similarity belies several important differences in other climate metrics, such as warming over land masses, the strength of the Atlantic Meridional Overturning Circulation (AMOC), ocean acidification, sea ice coverage, and the global mean sea level change and its regional expressions. In 2100, the overshoot ensemble shows a greater global steric sea level rise and weaker AMOC mass transport than in the stabilization scenario, with both of these metrics close to the ensemble mean of RCP4.5. There is strong ocean surface cooling in the North Atlantic Ocean and Southern Ocean in response to overshoot forcing due to perturbations in the ocean circulation. Thus, overshoot forcing in this model reduces the rate of sea ice loss in the Labrador, Nordic, Ross, and Weddell seas relative to the stabilized pathway, suggesting a negative radiative feedback in response to the early rapid warming. Finally, the ocean perturbation in response to warming leads to strong pathway dependence of sea level rise in northern North American cities, with overshoot forcing producing up to 10 cm of additional sea level rise by 2100 relative to stabilization forcing.

Ocean chlorophyll concentration, a proxy for phytoplankton, is strongly influenced by internal ocean dynamics such as those associated with El Niño–Southern Oscillation (ENSO). Observations show that ocean chlorophyll responses to ENSO generally lead sea surface temperature (SST) responses in the equatorial Pacific. A long-term global earth system model simulation incorporating marine biogeochemical processes also exhibits a preceding chlorophyll response. In contrast to simulated SST anomalies which significantly lag the wind-driven subsurface heat response to ENSO, chlorophyll anomalies respond rapidly. Iron was found to be the key factor connecting the simulated surface chlorophyll anomalies to the subsurface ocean response. Westerly wind bursts decrease central Pacific chlorophyll by reducing iron supply through wind-driven thermocline deepening, but increase western Pacific chlorophyll by enhancing the influx of coastal iron from the maritime continent. Our results mechanistically support the potential for chlorophyll-based indices to inform seasonal ENSO forecasts beyond previously identified SST-based indices.

Reliable estimates of historical and current biogeochemistry are essential for understanding past ecosystem variability and predicting future changes. Efforts to translate improved physical ocean state estimates into improved biogeochemical estimates, however, are hindered by high biogeochemical sensitivity to transient momentum imbalances that arise during physical data assimilation. Most notably, the breakdown of geostrophic constraints on data assimilation in equatorial regions can lead to spurious upwelling, resulting in excessive equatorial productivity and biogeochemical fluxes. This hampers efforts to understand and predict the biogeochemical consequences of El Niño and La Niña. We develop a strategy to robustly integrate an ocean biogeochemical model with an ensemble coupled-climate data assimilation system used for seasonal to decadal global climate prediction. Addressing spurious vertical velocities requires two steps. First, we find that tightening constraints on atmospheric data assimilation maintains a better equatorial wind stress and pressure gradient balance. This reduces spurious vertical velocities, but those remaining still produce substantial biogeochemical biases. The remainder is addressed by imposing stricter fidelity to model dynamics over data constraints near the equator. We determine an optimal choice of model-data weights that removed spurious biogeochemical signals while benefitting from off-equatorial constraints that still substantially improve equatorial physical ocean simulations. Compared to the unconstrained control run, the optimally constrained model reduces equatorial biogeochemical biases and markedly improves the equatorial subsurface nitrate concentrations and hypoxic area. The pragmatic approach described herein offers a means of advancing earth system prediction in parallel with continued data assimilation advances aimed at fully considering equatorial data constraints.

Reactive nitrogen (N) emissions have increased over the last 150 years as a result of greater fossil fuel combustion and food production. The resulting increase in N deposition can alter the function of ecosystems, but characterizing its ecological impacts remains challenging, in part because of uncertainties in model-based estimates of N dry deposition. Here, we leverage the tiled structure of the land component (LM3) of the Geophysical Fluid Dynamics Laboratory (GFDL) Earth System Model to represent the impact of physical, hydrological, and ecological heterogeneities on the surface removal of chemical tracers. We show that this framework can be used to estimate N deposition at more ecologically-relevant scales (e.g., natural vegetation, water bodies) than from the coarse-resolution global chemistry–climate model (GFDL-AM3). Focusing on North America, we show that the faster removal of N over forested ecosystems relative to cropland and pasture implies that coarse resolution estimates of N deposition from global models systematically underestimate N deposition to natural vegetation by 10 to 30% in the Central and Eastern US. Neglecting the subgrid scale heterogeneity of dry deposition velocities also results in an underestimate (overestimate) of the amount of reduced (oxidized) nitrogen deposited to water bodies. Overall, changes in land cover associated with human activities are found to slow down the removal of N from the atmosphere, causing a reduction in the dry oxidized, dry reduced, and total N deposition over the contiguous US of 8%, 26%, and 6%, respectively. We also find that the reduction in the overall rate of removal of N associated with land-use change tends to increase N deposition on the remaining natural vegetation and facilitate N export to Canada. We show that subgrid scale differences in the surface removal of oxidized and reduced nitrogen imply that near-term (2010–2050) changes in oxidized (−47%) and reduced (+40%) US N emissions will cause opposite changes in N deposition to water bodies (increase) and natural vegetation (decrease) in the Eastern US, with potential implications for acidification and ecosystems.

This study describes and evaluates the Fire Including Natural & Agricultural Lands model (FINAL) which, for the first time, explicitly simulates cropland and pasture management fires separately from non-agricultural fires. The non-agricultural fire module uses empirical relationships to simulate burned area in a quasi-mechanistic framework, similar to past fire modeling efforts, but with a novel optimization method that improves the fidelity of simulated fire patterns to new observational estimates of non-agricultural burning. The agricultural fire components are forced with estimates of cropland and pasture fire seasonality and frequency derived from observational land-cover and satellite fire datasets. FINAL accurately simulates the amount, distribution, and seasonal timing of burned cropland and pasture over 2001–2009 (global totals: 0.434 × 106 and 2.02 × 106 km2 yr−1 modeled, 0.454 × 106 and 2.04 × 106 km2 yr−1 observed), but carbon emissions for cropland and pasture fire are overestimated (global totals: 0.297 PgC yr−1 and 0.712 PgC yr−1 modeled, 0.194 PgC yr−1 and 0.538 PgC yr−1 observed). The non-agricultural fire module underestimates global burned area (1.66 × 106 km2 yr−1 modeled, 2.44 × 106 km2 yr−1 observed) and carbon emissions (1.33 PgC yr−1 modeled, 1.84 PgC yr−1 observed). The spatial pattern of total burned area and carbon emissions is generally well reproduced across much of sub-Saharan Africa, Brazil, central Asia, and Australia, whereas the boreal zone suffers from underestimates. FINAL represents an important step in the development of global fire models, and offers a strategy for fire models to consider human-driven fire regimes on cultivated lands. At the regional scale, simulations would benefit from refinements in the parameterizations and improved optimization datasets.

The ocean is the main source of thermal inertia in the climate system1. During recent decades, ocean heat uptake has been quantified by using hydrographic temperature measurements and data from the Argo float program, which expanded its coverage after 20072,3. However, these estimates all use the same imperfect ocean dataset and share additional uncertainties resulting from sparse coverage, especially before 20074,5. Here we provide an independent estimate by using measurements of atmospheric oxygen (O2) and carbon dioxide (CO2)—levels of which increase as the ocean warms and releases gases—as a whole-ocean thermometer. We show that the ocean gained 1.33 ± 0.20 × 1022 joules of heat per year between 1991 and 2016, equivalent to a planetary energy imbalance of 0.83 ± 0.11 watts per square metre of Earth’s surface. We also find that the ocean-warming effect that led to the outgassing of O2 and CO2 can be isolated from the direct effects of anthropogenic emissions and CO2 sinks. Our result—which relies on high-precision O2 measurements dating back to 19916—suggests that ocean warming is at the high end of previous estimates, with implications for policy-relevant measurements of the Earth response to climate change, such as climate sensitivity to greenhouse gases7 and the thermal component of sea-level rise.

To explore the mechanisms involved in the global ocean circulation response to the shoaling and closure of the Central American Seaway (CAS), we performed a suite of sensitivity experiments using the Geophysical Fluid Dynamics Laboratory Earth System Model (ESM), GFDL‐ESM 2G, varying only the seaway widths and sill depths. Changes in large‐scale transport, global ocean mean state, and deep‐ocean circulation in all simulations are driven by the direct impacts of the seaway on global mass, heat and salt transports. Net mass transport through the seaway into the Caribbean is 20.5‐23.1 Sv with a deep CAS, but only 14.1 Sv for the wide, shallow CAS. Seaway transport originates from the Antarctic Circumpolar Current in the Pacific and rejoins it in the South Atlantic, reducing the Indonesian Throughflow and transporting heat and salt southward into the South Atlantic, in contrast to present‐day and previous CAS simulations. The increased southward salt transport increases the large‐scale upper ocean density, and the freshening and warming from the changing ocean transports decreases the intermediate and deep‐water density. The new ocean circulation pathway traps heat in the Southern Hemisphere oceans and reduces the northern extent of Antarctic Bottom Water penetration in the Atlantic, strengthening and deepening Atlantic meridional overturning, in contrast to previous studies. In all simulations, the seaway has a profound effect on the global ocean mean state and alters deep‐water mass properties and circulation in the Atlantic, Indian and Pacific basins, with implications for changing deep‐water circulation as a possible driver for changes in long‐term climate.

Model intercomparison studies in the climate and Earth sciences communities have been crucial to building credibility and coherence for future projections. They have quantified variability among models, spurred model development, contrasted within- and among-model uncertainty, assessed model fits to historical data, and provided ensemble projections of future change under specified scenarios. Given the speed and magnitude of anthropogenic change in the marine environment and the consequent effects on food security, biodiversity, marine industries, and society, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. Here, we describe the Fisheries and Marine Ecosystem Model Intercomparison Project protocol version 1.0 (Fish-MIP v1.0), part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is a cross-sectoral network of climate impact modellers. Given the complexity of the marine ecosystem, this class of models has substantial heterogeneity of purpose, scope, theoretical underpinning, processes considered, parameterizations, resolution (grain size), and spatial extent. This heterogeneity reflects the lack of a unified understanding of the marine ecosystem and implies that the assemblage of all models is more likely to include a greater number of relevant processes than any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) Coupled Model Intercomparison Project Phase 5 (CMIP5) outputs under prescribed scenarios for historic (from the 1950s) and future (to 2100) time periods; it will be adapted to CMIP phase 6 (CMIP6) in future iterations. It also describes a standardized set of outputs for each participating Fish-MIP model to produce. This enables the broad characterization of differences between and uncertainties within models and projections when assessing climate and fisheries impacts on marine ecosystems and the services they provide. The systematic generation, collation, and comparison of results from Fish-MIP will inform an understanding of the range of plausible changes in marine ecosystems and improve our capacity to define and convey the strengths and weaknesses of model-based advice on future states of marine ecosystems and fisheries. Ultimately, Fish-MIP represents a step towards bringing together the marine ecosystem modelling community to produce consistent ensemble medium- and long-term projections of marine ecosystems.

We use a novel, high-resolution global climate model (GFDL-ESM2.6) to investigate the influence of warm and cold El Niño/Southern Oscillation (ENSO) events on the physics and biogeochemistry of the California Current System (CalCS). We focus on the effect of ENSO on variations in the O2 concentration and the pH of the coastal waters of the CalCS. An assessment of the CalCS response to six El Niño and seven La Niña events in ESM2.6 reveals significant variations in the response between events. However, these variations overlay a consistent physical and biogeochemical (O2 and pH) response in the composite mean. Focusing on the mean response, our results demonstrate that O2 and pH are affected rather differently in the euphotic zone above ~100 m. The strongest O2 response reaches up to several 100 km offshore, whereas the pH signal occurs only within a ~100 km-wide band along the coast. By splitting the changes in O2 and pH into individual physical and biogeochemical components that are affected by ENSO variability, we found that O2 variability in the surface ocean is primarily driven by changes in surface temperature that affect the O2 solubility. In contrast, surface pH changes are predominantly driven by changes in dissolved inorganic carbon (DIC), which in turn is affected by upwelling, explaining the confined nature of the pH signal close to the coast. Below ~100 m, we find conditions with anomalously low O2 and pH, and by extension also anomalously low aragonite saturation, during La Niña. This result is consistent with findings from previous studies and highlights the stress that the CalCS ecosystem could periodically undergo in addition to impacts due to climate change.

The measured concentration of chlorophyll a in the surface ocean spans four orders of magnitude, from ∼0.01 mg m-3 in the oligotrophic gyres to >10 mg m-3 in coastal zones. Productive regions encompass only a small fraction of the global ocean area yet they contribute disproportionately to marine resources and biogeochemical processes, such as fish catch and coastal hypoxia. These regions and/or the full observed range of chlorophyll concentration, however, are often poorly represented in global earth system models (ESMs) used to project climate change impacts on marine ecosystems. Furthermore, recent high resolution (∼10 km) global earth system simulations suggest that this shortfall is not solely due to coarse resolution (∼100 km) of most global ESMs. By integrating a global biogeochemical model that includes two phytoplankton size classes (typical of many ESMs) into a regional simulation of the California Current System (CCS) we test the hypothesis that a combination of higher spatial resolution and enhanced resolution of phytoplankton size classes and grazer linkages may enable global ESMs to better capture the full range of observed chlorophyll. The CCS is notable for encompassing both oligotrophic (<0.1 mg m-3) and productive (>10 mg m-3) endpoints of the global chlorophyll distribution. As was the case for global high-resolution simulations, the regional high-resolution implementation with two size classes fails to capture the productive endpoint. The addition of a third phytoplankton size class representing a chain-forming coastal diatom enables such models to capture the full range of chlorophyll concentration along a nutrient supply gradient, from highly productive coastal upwelling systems to oligotrophic gyres. Weaker ‘top-down’ control on coastal diatoms results in stronger trophic decoupling and increased phytoplankton biomass, following the introduction of new nutrients to the photic zone. The enhanced representation of near-shore chlorophyll maxima allows the model to better capture coastal hypoxia along the continental shelf of the North American west coast and may improve the representation of living marine resources.

Globally, fires are a major source of carbon from the terrestrial biosphere to the atmosphere, occurring on a seasonal cycle and with substantial interannual variability. To understand past trends and variability in sources and sinks of terrestrial carbon, we need quantitative estimates of global fire distributions. Here we introduce an updated version of the Fire Including Natural and Agricultural Lands model, version 2 (FINAL.2), modified to include multi-day burning and enhanced fire spread rate in forest crowns. We demonstrate that the improved model reproduces the interannual variability and spatial distribution of fire emissions reported in present day remotely sensed inventories. We use FINAL.2 to simulate historical (post-1700) fires and attribute past fire trends and variability to individual drivers: land use and land cover change, population growth, and lightning variability. Global fire emissions of carbon increase by about 10% between 1700 and 1900, reaching a maximum of 3.4 PgC yr-1 in the 1910s, followed by a decrease to about 5% below year 1700 levels by 2010. The decrease in emissions from the 1910s to the present day is driven mainly by land use change, with a smaller contribution from increased fire suppression due to increased human population, and is largest in Sub-Saharan Africa and South Asia. Interannual variability of global fire emissions is similar in the present day as in the early historical period, but present day wildfires would be more variable in the absence of land use change.

Horizontal transport at the boundaries of the subtropical gyres plays a crucial role in providing the nutrients that fuel gyre primary productivity, the heat that helps restratify the surface mixed layer, and the dissolved inorganic carbon (DIC) that influences air‐sea carbon exchange. Mesoscale eddies may be an important component of these horizontal transports; however, previous studies have not quantified the horizontal tracer transport due to eddies across the subtropical gyre boundaries. Here we assess the physical mechanisms that control the horizontal transport of mass, heat, nutrients and carbon across the North Pacific and North Atlantic subtropical gyre boundaries using the eddy‐rich ocean component of a climate model (GFDL's CM2.6) coupled to a simple biogeochemical model (mini‐BLING). Our results suggest that horizontal transport across the gyre boundaries supplies a substantial amount of mass and tracers to the ventilated layer of both Northern Hemisphere subtropical gyres, with the Kuroshio and Gulf Stream acting as main exchange gateways. Mass, heat, and DIC supply is principally driven by the time‐mean circulation, whereas nutrient transport differs markedly from the other tracers, as nutrients are mainly supplied to both subtropical gyres by down‐gradient eddy mixing across gyre boundaries. A budget analysis further reveals that the horizontal nutrient transport, combining the roles of both mean and eddy components, is responsible for more than three quarters of the total nutrient supply into the subtropical gyres, surpassing a recent estimate based on a coarse resolution model and thus further highlighting the importance of horizontal nutrient transport.

A 0.24°C jump of record warm global mean surface temperature (GMST) over the past three consecutive record-breaking years (2014-2016) was highly unusual and largely a consequence of an El Niño that released unusually large amounts of ocean heat from the subsurface layer of the northwestern tropical Pacific (NWP). This heat had built up since the 1990s mainly due to greenhouse-gas (GHG) forcing and possible remote oceanic effects. Model simulations and projections suggest that the fundamental cause, and robust predictor of large record-breaking events of GMST in the 21st century is GHG forcing rather than internal climate variability alone. Such events will increase in frequency, magnitude and duration, as well as impact, in the future unless GHG forcing is reduced.

The Gulf Stream (GS) region has intense mesoscale variability that can affect the supply of nutrients to the euphotic zone (Zeu). In this study, a recently developed high-resolution coupled physical-biological model is used to conduct a 25-year simulation in the Northwest Atlantic. The Reynolds decomposition method is applied to quantify the nitrate budget and shows that the mesoscale variability is important to the vertical nitrate supply over the GS region. The decomposition, however, cannot isolate eddy effects from those arising from other mesoscale phenomena. This limitation is addressed by analyzing a large sample of eddies detected and tracked from the 25-year simulation. The eddy composite structures indicate that positive nitrate anomalies within Zeu exist in both cyclonic eddies (CEs) and anticyclonic eddies (ACEs) over the GS region, and are even more pronounced in the ACEs. Our analysis further indicates that positive nitrate anomalies mostly originate from enhanced vertical advective flux rather than vertical turbulent diffusion. The eddy-wind interaction-induced Ekman pumping is very likely the mechanism driving the enhanced vertical motions and vertical nitrate transport within ACEs. This study suggests that the ACEs in GS region may play an important role in modulating the oceanic biogeochemical properties by fueling local biomass production through the persistent supply of nitrate.

In this two-part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part I, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode – with prescribed sea surface temperatures (SSTs) and sea ice distribution – is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top-of-atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part II, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.

In Part II of this two-part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part I. Part II provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.

he recent ‘warming hiatus’ presents an excellent opportunity to investigate climate sensitivity of carbon cycle processes. Here we combine satellite and atmospheric observations to show that the rate of net biome productivity (NBP) has significantly accelerated from −0.007 ± 0.065 PgC yr−2 over the warming period (1982 to 1998) to 0.119 ± 0.071 PgC yr−2 over the warming hiatus (1998–2012). This acceleration in NBP is not due to increased primary productivity, but rather reduced respiration that is correlated (r = 0.58; P = 0.0007) and sensitive (γ = 4.05 to 9.40 PgC yr−1 per °C) to land temperatures. Global land models do not fully capture this apparent reduced respiration over the warming hiatus; however, an empirical model including soil temperature and moisture observations better captures the reduced respiration.

Fisheries and aquaculture make a crucial contribution to global food security, nutrition and livelihoods. However, the UN Sustainable Development Goals separate marine and terrestrial food production sectors and ecosystems. To sustainably meet increasing global demands for fish, the interlinkages among goals within and across fisheries, aquaculture and agriculture sectors must be recognized and addressed along with their changing nature. Here, we assess and highlight development challenges for fisheries-dependent countries based on analyses of interactions and trade-offs between goals focusing on food, biodiversity and climate change. We demonstrate that some countries are likely to face double jeopardies in both fisheries and agriculture sectors under climate change. The strategies to mitigate these risks will be context-dependent, and will need to directly address the trade-offs among Sustainable Development Goals, such as halting biodiversity loss and reducing poverty. Countries with low adaptive capacity but increasing demand for food require greater support and capacity building to transition towards reconciling trade-offs. Necessary actions are context-dependent and include effective governance, improved management and conservation, maximizing societal and environmental benefits from trade, increased equitability of distribution and innovation in food production, including continued development of low input and low impact aquaculture.

The ozone (O3) dry depositional sink and its contribution to observed variability in tropospheric O3 are both poorly understood. Distinguishing O3 uptake through plant stomata versus other pathways is relevant for quantifying the O3 influence on carbon and water cycles. We use a decade of O3, carbon, and energy eddy covariance (EC) fluxes at Harvard Forest to investigate interannual variability (IAV) in O3 deposition velocities ( math formula). In each month, monthly mean math formula for the highest year is twice that for the lowest. Two independent stomatal conductance estimates, based on either water vapor EC or gross primary productivity, vary little from year to year relative to canopy conductance. We conclude that nonstomatal deposition controls the substantial observed IAV in summertime math formula during the 1990s over this deciduous forest. The absence of obvious relationships between meteorology and math formula implies a need for additional long-term, high-quality measurements and further investigation of nonstomatal mechanisms.

Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model’s near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2–3 years. In the tropics,long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model’s novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.

Climate change is expected to modify ecological responses in the ocean, with the potential for important effects on the ecosystem services provided to humankind. Here we address the question of how rapidly multiple drivers of marine ecosystem change develop in the future ocean. By analysing an ensemble of models we find that, within the next 15 years, the climate change-driven trends in multiple ecosystem drivers emerge from the background of natural variability in 55% of the ocean and propagate rapidly to encompass 86% of the ocean by 2050 under a ‘business-as-usual’ scenario. However, we also demonstrate that the exposure of marine ecosystems to climate change-induced stress can be drastically reduced via climate mitigation measures; with mitigation, the proportion of ocean susceptible to multiple drivers within the next 15 years is reduced to 34%. Mitigation slows the pace at which multiple drivers emerge, allowing an additional 20 years for adaptation in marine ecological and socio-economic systems alike.

Annual nitrate cycles have been measured throughout the pelagic waters of the Southern Ocean, including regions with seasonal ice cover and southern hemisphere subtropical zones. Vertically resolved nitrate measurements were made using in situ ultraviolet spectrophotometer (ISUS) and submersible ultraviolet nitrate analyzer (SUNA) optical nitrate sensors deployed on profiling floats. Thirty-one floats returned forty complete annual cycles. The mean nitrate profile from the month with the highest winter nitrate minus the mean profile from the month with the lowest nitrate yields the annual nitrate drawdown. This quantity was integrated to 200 m depth and converted to carbon using the Redfield Ratio to estimate Annual Net Community Production (ANCP) throughout the Southern Ocean south of 30° S. A well-defined, zonal mean distribution is found with highest values (3 to 4 mol C m−2 y−1) from 40 to 50° S. Lowest values are found in the subtropics and in the seasonal ice zone. The area weighted mean was 2.9 mol C m−2 y−1 for all regions south of 40° S. Cumulative ANCP south of 50° S is 1.3 Pg C y−1. This represents about 13% of global ANCP in about 14% of the global ocean area.

Accurate representation of the remineralization of sinking organic matter is crucial for reliable projections of the marine carbon cycle. Both water temperature and oxygen concentration are thought to influence remineralization rates, but limited data constraints have caused disagreement concerning the degree of these influences. We analyse a compilation of POC flux measurements from 19 globally distributed sites. Our results indicate that the attenuation of the flux of particulate organic matter depends on temperature with a Q10 between 1.5 and 2.01, and on oxygen described by a half saturation constant between 4 and 12 μmol/L. We assess the impact of the temperature and oxygen dependence in the biogeochemistry model COBALT, coupled to GFDL's Earth System Model ESM2M. The new remineralization parameterization results in shallower remineralization in the low latitudes but deeper remineralization in the high latitudes, redistributing POC flux towards the poles. It also decreases the volume of the oxygen minimum zones, partly addressing a long-standing bias in global climate models. Extrapolating temperature-dependent remineralization rates to the surface (i.e., beyond the depth range of POC flux data) resulted in rapid recycling and excessive surface nutrients. Surface nutrients could be ameliorated by reducing near surface rates in a manner consistent with bacterial colonization, suggesting the need for improved remineralization constraints within the euphotic zone. The temperature and oxygen dependence cause an additional 10% decrease in global POC flux at 500m depth, but no significant change in global POC flux at 2000m under the RCP8.5 future projection.

Climate change is likely to profoundly modulate the burden of infectious diseases. However, attributing health impacts to a changing climate requires being able to associate changes in infectious disease incidence with the potentially complex influences of climate. This aim is further complicated by nonlinear feedbacks inherent in the dynamics of many infections, driven by the processes of immunity and transmission. Here, we detail the mechanisms by which climate drivers can shape infectious disease incidence, from direct effects on vector life history to indirect effects on human susceptibility, and detail the scope of variation available with which to probe these mechanisms. We review approaches used to evaluate and quantify associations between climate and infectious disease incidence, discuss the array of data available to tackle this question, and detail remaining challenges in understanding the implications of climate change for infectious disease incidence. We point to areas where synthesis between approaches used in climate science and infectious disease biology provide potential for progress.

Oxygen concentrations are hypothesized to decrease in many areas of the ocean as a result of anthropogenically-driven climate change, resulting in habitat compression for pelagic animals. The oxygen partial pressure, pO2, at which blood is 50% saturated (P50) is a measure of blood oxygen affinity and a gauge of the tolerance of animals for low ambient oxygen. Tuna species display a wide range of blood oxygen affinities (i.e., P50 values) and therefore may be differentially impacted by habitat compression as they make extensive vertical movements to forage on sub-daily time scales. To project the effects of end-of-the-century climate change on tuna habitat, we calculate tuna P50 depths (i.e., the vertical position in the water column at which ambient pO2 is equal to species-specific blood P50 values) from 21st century Earth System Model (ESM) projections included in the fifth phase of the Climate Model Intercomparison Project (CMIP5). Overall, we project P50 depths to shoal, indicating likely habitat compression for tuna species due to climate change. Tunas that will be most impacted by shoaling are Pacific and southern bluefin tunas – habitat compression is projected for the entire geographic range of Pacific bluefin tuna and for the spawning region of southern bluefin tuna. Vertical shifts in P50 depths will potentially influence resource partitioning among Pacific bluefin, bigeye, yellowfin, and skipjack tunas in the northern subtropical and eastern tropical Pacific Ocean, the Arabian Sea, and the Bay of Bengal. By establishing linkages between tuna physiology and environmental conditions, we provide a mechanistic basis to project the effects of anthropogenic climate change on tuna habitats.

We investigated regime shifts in seasonal zooplankton communities of the Northeast continental shelf Large Marine Ecosystem (NES) and its subcomponent ecoregions over a multi-decadal period (1977–2013). Our cross ecoregion analysis shows that regime shifts in different ecoregions often exhibited very distinct characteristics, emphasizing more granular fluctuations in NES plankton communities relative to previous work. Shifts early in the time series generally reflected an increase in abundance levels. The response of zooplankton abundance within fall communities was more similar among ecoregions than for spring communities. The Gulf of Maine exhibited highly distinct patterns from other ecoregions, with regime shifts identified in the early 1980s, early 2000s, and mid-2000s for spring communities. Regime shifts were identified in the early to mid-1990s for the NES, Georges Bank, and the Mid-Atlantic Bight ecoregions, while the fall communities experienced shifts in the early 1990s and late 1980s for the NES and Georges Bank, but in the late 1990s in the Mid-Atlantic Bight. A constrained correspondence analysis of zooplankton community against local and basin-scale climatological indices suggests that water temperature, stratification, and the Atlantic multidecadal oscillation (AMO) were the predominant factors in driving the zooplankton community composition.

Illness caused by pathogenic strains of Vibrio bacteria incurs significant economic and health care costs in many areas around the world. In the Chesapeake Bay, the two most problematic species are V. vulnificus and V. parahaemolyticus, which cause infection both from exposure to contaminated water and consumption of contaminated seafood. We used existing Vibrio habitat models, four global climate models, and a recently developed statistical downscaling framework to project the spatiotemporal probability of occurrence of V. vulnificus and V. cholerae in the estuarine environment, and the mean concentration of V. parahaemolyticus in oysters in the Chesapeake Bay by the end of the 21st century. Results showed substantial future increases in season length and spatial habitat for V. vulnificus and V. parahaemolyticus, while projected increase in V. cholerae habitat was less marked and more spatially heterogeneous. Our findings underscore the need for spatially variable inputs into models of climate impacts on Vibrios in estuarine environments. Overall, economic costs associated with Vibrios in the Chesapeake Bay, such as incidence of illness and management measures on the shellfish industry, may increase under climate change, with implications for recreational and commercial uses of the ecosystem.

Two state-of-the-art Earth System Models (ESMs) were used in an idealized experiment to explore the role of mountains in shaping Earth’s climate system. Similar to previous studies, removing mountains from both ESMs results in the winds becoming more zonal, and weaker Indian and Asian monsoon circulations. However, there are also broad changes to the Walker circulation and the El Niño Southern Oscillation (ENSO). Without orography, convection moves across the entire equatorial Indo-Pacific basin on interannual timescales. The ENSO has a stronger amplitude, lower frequency and increased regularity. A wider equatorial wind zone and changes to equatorial wind stress curl result in a colder cold tongue and a steeper equatorial thermocline across the Pacific basin during La Niña years. Anomalies associated with ENSO warm events are larger without mountains, and have greater impact on the mean tropical climate than when mountains are present. Without mountains the centennial-mean Pacific Walker circulation weakens in both models by ~45%, but the strength of the mean Hadley circulation changes by <2%. Changes in the Walker circulation in these experiments can be explained by the large spatial excursions of atmospheric deep convection on interannual timescales. These results suggest that mountains are an important control on the large-scale tropical circulation, impacting ENSO dynamics and the Walker circulation, but have little impact on the strength of the Hadley circulation.

The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth System Models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) versus when integrated within fully coupled Earth System Models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled online to ocean circulation models, initialized with observational data or output from a model spin up, and forced by repeating the 1948–2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF6 and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin up, preferably for 2000 years or more and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are founded on those from previous phases of the Ocean Carbon-Cycle Model Intercomparison Project. They have been merged and updated to reflect improvements concerning gas exchange, carbonate chemistry, and new data for initial conditions and atmospheric gas histories. Code is provided to facililtate their implementation.

Climate-related shifts in marine mammal range and distribution have been observed in some populations; however, the nature and magnitude of future responses are uncertain in novel environments projected under climate change. This poses a challenge for agencies charged with management and conservation of these species. Specialized diets, restricted ranges, or reliance on specific substrates or sites (e.g., for pupping) make many marine mammal populations particularly vulnerable to climate change. High-latitude, predominantly ice-obligate, species have experienced some of the largest changes in habitat and distribution and these are expected to continue. Efforts to predict and project marine mammal distributions to date have emphasized data-driven statistical habitat models. These have proven successful for short time-scale (e.g., seasonal) management activities, but confidence that such relationships will hold for multi-decade projections and novel environments is limited. Recent advances in mechanistic modeling of marine mammals (i.e., models that rely on robust physiological and ecological principles expected to hold under climate change) may address this limitation. The success of such approaches rests on continued advances in marine mammal ecology, behavior, and physiology together with improved regional climate projections. The broad scope of this challenge suggests initial priorities be placed on vulnerable species or populations (those already experiencing declines or projected to undergo ecological shifts resulting from climate changes that are consistent across climate projections) and species or populations for which ample data already exist (with the hope that these may inform climate change sensitivities in less well observed species or populations elsewhere). The sustained monitoring networks, novel observations, and modeling advances required to more confidently project marine mammal distributions in a changing climate will ultimately benefit management decisions across time-scales, further promoting the resilience of marine mammal populations.

Photosynthesis fuels marine food webs, yet differences in fish catch across globally distributed marine ecosystems far exceed differences in net primary production (NPP). We consider the hypothesis that ecosystem-level variations in pelagic and benthic energy flows from phytoplankton to fish, trophic transfer efficiencies, and fishing effort can quantitatively reconcile this contrast in an energetically consistent manner. To test this hypothesis, we enlist global fish catch data that include previously neglected contributions from small-scale fisheries, a synthesis of global fishing effort, and plankton food web energy flux estimates from a prototype high-resolution global earth system model (ESM). After removing a small number of lightly fished ecosystems, stark interregional differences in fish catch per unit area can be explained (r = 0.79) with an energy-based model that (i) considers dynamic interregional differences in benthic and pelagic energy pathways connecting phytoplankton and fish, (ii) depresses trophic transfer efficiencies in the tropics and, less critically, (iii) associates elevated trophic transfer efficiencies with benthic-predominant systems. Model catch estimates are generally within a factor of 2 of values spanning two orders of magnitude. Climate change projections show that the same macroecological patterns explaining dramatic regional catch differences in the contemporary ocean amplify catch trends, producing changes that may exceed 50% in some regions by the end of the 21st century under high-emissions scenarios. Models failing to resolve these trophodynamic patterns may significantly underestimate regional fisheries catch trends and hinder adaptation to climate change.

The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent fifth phase, CMIP5, has created nearly two petabytes of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP, i.e. CMIP6: How does the Earth System respond to changes in forcing? What are the origins and consequences of systematic model biases? How can we assess future climate changes given internal climate variability, predictability and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor and requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP which remain a major climate modeling challenge. These biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.

Successful projection of the distribution of surface temperature change increases our confidence in climate models. Here we evaluate projections of global warming from almost 30 years ago using the observations made during the past half century.

Ecosystem carbon (C) balance is hypothesised to be sensitive to the mycorrhizal strategies that plants use to acquire nutrients. To test this idea, we coupled an optimality-based plant nitrogen (N) acquisition model with a microbe-focused soil organic matter (SOM) model. The model accurately predicted rhizosphere processes and C–N dynamics across a gradient of stands varying in their relative abundance of arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) trees. When mycorrhizal dominance was switched – ECM trees dominating plots previously occupied by AM trees, and vice versa – legacy effects were apparent, with consequences for both C and N stocks in soil. Under elevated productivity, ECM trees enhanced decomposition more than AM trees via microbial priming of unprotected SOM. Collectively, our results show that ecosystem responses to global change may hinge on the balance between rhizosphere priming and SOM protection, and highlight the importance of dynamically linking plants and microbes in terrestrial biosphere models.

Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefitting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystem-relevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.

Populations of small pelagic fish are strongly influenced by climate. The inability of managers to anticipate environment-driven fluctuations in stock productivity or distribution can lead to overfishing and stock collapses, inflexible management regulations inducing shifts in the functional response to human predators, lost opportunities to harvest populations, bankruptcies in the fishing industry, and loss of resilience in the human food supply. Recent advances in dynamical global climate prediction systems allow for sea surface temperature (SST) anomaly predictions at a seasonal scale over many shelf ecosystems. Here we assess the utility of SST predictions at this “fishery relevant” scale to inform management, using Pacific sardine as a case study. The value of SST anomaly predictions to management was quantified under four harvest guidelines (HGs) differing in their level of integration of SST data and predictions. The HG that incorporated stock biomass forecasts informed by skillful SST predictions led to increases in stock biomass and yield, and reductions in the probability of yield and biomass falling below socioeconomic or ecologically acceptable levels. However, to mitigate the risk of collapse in the event of an erroneous forecast, it was important to combine such forecast-informed harvest controls with additional harvest restrictions at low biomass.

Decisions made by fishers and fisheries managers are informed by climate and fisheries observations that now often span more than 50 years. Multi-annual climate forecasts could further inform such decisions if they were skillful in predicting future conditions relative to the 50-year scope of past variability. We demonstrate that an existing multi-annual prediction system skillfully forecasts the probability of next year, the next 1–3 years, and the next 1–10 years being warmer or cooler than the 50-year average at the surface in coastal ecosystems. Probabilistic forecasts of upper and lower seas surface temperature (SST) terciles over the next 3 or 10 years from the GFDL CM 2.1 10-member ensemble global prediction system showed significant improvements in skill over the use of a 50-year climatology for most Large Marine Ecosystems (LMEs) in the North Atlantic, the western Pacific, and Indian oceans. Through a comparison of the forecast skill of initialized and uninitialized hindcasts, we demonstrate that this skill is largely due to the predictable signature of radiative forcing changes over the 50-year timescale rather than prediction of evolving modes of climate variability. North Atlantic LMEs stood out as the only coastal regions where initialization significantly contributed to SST prediction skill at the 1 to 10 year scale.

Anthropogenic climate change has shifted the biogeography and phenology of many terrestrial and marine species. Marine phytoplankton communities appear sensitive to climate change, yet understanding of how individual species may respond to anthropogenic climate change remains limited. Here, using historical environmental and phytoplankton observations, we characterize the realized ecological niches for 87 North Atlantic diatom and dinoflagellate taxa and project changes in species biogeography between mean historical (1951–2000) and future (2051–2100) ocean conditions. We find that the central positions of the core range of 74% of taxa shift poleward at a median rate of 12.9 km per decade (km⋅dec−1), and 90% of taxa shift eastward at a median rate of 42.7 km⋅dec−1. The poleward shift is faster than previously reported for marine taxa, and the predominance of longitudinal shifts is driven by dynamic changes in multiple environmental drivers, rather than a strictly poleward, temperature-driven redistribution of ocean habitats. A century of climate change significantly shuffles community composition by a basin-wide median value of 16%, compared with seasonal variations of 46%. The North Atlantic phytoplankton community appears poised for marked shift and shuffle, which may have broad effects on food webs and biogeochemical cycles.

The response of the terrestrial water cycle to global warming is central to issues including water resources, agriculture and ecosystem health. Recent studies1, 2, 3, 4, 5, 6 indicate that aridity, defined in terms of atmospheric supply (precipitation, P) and demand (potential evapotranspiration, Ep) of water at the land surface, will increase globally in a warmer world. Recently proposed mechanisms for this response emphasize the driving role of oceanic warming and associated atmospheric processes4, 5. Here we show that the aridity response is substantially amplified by land–atmosphere feedbacks associated with the land surface’s response to climate and CO2 change. Using simulations from the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment7, 8, 9, we show that global aridity is enhanced by the feedbacks of projected soil moisture decrease on land surface temperature, relative humidity and precipitation. The physiological impact of increasing atmospheric CO2 on vegetation exerts a qualitatively similar control on aridity. We reconcile these findings with previously proposed mechanisms5 by showing that the moist enthalpy change over land is unaffected by the land hydrological response. Thus, although oceanic warming constrains the combined moisture and temperature changes over land, land hydrology modulates the partitioning of this enthalpy increase towards increased aridity.

We use a large initial condition suite of simulations (30 runs) with an Earth system model to assess the detectability of biogeochemical impacts of ocean acidification (OA) on the marine alkalinity distribution from decadally repeated hydrographic measurements such as those produced by the Global Ship-Based Hydrographic Investigations Program (GO-SHIP). Detection of these impacts is complicated by alkalinity changes from variability and long-term trends in freshwater and organic matter cycling and ocean circulation. In our ensemble simulation, variability in freshwater cycling generates large changes in alkalinity that obscure the changes of interest and prevent the attribution of observed alkalinity redistribution to OA. These complications from freshwater cycling can be mostly avoided through salinity normalization of alkalinity. With the salinity-normalized alkalinity, modeled OA impacts are broadly detectable in the surface of the subtropical gyres by 2030. Discrepancies between this finding and the finding of an earlier analysis suggest that these estimates are strongly sensitive to the patterns of calcium carbonate export simulated by the model. OA impacts are detectable later in the subpolar and equatorial regions due to slower responses of alkalinity to OA in these regions and greater seasonal equatorial alkalinity variability. OA impacts are detectable later at depth despite lower variability due to smaller rates of change and consistent measurement uncertainty.

Observations indicate that spring and fall phytoplankton blooms on the Eastern Bering Sea (EBS) continental shelf tend to co-vary on inter-annual scales – that is, a year with a strong spring bloom also tends to have a strong fall bloom. Similar co-variability of primary production is also seen in the multi-year (1987–2007) integration of a coupled physical–biological model. Moreover, the modeled seasonal amplitudes of 10-meter chlorophyll-a concentrations at the EBS middle shelf mooring locations, computed using the canonical Redfield ratio and a mean carbon-to-chlorophyll-a ratio, are generally consistent with the in situ mooring measurements. The coupled physical–biological model simulation is used to examine the relative contributions of wind mixing, local nutrient recycling/regeneration, horizontal nutrient advection, and water-column stability to this co-variability. There is no significant correlation between the spring and fall surface wind mixing. Although wind mixing is an important mechanism for bringing nutrients in the lower water column to the surface layers, it is not the mechanism tying the two seasons׳ productivity together. Local regeneration/recycling of the nutrients initially fueling spring production is an important mechanism for spring-to-fall nutrient accumulation in the bottom layers at the middle shelf. Horizontal advection does not appear to be the dominant factor for supplying nutrients to the middle shelf during the spring-to-fall period. Fall primary production in the model is strongly influenced by the lower water-column stability/stratification. Taken together, these results highlight the importance of local recycling/regeneration of nutrients assimilated by spring phytoplankton bloom in linking together the spring and fall primary productions on EBS middle shelf.

The global ocean is projected to be warmer, less oxygenated and more acidic in the 21st century relative to the present day, resulting in changes in the biogeography and productivity of marine organisms and ecosystems. Previous studies using a Dynamic Bioclimate Envelope Model (DBEM) projected increases in potential catch in high latitude regions and decreases in tropical regions over the next few decades. A major structural uncertainty of the projected redistribution of species and fisheries catches can be attributed to the habitat suitability algorithms used. Here, we compare the DBEM projections of potential catches of 500 species of exploited marine fishes and invertebrates from 1971 to 2060 using three versions of DBEM that differ by the algorithm used to predict relative habitat suitability: DBEM-Basic, DBEM-Maxent and DBEM-Aquamaps. All the DBEM models have similar skill in predicting the occurrence of exploited species and distribution of observed fisheries production. Globally, the models project a decrease in catch potential of 3% to 13% by 2050 under a high emissions scenario (Representative Concentration Pathway 8.5). For the majority of the modelled species, projections by DBEM-Maxent are less sensitive to changes in ocean properties than those by DBEM-Aquamaps. The mean magnitude of projected changes relative to differences between projections differ between regions, being highest (>1 times the standard deviation) in the tropical regions and Arctic Ocean and lowest in three of the main Eastern Boundary Upwelling regions, the eastern Indian Ocean and the Southern Ocean. These results suggest that the qualitative patterns of changes in catch potential reported in previous studies are not affected by the structural uncertainty of DBEM, particularly in areas where catch potential was projected to be most sensitive to climate change. However, when making projections of fish stocks and their potential catches using DBEM in the future, multiple versions of DBEM should be used to quantify the uncertainty associated with structural uncertainty of the models. Overall, this study contributes to improving projection of future changes in living marine resources by exploring one aspect of the cascade of uncertainty associated with such projections.

The Fifth Assessment Report of the Intergovernmental Panel on Climate Change highlights that climate change and ocean acidification are challenging the sustainable management of living marine resources (LMRs). Formal and systematic treatment of uncertainty in existing LMR projections, however, is lacking. We synthesize knowledge of how to address different sources of uncertainty by drawing from climate model intercomparison efforts. We suggest an ensemble of available models and projections, informed by observations, as a starting point to quantify uncertainties. Such an ensemble must be paired with analysis of the dominant uncertainties over different spatial scales, time horizons, and metrics. We use two examples: (i) global and regional projections of Sea Surface Temperature and (ii) projection of changes in potential catch of sablefish (Anoplopoma fimbria) in the 21st century, to illustrate this ensemble model approach to explore different types of uncertainties. Further effort should prioritize understanding dominant, undersampled dimensions of uncertainty, as well as the strategic collection of observations to quantify, and ultimately reduce, uncertainties. Our proposed framework will improve our understanding of future changes in LMR and the resulting risk of impacts to ecosystems and the societies under changing ocean conditions.

Attributing uncertainty in ocean carbon uptake between societal trajectory (scenarios), earth system model construction (structure), and inherent natural variation in climate (internal), is critical to make progress in identifying, understanding and reducing those uncertainties. In the present issue of Global Biogeochemical Cycles, Lovenduski et al. (2016) disentangle these drivers of uncertainty in ocean carbon uptake over time and space and assess the resulting implications for the emergence timescales of structural and scenario uncertainty over internal variability. Such efforts are critical for establishing realizable and efficient monitoring goals and prioritizing areas of continued model development. Under recently proposed climate stabilization targets, such efforts to partition uncertainty also become increasingly critical to societal decision-making in the context of carbon stabilization.

Observations show that Australian dust activity varies by a factor of 4 on decadal timescales. General circulation models, however, typically fail to simulate this variability. Here we introduce a new dust parameterization into the NOAA/Geophysical Fluid Dynamics Laboratory climate model CM3 that represents land surface processes controlling dust sources including soil water and ice, snow cover, vegetation characteristics, and land type. In an additional novel step, we couple this new dust parameterization to the dynamic vegetation model LM3. In Australia, the new parameterization amplifies the magnitude and timescale of dust variability and better simulates the El Niño–Southern Oscillation-dust relationship by more than doubling its strength. We attribute these improvements primarily to the slow response time of vegetation to precipitation anomalies and show that vegetation changes account for approximately 50% of enhanced dust emission during El Niño events. The amplified dust leads to radiative forcing over Australia greater than −1 and −20 W/m2 at top of atmosphere and surface, respectively.

By coordinating the design and distribution of global climate model simulations of the past, current and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima experiments) and the CMIP Historical Simulation (1850–near-present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP, (2) common standards, coordination, infrastructure and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble, and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and the CMIP Historical Simulation to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP Historical Simulation, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. The participation in the CMIP6-Endorsed MIPs will be at the discretion of the modelling groups, and will depend on scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: (i) how does the Earth system respond to forcing?, (ii) what are the origins and consequences of systematic model biases?, and (iii) how can we assess future climate changes given climate variability, predictability and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and the CMIP6 Historical Simulation, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.

The Coupled Model Intercomparison Project (CMIP) has successfully provided the climate community with a rich collection of simulation output from Earth system models (ESMs) that can be used to understand past climate changes and make projections and uncertainty estimates of the future. Confidence in ESMs can be gained because the models are based on physical principles and reproduce many important aspects of observed climate. More research is required to identify the processes that are most responsible for systematic biases and the magnitude and uncertainty of future projections so that more relevant performance tests can be developed. At the same time, there are many aspects of ESM evaluation that are well established and considered an essential part of systematic evaluation but have been implemented ad hoc with little community coordination. Given the diversity and complexity of ESM analysis, we argue that the CMIP community has reached a critical juncture at which many baseline aspects of model evaluation need to be performed much more efficiently and consistently. Here, we provide a perspective and viewpoint on how a more systematic, open, and rapid performance assessment of the large and diverse number of models that will participate in current and future phases of CMIP can be achieved, and announce our intention to implement such a system for CMIP6. Accomplishing this could also free up valuable resources as many scientists are frequently "re-inventing the wheel" by re-writing analysis routines for well-established analysis methods. A more systematic approach for the community would be to develop and apply evaluation tools that are based on the latest scientific knowledge and observational reference, are well suited for routine use, and provide a wide range of diagnostics and performance metrics that comprehensively characterize model behaviour as soon as the output is published to the Earth System Grid Federation (ESGF). The CMIP infrastructure enforces data standards and conventions for model output and documentation accessible via the ESGF, additionally publishing observations (obs4MIPs) and reanalyses (ana4MIPs) for model intercomparison projects using the same data structure and organization as the ESM output. This largely facilitates routine evaluation of the ESMs, but to be able to process the data automatically alongside the ESGF, the infrastructure needs to be extended with processing capabilities at the ESGF data nodes where the evaluation tools can be executed on a routine basis. Efforts are already underway to develop community-based evaluation tools, and we encourage experts to provide additional diagnostic codes that would enhance this capability for CMIP. At the same time, we encourage the community to contribute observations and reanalyses for model evaluation to the obs4MIPs and ana4MIPs archives. The intention is to produce through the ESGF a widely accepted quasi-operational evaluation framework for CMIP6 that would routinely execute a series of standardized evaluation tasks. Over time, as this capability matures, we expect to produce an increasingly systematic characterization of models which, compared with early phases of CMIP, will more quickly and openly identify the strengths and weaknesses of the simulations. This will also reveal whether long-standing model errors remain evident in newer models and will assist modelling groups in improving their models. This framework will be designed to readily incorporate updates, including new observations and additional diagnostics and metrics as they become available from the research community.

Future projections of potential ocean ecosystem stressors, such as acidification, warming, deoxygenation and changes in ocean productivity, are uncertain due to incomplete understanding of fundamental processes, internal climate variability, and divergent carbon emissions scenarios. This complicates climate change impact assessments. We evaluate the relative importance of these uncertainty sources in projections of potential stressors as a function of projection lead-time and spatial scale. Internally generated climate variability is the dominant source of uncertainty in mid-to-low latitudes and in most coastal Large Marine Ecosystems over the next few decades, suggesting irreducible uncertainty inherent in these short projections. Uncertainty in projections of century-scale global sea surface temperature (SST), global thermocline oxygen, and regional surface pH is dominated by scenario uncertainty, highlighting the critical importance of policy decisions on carbon emissions. In contrast, uncertainty in century-scale projections of net primary productivity (NPP), low oxygen waters, and Southern Ocean SST is dominated by model uncertainty, underscoring the importance of overcoming deficiencies in scientific understanding and improved process representation in Earth system models are critical for making more robust projections of these potential stressors. We also show that changes in the combined potential stressors emerge from the noise in 39% (34 – 44%) of the ocean by 2016-2035 relative to the 1986-2005 reference period and in 54% (50 – 60%) of the ocean by 2076-2095 following a high carbon emissions scenario. Projected large changes in surface pH and SST can be reduced substantially and rapidly with aggressive carbon emission mitigation, but only marginally for oxygen. The regional importance of model uncertainty and internal variability underscores the need for expanded and improved multi-model and large initial condition ensemble projections with Earth system models for evaluating regional marine resource impacts.

Formal detection and attribution studies have used observations and climate models to identify an anthropogenic warming signature in the upper (0–700 m) ocean1, 2, 3, 4. Recently, as a result of the so-called surface warming hiatus, there has been considerable interest in global ocean heat content (OHC) changes in the deeper ocean, including natural and anthropogenically forced changes identified in observational5, 6, 7, modelling8, 9 and data re-analysis10, 11 studies. Here, we examine OHC changes in the context of the Earth’s global energy budget since early in the industrial era (circa 1865–2015) for a range of depths. We rely on OHC change estimates from a diverse collection of measurement systems including data from the nineteenth-century Challenger expedition12, a multi-decadal record of ship-based in situ mostly upper-ocean measurements, the more recent near-global Argo floats profiling to intermediate (2,000 m) depths13, and full-depth repeated transoceanic sections5. We show that the multi-model mean constructed from the current generation of historically forced climate models is consistent with the OHC changes from this diverse collection of observational systems. Our model-based analysis suggests that nearly half of the industrial-era increases in global OHC have occurred in recent decades, with over a third of the accumulated heat occurring below 700 m and steadily rising.

The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses these aims in two complementary manners: (A) by providing an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing, (B) by providing a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) offering details for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows that of the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II have become the standard method to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP (Scenario MIP), as well as the ocean-sea ice OMIP simulations. The bulk of this paper offers scientific rationale for saving these diagnostics.

Coordinated experimental design and implementation has become a cornerstone of global climate modelling. So-called Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models to identify common signals and understand model similarities and differences without being hindered by ad-hoc differences in model set-up or experimental boundary conditions. The activity known as the Coupled Model Intercomparison Project (CMIP) has thus grown significantly in scope and as it enters its 6th phase, CMIP6, the design and documentation of individual simulations has been devolved to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilise climate or avoid dangerous climate change. For over a decade C4MIP has coordinated coupled climate-carbon cycle simulations and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has formed this experimental design the simulations also fit into the wider CMIP activity and conform to some common standards such as documentation and diagnostic requests and are designed to complement the CMIP core experiments known as the DECK. C4MIP has 3 key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation; (2) idealised coupled and partially-coupled simulations with 1 % per year increases in CO2 to enable diagnosis of feedback strength and its components; (3) future scenario simulations to project how the Earth System will respond over the 21st century and beyond to anthropogenic activity. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set-up and run the simulations. Particular attention is paid to boundary conditions and input data required, and also the output diagnostics requested. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.

Nitrous oxide (N2O) is an important greenhouse gas and ozone depleting substance. Previous projections of agricultural N2O (the dominant anthropogenic source) show emissions changing in tandem, or at a faster rate than changes in nitrogen (N) consumption. However, recent studies suggest that the carbon dioxide (CO2) fertilization effect may increase plant N uptake, which could decrease soil N losses and dampen increases in N2O. To evaluate this hypothesis at a global scale, we use a process-based land model with a coupled carbon-nitrogen cycle to examine how changes in climatic factors, land-use, and N application rates could affect agricultural N2O emissions by 2050. Assuming little improvement in N use efficiency (NUE), the model projects a 24%–31% increase in global agricultural N2O emissions by 2040–2050 depending on the climate scenario—a relatively moderate increase compared to the projected increases in N inputs (42%–44%) and previously published emissions projections (38%–75%). This occurs largely because the CO2 fertilization effect enhances plant N uptake in several regions, which subsequently dampens N2O emissions. And yet, improvements in NUE could still deliver important environmental benefits by 2050: equivalent to 10 Pg CO2 equivalent and 0.6 Tg ozone depletion potential.

Thermal expansion of the ocean in response to warming is an important component of historical sea-level rise1. Observational studies show that the Atlantic and Southern oceans are warming faster than the Pacific Ocean2, 3, 4, 5. Here we present simulations using a numerical atmospheric-ocean general circulation model with an interactive carbon cycle to evaluate the impact of carbon emission rates, ranging from 2 to 25 GtC yr−1, on basin-scale ocean heat uptake and sea level. For simulations with emission rates greater than 5 GtC yr−1, sea-level rise is larger in the Atlantic than Pacific Ocean on centennial timescales. This basin-scale asymmetry is related to the shorter flushing timescales and weakening of the overturning circulation in the Atlantic. These factors lead to warmer Atlantic interior waters and greater thermal expansion. In contrast, low emission rates of 2 and 3 GtC yr−1 will cause relatively larger sea-level rise in the Pacific on millennial timescales. For a given level of cumulative emissions, sea-level rise is largest at low emission rates. We conclude that Atlantic coastal areas may be particularly vulnerable to near-future sea-level rise from present-day high greenhouse gas emission rates.

The North Pacific gyre boundaries are characterized by stark contrasts in physical and biogeochemical properties. Meridional movement of gyre boundaries, influenced by climate change, can therefore exert a large influence on not only marine ecosystems but also on climate. We examine the evidence for wind-driven southward shifts in subsurface temperature, salinity, PO₄, and O₂ within the Northwest Pacific from the 1950s to the 2000s. Gyre boundary shifts can explain 30 ~ 60% of temperature and salinity trends zonally averaged in the Northwest Pacific, and observed PO₄ and O₂ trends along the 137°E and 144°E meridians. The close tie between the wind-driven shifts in gyre boundaries and the tracer distributions is further supported by results from an eddy-resolving (0.1° × 0.1°) GFDL climate model, suggesting that the physical and biogeochemical properties averaged within the Northwest Pacific gyre boundaries closely follow the latitude changes of the zero Sverdrup stream function with lags of zero to three years. The gyre shift effect on tracer distribution is poorly represented in a coarse resolution (1° × 1°) model due partly to poor representations of fronts and eddies. This study suggests that future changes in Northwest Pacific PO₄ and O₂ content may depend not only on ocean temperature and stratification, but also on the ocean gyre response to winds.

Accurate projections of marine particle export production (EP) are crucial for predicting the response of the marine carbon cycle to climate change, yet models show a wide range in both global EP and their responses to climate change. This is, in part, due to EP being the net result of a series of processes, starting with net primary production (NPP) in the sunlit upper ocean, followed by the formation of particulate organic matter and the subsequent sinking and remineralization of these particles, with each of these processes responding differently to changes in environmental conditions. Here, we compare future projections in EP over the 21st century, generated by four marine ecosystem models under IPCC's high emission scenario RCP8.5, and determine the processes driving these changes. The models simulate small to modest decreases in global EP between −1 and −12 %. Models differ greatly with regard to the drivers causing these changes. Among them, the formation of particles is the most uncertain process with models not agreeing on either magnitude or the direction of change. The removal of the sinking particles by remineralization is simulated to increase in the low and intermediate latitudes in three models, driven by either warming-induced increases in remineralization or slower particle sinking, and show insignificant changes in the remaining model. Changes in ecosystem structure, particularly the relative role of diatoms matters as well, as diatoms produce larger and denser particles that sink faster and are partly protected from remineralization. Also this controlling factor is afflicted with high uncertainties, particularly since the models differ already substantially with regard to both the initial (present-day) distribution of diatoms (between 11–94 % in the Southern Ocean) and the diatom contribution to particle formation (0.6–3.8 times lower/higher than their contribution to biomass). As a consequence, changes in diatom concentration are a strong driver for EP changes in some models but of low significance in others. Observational and experimental constraints on ecosystem structure and how the fixed carbon is routed through the ecosystem to produce export production are urgently needed in order to improve current generation ecosystem models and their ability to project future changes.

Human land-use activities have resulted in large to the Earth surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the questions: (1) What are the effects of LULCC on climate and biogeochemical cycling (past–future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy and are there regional land-management strategies with promise to help mitigate and/or adapt to climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from land-use change relative to fossil fuel emissions, separation of biogeochemical from biogeophysical effects of land-use, the unique impacts of land-cover change versus land management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent that impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use. LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use dataset, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to-. In this paper, we describe the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to experiments from the CMIP core, ScenarioMIP, and C4MIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model experiments designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request (primary and secondary land, crops, pasture, urban). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible.

Despite 30 years of basin-wide nutrient-reduction efforts, severe hypoxia continues to be observed in the Chesapeake Bay. Here we demonstrate the critical influence of climate variability, interacting with accumulated nitrogen (N) over multidecades, on Susquehanna River dissolved nitrogen (DN) loads, known precursors of the hypoxia in the Bay. We used the process model LM3-TAN (Terrestrial and Aquatic Nitrogen), which is capable of capturing both seasonal and decadal-to-century changes in vegetation-soil-river N storage, and produced nine scenarios of DN-load distributions under different short-term scenarios of climate variability and extremes. We illustrate that after 1 to 3 yearlong dry spells, the likelihood of exceeding a threshold DN load (56 kt yr−1) increases by 40 to 65% due to flushing of N accumulated throughout the dry spells and altered microbial processes. Our analyses suggest that possible future increases in climate variability/extremes—specifically, high precipitation occurring after multiyear dry spells—could likely lead to high DN-load anomalies and hypoxia.

The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959–2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free versus ice-influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling.

A number of recent studies investigated impacts of Land-Use and Land-Cover Changes (LULCC) on climate with global Earth System Models (ESMs). Yet many ESMs are still missing a representation of the most extreme form of natural landscape modification – urban settlements. Moreover, long-term (i.e. decades to century) transitions between build-up and other land cover types due to urbanization and de-urbanization have not been examined in the literature. In this study we evaluate a new urban canopy model (UCM) that characterizes urban physical and biogeochemical processes within the sub-grid tiling framework of the Geophysical Fluid Dynamics Laboratory (GFDL) land model, LM3. The new model LM3-UCM is based on the urban canyon concept and simulates exchange of energy, water (liquid and solid), and carbon between urban land and the atmosphere. LM3-UCM has several unique features, including explicit treatment of vegetation inside the urban canyon and dynamic transition between urban, agricultural and unmanaged tiles. The model is evaluated using observational datasets collected at three urban sites: Marseille in France, Basel in Switzerland and Baltimore in the United States. It is found that LM3-UCM satisfactorily reproduces canyon air temperature, surface temperatures, radiative fluxes, and turbulent heat fluxes at the three urban sites. LM3-UCM can capture urban features in a computationally efficient manner and is incorporated into the land component of GFDL ESMs. This new capability will enable improved understanding of climate change effects on cities and the impacts of urbanization on climate.

Using a newly developed urban canopy model coupled to the Geophysical Fluid Dynamics Laboratory (GFDL) land model LM3 (LM3-UCM), this study examines the urban land use impacts over the Continental United States (CONUS) under the present-day climate and two future scenarios. Using natural (undisturbed) vegetation systems as references where no land use has occurred, the LM3-UCM simulations show that the spatial pattern of summer (June, July, and August) temperature differences between urban and natural vegetation systems is primarily controlled by the spatial pattern of differences in evapotranspiration, which further depends on the spatial distribution of precipitation. The magnitude of temperature differences generally increases as the summer precipitation amount increases and then levels off when the total summer precipitation amount exceeds 400 mm, which is broadly consistent with previous studies but with significant variability. In winter (December, January, February), the magnitude of temperature differences is more controlled by the building heating than the precipitation amount. At high latitudes where snow is an important factor in radiative balance, the magnitude is also affected by a larger net shortwave radiation input for urban areas due to the lower albedo of cities. Although both urban and natural vegetation temperatures increase as the climate warms, their increasing rates are different and hence their differences change with time. It is found that the multi-decadal trend of summer temperature difference is negligible. However, the winter temperature differences show a strong negative trend, which is caused by reduced building heating requirements under a warming climate.

Marine species ranging in size from microscopic zooplankton to large predatory fish move vertically in the ocean water column to forage for food and avoid predators. Oxygen and temperature decrease, often rapidly, from shallow to deeper depths, restricting the ability of species to use the vertical habitat. One physiological trait that determines the tolerance of organisms to low oxygen is the oxygen affinity of oxygen carrier proteins, hemoglobin and hemocyanin, in the blood. To quantify the range of oxygen affinities for marine organisms, we surveyed the literature for measurements of oxygen binding to blood at multiple temperatures to account for its temperature sensitivity. Oxygen affinity is mapped within the ocean environment using the depth at which oxygen pressure decreases to the point at which the blood is 50% oxygenated (P50 depth) as organisms move from the surface to depth in the ocean water column. We find that vertical gradients in both temperature and oxygen impact the vertical position and areal extent of P50 depths. Shifts in P50 due to temperature cause physiological types with the same P50 in the surface ocean to have different P50 depths and physiological types with different P50’s in the surface ocean to have the same P50 depth. The vertical distances between P50 depths are spatially variable, which may determine the frequency of ecological interactions, such as competition and predation. In summary, P50 depth, which represents a key physiological transition point between dexoxygenated and oxygenated blood, provides mechanistic insight into organism function within the water column of the global ocean.

Observed seasonal cycles in atmospheric potential oxygen (APO ~ O2 + 1.1 CO2) were used to evaluate 8 ocean biogeochemistry models from the Coupled Model Intercomparison Project (CMIP5). Model APO seasonal cycles were computed from the CMIP5 air-sea O2 and CO2 fluxes and compared to observations at 3 Southern Hemisphere monitoring sites. Four of the models captured either the observed APO seasonal amplitude or phasing relatively well, while the other four did not. Many models had an unrealistic seasonal phasing or amplitude of the CO2 flux, which in turn influenced APO. By 2100 under RCP8.5, the models projected little change in the O2 component of APO but large changes in the seasonality of the CO2 component associated with ocean acidification. The models with poorer performance on present-day APO tended to project larger net carbon uptake in the Southern Ocean, both today and in 2100.

We examine interannual variability of phytoplankton blooms in northwestern Arabian Sea and Gulf of Oman. Satellite data (SeaWIFS ocean color) shows two climatological blooms in this region, a wintertime bloom peaking in February and a summertime bloom peaking in September. A pronounced anti-correlation between the AVISO sea surface height anomaly (SSHA) and chlorophyll is found during the wintertime bloom. On a regional scale, interannual variability of the wintertime bloom is thus dominated by cyclonic eddies which vary in location from one year to another. These results were compared against the outputs from three different 3-D Earth System models. We show that two coarse (1°) models with the relatively complex biogeochemistry (TOPAZ) capture the annual cycle but neither eddies nor the interannual variability. An eddy-resolving model (GFDL CM2.6) with a simpler biogeochemistry (miniBLING) displays larger interannual variability, but overestimates the wintertime bloom and captures eddy-bloom coupling in the south but not in the north. The southern part of the domain is a region with a much sharper thermocline and nutricline relatively close to the surface, in which eddies modulate diffusive nutrient supply to the surface (a mechanism not previously emphasized in the literature). We suggest that for the model to simulate the observed wintertime blooms within cyclones, it will be necessary to represent this relatively unusual nutrient structure as well as the cyclonic eddies. This is a challenge in the Northern Arabian Sea as it requires capturing the details of the outflow from the Persian Gulf.

During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were carried out on the systematic assessment of the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. Mean-state assessments routinely compared model hindcasts to available modern biogeochemical observations. However, these assessments considered neither the extent of equilibrium in modeled biogeochemical reservoirs nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESM) contribute to model-to-model differences in the simulated fields. We take advantage of a 500 year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and is consistent when confronted against a larger ensemble of CMIP5 models. This shows that drift has implications on their performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to-model uncertainty. This requires more attention in future model intercomparison exercices in order to provide realistic ESM results on marine biogeochemistry and carbon cycle feedbacks.

Plant photosynthesis and respiration are the largest carbon fluxes between the terrestrial biosphere and the atmosphere1, and their parameterizations represent large sources of uncertainty in projections of land carbon uptake in Earth system models2, 3 (ESMs). The incorporation of temperature acclimation of photosynthesis and foliar respiration, commonly observed processes, into ESMs has been proposed as a way to reduce this uncertainty2. Here we show that, across 15 flux tower sites spanning multiple biomes at various locations worldwide (10° S–67° N), acclimation parameterizations4, 5 improve a model’s ability to reproduce observed net ecosystem exchange of CO2. This improvement is most notable in tropical biomes, where photosynthetic acclimation increased model performance by 36%. The consequences of acclimation for simulated terrestrial carbon uptake depend on the process, region and time period evaluated. Globally, including acclimation has a net effect of increasing carbon assimilation and storage, an effect that diminishes with time, but persists well into the future. Our results suggest that land models omitting foliar temperature acclimation are likely to overestimate the temperature sensitivity of terrestrial carbon exchange, thus biasing projections of future carbon storage and estimates of policy indicators such as the transient climate response to cumulative carbon emissions.

Numerical models of ocean biogeochemistry are relied upon to make projections about the impact of climate change on marine resources and test hypotheses regarding the drivers of past changes in climate and ecosystems. In large areas of the ocean, iron availability regulates the functioning of marine ecosystems and hence the ocean carbon cycle. Accordingly, our ability to quantify the drivers and impacts of fluctuations in ocean ecosystems and carbon cycling in space and time relies on first achieving an appropriate representation of the modern marine iron cycle in models. When the iron distributions from thirteen global ocean biogeochemistry models are compared against the latest oceanic sections from the GEOTRACES programme we find that all models struggle to reproduce many aspects of the observed spatial patterns. Models that reflect the emerging evidence for multiple iron sources or subtleties of its internal cycling perform much better in capturing observed features than their simpler contemporaries, particularly in the ocean interior. We show that the substantial uncertainty in the input fluxes of iron results in a very wide range of residence times across models, which has implications for the response of ecosystems and global carbon cycling to perturbations. Given this large uncertainty, iron-fertilisation experiments based on any single current generation model should be interpreted with caution. Improvements to how such models represent iron scavenging and also biological cycling are needed to raise confidence in their projections of global biogeochemical change in the ocean.

Connections between wildfires and modes of variability in climate are sought as a means for predicting fire activity on interannual to multi-decadal timescales. Several fire drivers, such as temperature and local drought index, have been shown to vary on these timescales, and analysis of tree-ring data suggests covariance between fires and climate oscillation indices in some regions. However, the shortness of the satellite record of global fire events limits investigations on larger spatial scales. Here we explore the interplay between climate variability and wildfire emissions with the preindustrial long control numerical experiments and historical ensembles of CESM1 and the NOAA/GFDL ESM2Mb. We find that interannual variability in fires is underpredicted in both Earth System models (ESMs) compared to present day fire emission inventories. Modeled fire emissions respond to the El Niño/southern oscillation (ENSO) and Pacific decadal oscillation (PDO) with increases in southeast Asia and boreal North America emissions, and decreases in southern North America and Sahel emissions, during the ENSO warm phase in both ESMs, and the PDO warm phase in CESM1. Additionally, CESM1 produces decreases in boreal northern hemisphere fire emissions for the warm phase of the Atlantic Meridional Oscillation. Through analysis of the long control simulations, we show that the 20th century trends in both ESMs are statistically significant, meaning that the signal of anthropogenic activity on fire emissions over this time period is detectable above the annual to decadal timescale noise. However, the trends simulated by the two ESMs are of opposite sign (CESM1 decreasing, ESM2Mb increasing), highlighting the need for improved understanding, proxy observations, and modeling to resolve this discrepancy.

High latitude phytoplankton blooms support productive fisheries and play an important role in oceanic uptake of atmospheric carbon dioxide. In the subarctic North Atlantic Ocean, blooms are a recurrent feature each year, while in the eastern subarctic Pacific only small changes in chlorophyll (Chl) are seen over the annual cycle. Here, we show that when evaluated using phytoplankton carbon biomass (Cphyto) rather than Chl, an annual bloom in the North Pacific is evident and can even rival blooms observed in the North Atlantic. The annual increase in subarctic Pacific phytoplankton biomass is not readily observed in the Chl record because it is paralleled by light- and nutrient-driven decreases in cellular pigment levels (Cphyto:Chl). Specifically, photoacclimation and iron stress effects on Cphyto:Chl oppose the biomass increase, leading to only modest changes in bulk Chl. The magnitude of the photoacclimation effect is quantified using descriptors of the near-surface light environment and a photophysiological model. Iron-stress effects are diagnosed from satellite chlorophyll fluorescence data. Last, we show that biomass accumulation in the Pacific is slower than the Atlantic, but is closely tied to similar levels of seasonal nutrient uptake in both basins. Annual cycles of satellite-derived Chl and Cphyto are reproduced by in situ autonomous profiling floats. These results contradict the long-standing paradigm that environmental conditions prevent phytoplankton accumulation in the subarctic Northeast Pacific and suggest a greater seasonal decoupling between phytoplankton growth and losses than traditionally implied. Further, our results highlight the role of physiological processes in shaping bulk properties, such as Chl, and their interpretation in studies of ocean ecosystem dynamics and climate change.

Marine viruses are critical drivers of ocean biogeochemistry, and their abundances vary spatiotemporally in the global oceans, with upper estimates exceeding 108 per ml. Over many years, a consensus has emerged that virus abundances are typically tenfold higher than microbial cell abundances. However, the true explanatory power of a linear relationship and its robustness across diverse ocean environments is unclear. Here, we compile 5,671 microbial cell and virus abundance estimates from 25 distinct marine surveys and find substantial variation in the virus-to-microbial cell ratio, in which a 10:1 model has either limited or no explanatory power. Instead, virus abundances are better described as nonlinear, power-law functions of microbial cell abundances. The fitted scaling exponents are typically less than 1, implying that the virus-to-microbial cell ratio decreases with microbial cell density, rather than remaining fixed. The observed scaling also implies that viral effect sizes derived from ‘representative’ abundances require substantial refinement to be extrapolated to regional or global scales.

The impacts of climate extremes on terrestrial ecosystems are poorly understood but important for predicting carbon cycle feedbacks to climate change. Coupled climate–carbon cycle models typically assume that vegetation recovery from extreme drought is immediate and complete, which conflicts with the understanding of basic plant physiology. We examined the recovery of stem growth in trees after severe drought at 1338 forest sites across the globe, comprising 49,339 site-years, and compared the results with simulated recovery in climate-vegetation models. We found pervasive and substantial “legacy effects” of reduced growth and incomplete recovery for 1 to 4 years after severe drought. Legacy effects were most prevalent in dry ecosystems, among Pinaceae, and among species with low hydraulic safety margins. In contrast, limited or no legacy effects after drought were simulated by current climate-vegetation models. Our results highlight hysteresis in ecosystem-level carbon cycling and delayed recovery from climate extremes.

The terrestrial biosphere is currently a strong carbon (C) sink but may switch to a source in the 21st century as climate-driven losses exceed CO2-driven C gains, thereby accelerating global warming. Although it has long been recognized that tropical climate plays a critical role in regulating interannual climate variability, the causal link between changes in temperature and precipitation and terrestrial processes remains uncertain. Here, we combine atmospheric mass balance, remote sensing-modeled datasets of vegetation C uptake, and climate datasets to characterize the temporal variability of the terrestrial C sink and determine the dominant climate drivers of this variability. We show that the interannual variability of global land C sink has grown by 50–100% over the past 50 y. We further find that interannual land C sink variability is most strongly linked to tropical nighttime warming, likely through respiration. This apparent sensitivity of respiration to nighttime temperatures, which are projected to increase faster than global average temperatures, suggests that C stored in tropical forests may be vulnerable to future warming.

Widespread negative correlations between summertime-mean temperatures and precipitation over land regions are a well-known feature of terrestrial climate. This behavior has generally been interpreted in the context of soil moisture-atmosphere coupling, with soil moisture deficits associated with reduced rainfall leading to enhanced surface sensible heating and higher surface temperature. The present study revisits the genesis of these negative temperature-precipitation correlations using simulations from the Global Land-Atmosphere Coupling Experiment - Coupled Model Intercomparison Project phase 5 (GLACE-CMIP5) multi-model experiment. The analyses are based on simulations with 5 climate models, which were integrated with prescribed (non-interactive) and with interactive soil moisture over the period 1950-2100. While the results presented here generally confirm the interpretation that negative correlations between seasonal temperature and precipitation arise through the direct control of soil moisture on surface heat flux partitioning, the presence of widespread negative correlations when soil moisture-atmosphere interactions are artificially removed in at least two out of five models suggests that atmospheric processes, in addition to land surface processes, contribute to the observed negative temperature-precipitation correlation. On longer timescales, the negative correlation between precipitation and temperature is shown to have implications for the projection of climate change impacts on near surface climate: in all models, in the regions of strongest temperature-precipitation anti-correlation on interannual timescales, long-term regional warming is modulated to a large extent by the regional response of precipitation to climate change, with precipitation increases (decreases) being associated with minimum (maximum) warming. This correspondence appears to arise largely as the result of soil-moisture atmosphere interactions.

Aim There has been considerable effort allocated to understanding the impact of climate change on our physical environment, but comparatively little to how life on Earth and ecosystem services will be affected. Therefore, we have developed a spatial–temporal food web model of the global ocean, spanning from primary producers through to top predators and fisheries. Through this, we aim to evaluate how alternative management actions may impact the supply of seafood for future generations. Location Global ocean. Methods We developed a modelling complex to initially predict the combined impact of environmental parameters and fisheries on global seafood production, and initially evaluated the model's performance through hindcasting. The modelling complex has a food web model as core, obtains environmental productivity from a biogeochemical model and assigns global fishing effort spatially. We tuned model parameters based on Markov chain random walk stock reduction analysis, fitting the model to historic catches. We evaluated the goodness-of-fit of the model to data for major functional groups, by spatial management units and globally. Results This model is the most detailed ever constructed of global fisheries, and it was able to replicate broad patterns of historic fisheries catches with best agreement for the total catches and good agreement for species groups, with more variation at the regional level. Main conclusions We have developed a modelling complex that can be used for evaluating the combined impact of fisheries and climate change on upper-trophic level organisms in the global ocean, including invertebrates, fish and other large vertebrates. The model provides an important step that will allow global-scale evaluation of how alternative fisheries management measures can be used for mitigation of climate change.

This study examines the role of processes transporting tracers across the Polar Front (PF) in the depth interval between the surface and major topographic sills, which we refer to as the “PF core”. A preindustrial control simulation of an eddying climate model coupled to a biogeochemical model (CM2.6-miniBLING, 0.1° ocean model) is used to investigate the transport of heat, carbon, oxygen and phosphate across the PF core, with a particular focus on the role of mesoscale eddies. We find that the total transport across the PF core results from an ubiquitous Ekman transport that drives the upwelled tracers to the north, and a localized opposing eddy transport that induces tracer leakages to the south at major topographic obstacles. In the Ekman layer, the southward eddy transport only partially compensates the northward Ekman transport, while below the Ekman layer, the southward eddy transport dominates the total transport but remains much smaller in magnitude than the near-surface northward transport. Most of the southward branch of the total transport is achieved below the PF core, mainly through geostrophic currents. We find that the eddy diffusive transport reinforces the southward eddy advective transport for carbon and heat, and opposes it for oxygen and phosphate. Eddy advective transport is likely to be the leading-order component of eddy-induced transport for all four tracers. However, eddy diffusive transport may provide a significant contribution to the southward eddy heat transport due to strong along-isopycnal temperature gradients.

The world’s major Eastern Boundary Currents (EBC) are critically important areas for global fisheries. Computational limitations have divided past EBC modeling into two types: high-resolution regional approaches that resolve the strong mesoscale structures involved; and coarse global approaches that represent the largescale context for EBCs but crudely resolve only the largest scales of their local manifestation. These latter global studies have illustrated the complex mechanisms involved in the climate change and acidification response in these regions, with the EBC response dominated not by local adjustments but large-scale reorganization of ocean circulation through remote forcing of water mass supply pathways. While qualitatively illustrating the limitations of regional high-resolution studies in long-term projections, these studies lack the ability to robustly quantify change because of the inability of these models to represent the baseline mesoscale structures of EBCs. In the present work, we compare current generation coarse resolution (1˚) and a prototype next generation high-resolution (1/10˚) Earth System Models (ESMs) from NOAA ’s Geophysical Fluid Dynamics Laboratory in representing the four major EBCs. We review the long-known temperature biases that the coarse models suffer in being unable to represent the timing and intensity of upwelling-favorable winds. In promising contrast, we show that the high-resolution prototype is capable of representing not only the overall mesoscale structure in physical and biogeochemical fields, but also the appropriate offshore extent of temperature anomalies and other EBC characteristics. In terms of representation of large-scale circulation, results were mixed, with the high-resolution prototype addressing some, but not all, of the biases in the coarse-resolution ESM. The ability to simulate EBCs in the global context at high resolution in global ESMs represents a fundamental milestone towards both seasonal to interannual ecological forecasting and long-term projection of climate, ecosystem, and acidification baselines and sensitivity. http://www.calcofi.org/publications/calcofireports/v56/Vol56-Dunne.web.72-75.pdf

The spring phytoplankton bloom on the US Northeast Continental Shelf is a feature of the ecosystem production cycle that varies annually in timing, spatial extent, and magnitude. To quantify this variability, we analyzed remotely-sensed ocean color data at two spatial scales, one based on ecologically defined sub-units of the ecosystem (production units) and the other on a regular grid (0.5°). Five units were defined: Gulf of Maine East and West, Georges Bank, and Middle Atlantic Bight North and South. The units averaged 47×103 km2 in size. The initiation and termination of the spring bloom were determined using change-point analysis with constraints on what was identified as a bloom based on climatological bloom patterns. A discrete spring bloom was detected in most years over much of the western Gulf of Maine production unit. However, bloom frequency declined in the eastern Gulf of Maine and transitioned to frequencies as low as 50% along the southern flank of the Georges Bank production unit. Detectable spring blooms were episodic in the Middle Atlantic Bight production units. In the western Gulf of Maine, bloom duration was inversely related to bloom start day; thus, early blooms tended to be longer lasting and larger magnitude blooms. We view this as a phenological mismatch between bloom timing and the “top-down” grazing pressure that terminates a bloom. Estimates of secondary production were available from plankton surveys that provided spring indices of zooplankton biovolume. Winter chlorophyll biomass had little effect on spring zooplankton biovolume, whereas spring chlorophyll biomass had mixed effects on biovolume. There was evidence of a “bottom up” response seen on Georges Bank where spring zooplankton biovolume was positively correlated with the concentration of chlorophyll. However, in the western Gulf of Maine, biovolume was uncorrelated with chlorophyll concentration, but was positively correlated with bloom start and negatively correlated with magnitude. This observation is consistent with both a “top-down” mechanism of control of the bloom and a “bottom-up” effect of bloom timing on zooplankton grazing. Our inability to form a consistent model of these relationships across adjacent systems underscores the need for further research.

We assess the uptake, transport and storage of oceanic anthropogenic carbon and heat over the period 1861 to 2005 in a new set of coupled carbon-climate Earth System models conducted for the fifth Coupled Model Intercomparison Project (CMIP5), with a particular focus on the Southern Ocean. Simulations show the Southern Ocean south of 30°S, occupying 30% of global surface ocean area, accounts for 43 ± 3% (42 ± 5 Pg C) of anthropogenic CO2 and 75 ± 22% (23 ± 9 *1022J) of heat uptake by the ocean over the historical period. Northward transport out of the Southern Ocean is vigorous, reducing the storage to 33 ± 6 Pg anthropogenic carbon and 12 ± 7 *1022J heat in the region. The CMIP5 models as a class tend to underestimate the observational-based global anthropogenic carbon storage, but simulate trends in global ocean heat storage over the last fifty years within uncertainties of observation-based estimates. CMIP5 models suggest global and Southern Ocean CO2 uptake have been largely unaffected by recent climate variability and change. Anthropogenic carbon and heat storage show a common broad-scale pattern of change, but ocean heat storage is more structured than ocean carbon storage. Our results highlight the significance of the Southern Ocean for the global climate and as the region where models differ the most in representation of anthropogenic CO2 and in particular heat uptake.

Earth System Models increasingly include ocean biogeochemistry models in order to predict changes in ocean carbon storage, hypoxia and biological productivity under climate change. However, state-of-the-art ocean biogeochemical models include many advected tracers, that significantly increase the computational resources required, forcing a tradeoff with spatial resolution. Here, we compare a state-of-the art model with 30 prognostic tracers (TOPAZ) with two reduced-tracer models, one with 6 tracers (BLING), the other with 3 tracers (miniBLING). The reduced-tracer models employ parameterized, implicit biological functions, that nonetheless capture many of the most important processes resolved by TOPAZ. All three are embedded in the same coupled climate model. Despite the large difference in tracer number, the absence of tracers for living organic matter is shown to have a minimal impact on the transport of nutrient elements, and the three models produce similar mean annual pre-industrial distributions of macronutrients, oxygen and carbon. Significant differences do exist amongst the models, in particular the seasonal cycle of biomass and export production, but it does not appear that these are necessary consequences of the reduced tracer number. With increasing CO2, changes in dissolved oxygen and anthropogenic carbon uptake are very similar across the different models. Thus, while the reduced-tracer models do not explicitly resolve the diversity and internal dynamics of marine ecosystems, we demonstrate that such models are applicable to a broad suite of major biogeochemical concerns, including anthropogenic change. These results are very promising for the further development and application of reduced-tracer biogeochemical models that incorporate ‘sub-ecosystem-scale' parameterizations.

We characterize impacts on heat in the ocean climate system from transient ocean mesoscale eddies. Our tool is a suite of centennial-scale 1990 radiatively forced numerical climate simulations from three GFDL coupled models comprising the CM2-O model suite. CM2-O models differ in their ocean resolution: CM2.6 uses a 0.1° ocean grid, CM2.5 uses an intermediate grid with 0.25° spacing, and CM2-1deg uses a nominally 1.0° grid. Analysis of the ocean heat budget reveals that mesoscale eddies act to transport heat upward in a manner that partially compensates (or offsets) for the downward heat transport from the time mean currents. Stronger vertical eddy heat transport in CM2.6 relative to CM2.5 accounts for the significantly smaller temperature drift in CM2.6. The mesoscale eddy parameterization used in CM2-1deg also imparts an upward heat transport, yet it differs systematically from that found in CM2.6. This analysis points to the fundamental role that ocean mesoscale features play in transient ocean heat uptake. In general, the more accurate simulation found in CM2.6 provides an argument for either including a rich representation of the ocean mesoscale in model simulations of the mean and transient climate, or for employing parameterizations that faithfully reflect the role of eddies in both lateral and vertical heat transport.

We use a suite of eight ocean biogeochemical/ecological general circulation models from the MAREMIP and CMIP5 archives to explore the relative roles of changes in winds (positive trend of Southern Annular Mode, SAM) and in warming- and freshening-driven trends of upper ocean stratification in altering export production and CO₂ uptake in the Southern Ocean at the end of the 21st century. The investigated models simulate a broad range of responses to climate change, with no agreement on a dominance of either the SAM or the warming signal south of 44 ∘ S. In the southernmost zone, i.e., south of 58∘ S, they concur on an increase of biological export production, while between 44 and 58∘ S the models lack consensus on the sign of change in export. Yet, in both regions, the models show an enhanced CO₂ uptake during spring and summer. This is due to a larger CO₂ (aq) drawdown by the same amount of summer export production at a higher Revelle factor at the end of the 21st century. This strongly increases the importance of the biological carbon pump in the entire Southern Ocean. In the temperate zone, between 30 and 44∘ S all models show a predominance of the warming signal and a nutrient-driven reduction of export production. As a consequence, the share of the regions south of 44∘ S to the total uptake of the Southern Ocean south of 30∘ S is projected to increase at the end of the 21st century from 47 to 66% with a commensurable decrease to the north. Despite this major reorganization of the meridional distribution of the major regions of uptake, the total uptake increases largely in line with the rising atmospheric CO₂. Simulations with the MITgcm-REcoM2 model show that this is mostly driven by the strong increase of atmospheric CO₂, with the climate-driven changes of natural CO₂ exchange offsetting that trend only to a limited degree (∼10%) and with negligible impact of climate effects on anthropogenic CO₂ uptake when integrated over a full annual cycle south of 30∘S.

Reversibility studies suggest a lagged recovery of global mean sea surface temperatures after mitigation, raising the question of whether a similar lag is likely for marine net primary production (NPP). Here we assess NPP reversibility with a mitigation scenario in which projected Representative Concentration Pathway (RCP8.5) forcings are applied out to 2100, and then reversed over the course of the following century in a fully coupled carbon-climate earth system model. In contrast to the temperature lag, we find a rapid increase in global mean NPP, including an overshoot to values above contemporary means. The enhanced NPP arises from a transient imbalance between the cooling surface ocean and continued warming in subsurface waters, which weakens upper ocean density gradients, resulting in deeper mixing and enhanced surface nitrate. We also find a marine ecosystem regime shift as persistent silicate depletion results in increased prevalence of large, non-diatom phytoplankton.

We assess the ability of ocean biogeochemical models to represent seasonal structures in biomass and net community production (NCP) in the Southern Ocean. Two models are compared to observations on daily to seasonal time scales in four different sections of the region. We use daily satellite fields of Chlorophyll (Chl) as a proxy for biomass, and in-situ observations of O2 and Ar supersaturation (ΔO2Ar) to estimate NCP. ΔO2Ar is converted to the flux of biologically generated O2 from sea to air ("O2 bioflux"). All data are aggregated to a climatological year with a daily resolution. To account for potential regional differences within the Southern Ocean, we conduct separate analyses of sections south of South Africa, around the Drake Passage, south of Australia, and south of New Zealand. We find that the models simulate the upper range of Chl concentrations well, underestimate spring levels significantly, and show differences in skill between early and late parts of the growing season. While there is a great deal of scatter in the bioflux observations in general, the four sectors each have distinct patterns that the models pick up. Neither model exhibit a significant distinction between the Australian and New Zealand sectors, and between the Drake Passage and African sectors. South of 60° S, the models fail to predict the observed extent of biological O2 undersaturation. We suggest that this shortcoming may be due either to problems with the ecosystem dynamics or problems with the vertical transport of oxygen. Overall, the bioflux observations are in general agreement with the seasonal structures in satellite chlorophyll, suggesting that this seasonality represent changes in carbon biomass and not Chl : C ratios. This agreement is shared in the models and allows us to interpret the seasonal structure of satellite chlorophyll as qualitatively reflecting the integral of biological production over time for the purposes of model assessment.

The eruption of the Kasatochi volcano in August 2008 stimulated an anomalously high phytoplankton bloom in the otherwise iron-limited subarctic Pacific ocean. It has been proposed that this increased production may have been responsible for record returns of some Pacific salmon stocks in the following years. Here, we investigate the potential effect of volcanic-induced iron fertilization on the entire ecosystem, from phytoplankton through to top predators, using a fully-coupled end-to-end ecosystem model. Our simulations indicate that the volcanic iron fertilization could only stimulate modest increases, at most 10%, in the standing stock biomass of upper trophic level species, including fisheries targets such as Pacific salmon. Propagation of energy to higher trophic levels depends on the timing of the eruption, with more efficient crustaceous zooplankton pathways being favored earlier in the growing season and less-efficient gelatinous zooplankton pathways dominating during later months. However, effects were of modest magnitude for all eruption timings, and the strong level of connectivity within the food web makes the preferential stimulation of a single salmon stock implausible. This adds additional support to evidence suggesting that the Kasatochi eruption did not play a large role in subsequent high salmon returns and questions the value of much smaller-scale artificial fertilization for fisheries. Indeed, the onset of macronutrient limitation coupled with the highly-connected nature of the food web exert strong controls on the fisheries response to even complete removal of iron limitation in the subarctic Pacific.

Past model studies have projected a global decrease in marine net primary production (NPP) over the 21st century, but these studies focused on the multi-model mean and mostly ignored the large inter-model differences. Here, we analyze model simulated changes of NPP for the 21st century under IPCC's high emission scenario RCP8.5 using a suite of nine coupled carbon–climate Earth System Models with embedded marine ecosystem models with a focus on the spread between the different models and the underlying reasons. Globally, five out of the nine models show a decrease in NPP over the course of the 21st century, while three show no significant trend and one even simulates an increase. The largest model spread occurs in the low latitudes (between 30° S and 30° N), with individual models simulating relative changes between −25 and +40%. In this region, the inter-quartile range of the differences between the 2012–2031 average and the 2081–2100 average is up to 3 mol C m-2 yr-1. These large differences in future change mirror large differences in present day NPP. Of the seven models diagnosing a net decrease in NPP in the low latitudes, only three simulate this to be a consequence of the classical interpretation, i.e., a stronger nutrient limitation due to increased stratification and reduced upwelling. In the other four, warming-induced increases in phytoplankton growth outbalance the stronger nutrient limitation. However, temperature-driven increases in grazing and other loss processes cause a net decrease in phytoplankton biomass and reduces NPP despite higher growth rates. One model projects a strong increase in NPP in the low latitudes, caused by an intensification of the microbial loop, while the remaining model simulates changes of less than 0.5%. While there is more consistency in the modeled increase in NPP in the Southern Ocean, the regional inter-model range is also very substantial. In most models, this increase in NPP is driven by temperature, but is also modulated by changes in light, macronutrients and iron as well as grazing. Overall, current projections of future changes in global marine NPP are subject to large uncertainties and necessitate a dedicated and sustained effort to improve the models and the concepts and data that guide their development.

The term river herring collectively refers to alewife (Alosa pseudoharengus) and blueback herring (A. aestivalis), two anadromous fishes distributed along the east coast of North America. Historically, river herring spawning migrations supported important fisheries, and their spawning runs continue to be of cultural significance to many coastal communities. Recently, substantial declines in spawning run size prompted a petition to consider river herring for listing under the Endangered Species Act (ESA). The ESA status review process requires an evaluation of a species' response to multiple stressors, including climate change. For anadromous species that utilize a range of habitats throughout their life cycle, the response to a changing global climate is inherently complex and likely varies regionally. River herring occupy marine habitat for most of their lives, and we demonstrate that their relative abundance in the ocean has been increasing in recent years. We project potential effects of ocean warming along the US Atlantic coast on river herring in two seasons (spring and fall), and two future periods (2020–2060 and 2060–2100) by linking species distribution models to projected temperature changes from global climate models. Our analyses indicate that climate change will likely result in reductions in total suitable habitat across the study region, which will alter the marine distribution of river herring. We also project that density will likely decrease for both species in fall, but may increase in spring. Finally, we demonstrate that river herring may have increased sensitivity to climate change under a low abundance scenario. This result could be an important consideration for resource managers when planning for climate change because establishing effective conservation efforts in the near term may improve population resiliency and provide lasting benefits to river herring populations.

In this study we explore effects of land-use and land-cover change (LULCC) on surface climate using two ensembles of numerical experiments with the Geophysical Fluid Dynamics Laboratory (GFDL) comprehensive Earth System Model ESM2Mb. The experiments simulate historical climate with two different assumptions about LULCC: (1) no land use change with potential vegetation (PV) and (2) with the CMIP5 historical reconstruction of LULCC (LU). We used two different approached in the analysis: (1) we compare differences in LU and PV climates to evaluate the regional and global effects of LULCC, and (2) we characterize sub-grid climate differences among different land-use tiles within each grid cell in the LU experiment. Using the first method, we estimate the magnitude of LULCC effect to be similar to some previous studies. Using the second method we found a pronounced sub-grid signal of LULCC in near-surface temperature over majority of areas affected by LULCC. The signal is strongest on croplands, where it is detectable with 95% confidence over 68.5% of all non-glaciated land grid cells in June-July-August, compared to 8.3% in the first method. In agricultural areas, the sub-grid signal tends to be stronger than LU-PV signal by a factor of 1.3 in tropics in both summer and winter and by 1.5 in extra-tropics in winter. Our analysis for the first time demonstrates and quantifies the local, sub-grid scale LULCC effects with a comprehensive ESM and compares it to previous global and regional approaches.

We review and comment upon some themes in the recent stream of critical commentary on the assertion that “stationarity is dead,” attempting to clear up some misunderstandings; to note points of agreement; to elaborate on matters in dispute; and to share further relevant thoughts. This article is protected by copyright. All rights reserved.

The observed seasonal cycles in atmospheric potential oxygen (APO) at a range of mid to high latitude surface monitoring sites are compared to those inferred from the output of 6 Earth System Models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The simulated air–sea O2 fluxes are translated into APO seasonal cycles using a matrix method that takes into account atmospheric transport model (ATM) uncertainty among 13 different ATMs. Half of the ocean biogeochemistry models tested are able to reproduce the observed APO cycles at most sites, to within the current large ATM uncertainty, while the other half generally are not. Net Primary Production (NPP) and net community production (NCP), as estimated from satellite ocean color data, provide additional constraints, albeit more with respect to the seasonal phasing of ocean model productivity than the overall magnitude. The present analysis suggests that, of the tested ocean biogeochemistry models, CESM and GFDL ESM2M are best able to capture the observed APO seasonal cycle at both Northern and Southern Hemisphere sites. In the northern oceans, the comparison to observed APO suggests that most models tend to underestimate NPP or deep ventilation or both.

Current global inventories of ammonia emissions identify the ocean as the largest natural source. This source depends on seawater pH, temperature, and the concentration of total seawater ammonia (NHx(sw)), which reflects a balance between remineralization of organic matter, uptake by plankton, and nitrification. Here, we compare [NHx(sw)] from two global ocean biogeochemical models (BEC and COBALT) against extensive ocean observations. Simulated [NHx(sw)] are generally biased high. Improved simulation can be achieved in COBALT by increasing the plankton affinity for NHx within observed ranges. The resulting global ocean emissions is 2.5 TgN a−1, much lower than current literature values(7–23 TgN a−1), including the widely used GEIA inventory (8 TgN a−1). Such a weak ocean source implies that continental sources contribute more than half of atmospheric NHx over most of the ocean in the Northern hemisphere. Ammonia emitted from oceanic sources is insufficient to neutralize sulfate aerosol acidity, consistent with observations. There is evidence over the Equatorial Pacific for a missing source of atmospheric ammonia that could be due to photolysis of marine organic nitrogen at the ocean surface or in the atmosphere. Accommodating this possible missing source yields a global ocean emission of ammonia in the range 2–5 TgN a−1, comparable in magnitude to other natural sources from open fires and soils.

The global extent of agriculture demands a thorough understanding of the ways it impacts the Earth system through both the modification of the physical and biological characteristics of the landscape as well as through emissions of greenhouse gases and aerosols. People use fire to manage cropland and pasture in many parts of the world, impacting both the timing and amount of fire. So far, much previous research into how these land uses affect fire regimes has either focused on individual small regions or global patterns at annual or decadal scales. Moreover, because pasture is not mapped globally at high resolution, the amount of fire associated with pasture has never been quantified as it has for cropland. The work presented here resolves the effects of agriculture – including pasture – on fire on a monthly basis for regions across the world, using globally gridded data on fire activity and land use at 0.25° resolution. The first global estimate of pasture-associated fire reveals that it accounts for over 40 % of annual burned area. Cropland, generally assumed to reduce fire occurrence, is shown to enhance or suppress fire at different times of year within individual regions. These results bridge important gaps in the understanding of how agriculture and associated management practices influence vegetation fire, enabling the next generation of vegetation and Earth system models more realistically incorporate these anthropogenic effects.

Upwelling is critical to the biological production, acidification, and deoxygenation of the ocean's major eastern boundary current ecosystems. A leading conceptual hypothesis projects that the winds that induce coastal upwelling will intensify in response to increased land-sea temperature differences associated with anthropogenic global warming. We examine this hypothesis using an ensemble of coupled, ocean–atmosphere models and find limited evidence for intensification of upwelling-favorable winds or atmospheric pressure gradients in response to increasing land-sea temperature differences. However, our analyses reveal consistent latitudinal and seasonal dependence of projected changes in wind intensity associated with poleward migration of major atmospheric high-pressure cells. Summertime winds near poleward boundaries of climatological upwelling zones are projected to intensify, while winds near equatorward boundaries are projected to weaken. Developing a better understanding future changes in upwelling winds is essential to identifying portions of the oceans susceptible to increased hypoxia, ocean acidification, and eutrophication under climate change.

Sea surface temperature (SST) anomalies are often both leading indicators and important drivers of marine resource fluctuations. Assessment of the skill of SST anomaly forecasts within coastal ecosystems accounting for the majority of global fish yields, however, has been minimal. This reflects coarse global forecast system resolution and past emphasis on the predictability of ocean basin-scale SST variations. This paper assesses monthly to inter-annual SST anomaly predictions in coastal “Large Marine Ecosystems” (LMEs). We begin with an analysis of 7 well-observed LMEs adjacent to the United States and then examine how mechanisms responsible for prediction skill in these systems are reflected in predictions for LMEs globally. Historical SST anomaly estimates from the 1/4o daily Optimal Interpolation Sea Surface Temperature reanalysis (OISST.v2) were first found to be highly consistent with in-situ measurements for 6 of the 7 U.S. LMEs. Thirty years of retrospective forecasts from climate forecast systems developed at NOAA’s Geophysical Fluid Dynamics Laboratory (CM2.5-FLOR) and the National Center for Environmental Prediction (CFSv2) were then assessed against OISST.v2. Forecast skill varied widely by LME, initialization month, and lead but there were many cases of high skill that also exceeded that of a persistence forecast, some at leads greater than 6 months. Mechanisms underlying skill above persistence included accurate simulation of a) seasonal transitions between less predictable locally generated and more predictable basin-scale SST variability; b) seasonal transitions between different basin-scale influences; c) propagation of SST anomalies across seasons through sea ice; and d) re-emergence of previous anomalies upon the breakdown of summer stratification. Globally, significant skill above persistence across many tropical systems arises via mechanisms a) and b). Combinations of all four mechanisms contribute to less prevalent but nonetheless significant skill in extratropical systems. While continued refinement of global climate forecast systems and observations are needed to improve coastal SST anomaly prediction and extend predictions to other ecosystem relevant variables (e.g., salinity), present skill warrants close examination of forecasts for marine resource applications.

The abundance of alewife (Alosa pseudoharengus) and blueback herring (Alosa aestivalis) has declined throughout their range, and there are increasing concerns about their conservation status. Because of their diadromous life history, variability in rates of survival in freshwater can affect overall recruitment. The objective of our study was to assess how river temperature and flow influence young of the year (YOY) river herring recruitment in the Northeast US. Observations of adult and juvenile fish in five rivers were used to construct spawner-YOY recruits models; these rivers were chosen because of the length of the time series (>15 years) and the paired observations of spawners and juveniles. An environmentally-explicit stock recruitment model explained a substantial fraction (41 to 80%) of the variance in YOY abundance, depending on river system. Our approach allowed for a preliminary discussion of potential mechanisms, which need to be further substantiated by focused field and laboratory studies. Early summer river flow and river temperature had the greatest influence indicating the importance of conditions in nursery habitats. In certain systems, spring or fall conditions were also important determinants of survival suggesting additional effects of the environment on spawning of adults and juvenile egress from freshwater nursery habitats.

Large and chain-forming diatoms typically dominate the phytoplankton biomass after initiation of coastal upwelling. The ability of these diatoms to accelerate and maintain elevated nitrate uptake rates has been proposed to explain the dominance of diatoms over all other phytoplankton groups. Moreover, the observed delay in biomass accumulation following nitrate supply after initiation of upwelling events has been hypothesised to result from changes in the diatom community structure or from physiological acclimation. To investigate these mechanisms, we used both numerical modelling and experimental incubations that reproduced the characteristic succession from small to large species in phytoplankton community composition and size structure. Using the Tracers Of Phytoplankton with Allometric Zooplankton (TOPAZ) ecosystem model as a framework, we find that variations in functional group-specific traits must be taken into account, through adjustments of group-dependent maximum production rates (P_Cmax, s^{− 1}), in order to accurately reproduce the observed patterns and timescales of size-partitioned new production in a non-steady state environment. Representation of neither nutrient acclimation, nor diatom diversity in the model was necessary as long as lower than theoretical maximum production rates were implemented. We conclude that this physiological feature, P_Cmax, is critical in representing the early, relatively higher specific nitrate uptake rate of large diatoms, and explains the differential success of small and large phytoplankton communities in response to nitrate supply during upwelling.

Modeling the dynamics of marine populations at a global scale - from phytoplankton to fish - is necessary if we are to quantify how climate change and other broad-scale anthropogenic actions affect the supply of marine-based food. Here, we estimate the abundance and distribution of fish biomass using a simple size-based food web model coupled to simulations of global ocean physics and biogeochemistry. We focus on the spatial distribution of biomass, identifying highly productive regions - shelf seas, western boundary currents and major upwelling zones. In the absence of fishing, we estimate the total ocean fish biomass to be View the MathML source∼2.84×109tonnes, similar to previous estimates. However, this value is sensitive to the choice of parameters, and further, allowing fish to move had a profound impact on the spatial distribution of fish biomass and the structure of marine communities. In particular, when movement is implemented the viable range of large predators is greatly increased, and stunted biomass spectra characterizing large ocean regions in simulations without movement, are replaced with expanded spectra that include large predators. These results highlight the importance of considering movement in global-scale ecological models.

Viral lysis of microbial hosts releases organic matter that can then be assimilated by nontargeted microorganisms. Quantitative estimates of virus-mediated recycling of carbon in marine waters, first established in the late 1990s, were originally extrapolated from marine host and virus densities, host carbon content and inferred viral lysis rates. Yet, these estimates did not explicitly incorporate the cascade of complex feedbacks associated with virus-mediated lysis. To evaluate the role of viruses in shaping community structure and ecosystem functioning, we extend dynamic multitrophic ecosystem models to include a virus component, specifically parameterized for processes taking place in the ocean euphotic zone. Crucially, we are able to solve this model analytically, facilitating evaluation of model behavior under many alternative parameterizations. Analyses reveal that the addition of a virus component promotes the emergence of complex communities. In addition, biomass partitioning of the emergent multitrophic community is consistent with well-established empirical norms in the surface oceans. At steady state, ecosystem fluxes can be probed to characterize the effects that viruses have when compared with putative marine surface ecosystems without viruses. The model suggests that ecosystems with viruses will have (1) increased organic matter recycling, (2) reduced transfer to higher trophic levels and (3) increased net primary productivity. These model findings support hypotheses that viruses can have significant stimulatory effects across whole-ecosystem scales. We suggest that existing efforts to predict carbon and nutrient cycling without considering virus effects are likely to miss essential features of marine food webs that regulate global biogeochemical cycles.

The long-term and large scale dynamics of ecosystems are in large part determined by the performances of individual plants in competition with one another for light, water and nutrients. Woody biomass, a pool of carbon (C) larger than 50% of atmospheric CO2, exists because of height-structured competition for light. However, most of the current Earth System Models that predict climate change and C cycle feedbacks lack both a mechanistic formulation for height-structured competition for light and an explicit scaling from individual plants to the globe. In this study, we incorporate height-structured competition and explicit scaling from individuals to ecosystems into the land model (LM3) currently used in the Earth System Models developed by the Geophysical Fluid Dynamics Laboratory (GFDL). The height-structured formulation is based on the Perfect Plasticity Approximation (PPA), which has been shown to accurately scale from individual-level plant competition for light, water and nutrients to the dynamics of whole communities. Because of the tractability of the PPA, the coupled LM3–PPA model is able to include a large number of phenomena across a range of spatial and temporal scales, and still retain computational tractability, as well as close linkages to mathematically tractable forms of the model. We test a range of predictions against data from temperate broadleaved forests in the northern USA. The results show the model predictions agree with diurnal and annual C fluxes, growth rates of individual trees in the canopy and understory, tree size distributions, and species-level population dynamics during succession. We also show how the competitively optimal allocation strategy – the strategy that can competitively exclude all others – shifts as a function of the atmospheric CO2 concentration. This strategy is referred as an evolutionary stable strategy (ESS) in the ecological literature and is typically not the same as a productivity- or growth-maximizing strategy. Model simulations predict that C sinks caused by CO2 fertilization in forests limited by light and water will be down-regulated if allocation tracks changes in the competitive optimum. The implementation of the model in this paper is for temperate broadleaved forest trees, but the formulation of the model is general. It can be expanded to include other growth forms and physiologies simply by altering parameter values.

Eastern Pacific populations of the leatherback turtle (Dermochelys coriacea) have declined by over 90% during the past three decades. The decline is primarily attributed to human pressures, including unsustainable egg harvest, development on nesting beaches, and by-catch mortality. In particular, the effects of climate change may impose additional stress upon already threatened leatherback populations. This study analyzes how the pelagic habitat of Eastern Pacific leatherbacks may be affected by climate change over the next century. This population adheres to a persistent migration pattern; following nesting at Playa Grande, Costa Rica, individuals move rapidly through equatorial currents and into foraging habitat within the oligotrophic South Pacific Gyre. Forty-six nesting females were fitted with satellite tags. Based on the turtle positions, ten environmental variables were sampled along the tracks. Presence/absence habitat models were created to determine the oceanographic characteristics of the preferred turtle habitat. Core pelagic habitat was characterized by relatively low sea surface temperatures and chlorophyll-a. Based on these habitat models, we predicted habitat change using output from the Geophysical Fluid Dynamics Laboratory prototype Earth System Model under the Special Report on Emissions Scenario’s A2 (business-as-usual) scenario. Although the model predicted both habitat losses and gains throughout the region, we estimated that overall the core pelagic habitat of the Eastern Pacific leatherback population will decline by approximately 15 percent within the next century. This habitat modification might increase pressure on a critically endangered population, possibly forcing distributional shifts, behavioral changes, or even extinction.

Understanding how different physical processes can shape the probability distribution function (pdf) of surface temperature, in particular the tails of the distribution, is essential for the attribution and projection of future extreme temperature events. In this study, the contribution of soil moisture-atmosphere interactions to surface temperature pdfs is investigated. Soil moisture represents a key variable in the coupling of the land and atmosphere, since it controls the partitioning of available energy between sensible and latent heat flux at the surface. Consequently, soil moisture variability driven by the atmosphere may feed back on near-surface climate, in particular temperature. In this study, two simulations of the current-generation Geophysical Fluid Dynamics Laboratory (GFDL) earth system model, with and without interactive soil moisture, are analyzed in order to assess how soil moisture dynamics impact the simulated climate. Comparison of these simulations shows that soil moisture dynamics enhance both temperature mean and variance over regional ’hotspots’ of land-atmosphere coupling. Moreover, higher-order distribution moments such as skewness and kurtosis are also significantly impacted, suggesting an asymmetric impact on the positive and negative extremes of the temperature pdf. Such changes are interpreted in the context of altered distributions of the surface turbulent and radiative fluxes. That the moments of the temperature distribution may respond differentially to soil moisture dynamics underscores the importance of analyzing moments beyond the mean and variance to characterize fully the interplay of soil moisture and near surface temperature. In addition, it is shown that soil moisture dynamics impacts daily temperature variability at different time scales over different regions in the model.

We trace the marine biogeochemical silicon (Si) cycle using the stable isotope composition of Si dissolved in seawater (expressed as image). Open ocean image observations indicate a surprisingly strong influence of the physical circulation on the large-scale marine Si distribution. Here, we present an ocean general circulation model simulation that deconvolves the physical and biogeochemical controls on the image distribution in the deep oceanic interior. By parsing dissolved Si into its preformed and regenerated components, we separate the influence of deep water formation and circulation from the effects of biogeochemical cycling related to opal dissolution at depth. We show that the systematic meridional image gradient observed in the deep Atlantic Ocean is primarily determined by the preformed component of Si, whose distribution in the interior is controlled solely by the circulation. We also demonstrate that the image value of the regenerated component of Si in the global deep ocean is dominantly set by oceanic regions where opal export fluxes to the deep ocean are large, i.e. primarily in the Southern Ocean's opal belt. The global importance of this regionally dynamic Si cycling helps explain the observed strong physical control on the oceanic image distribution, since most of the regenerated Si present within the deep Atlantic and Indo-Pacific Oceans is in fact transported into these basins by deep waters flowing northward from the Southern Ocean. Our results thus provide a mechanistic explanation for the observed image distribution that emphasizes the dominant importance of the Southern Ocean in the marine Si cycle.

We examine the oceanic impact of large tropical volcanic eruptions as they appear in ensembles of historical simulations from eight Coupled Model Intercomparison Project Phase 5 models. These models show a response that includes lowering of global average sea surface temperature by 0.1-0.3 K, comparable to the observations. They show enhancement of Arctic ice cover in the years following major volcanic eruptions, with long-lived temperature anomalies extending to the mid-depth and deep ocean on decadal to centennial timescales. Regional ocean responses vary, although there is some consistent hemispheric asymmetry associated with the hemisphere in which the eruption occurs. Temperature decreases and salinity increases contribute to an increase in the density of surface water and an enhancement in the overturning circulation of the North Atlantic Ocean following these eruptions. The strength of this overturning increase varies considerably from model to model and is correlated with the background variability of overturning in each model. Any cause/effect relation between eruptions and the phase of El Niño is weak.

This study aims at evaluating the potential for impacts of ocean acidification on North Atlantic deep-sea ecosystems in response to IPCC AR5 Representative Concentration Pathways (RCP). Deep-sea biota is likely highly vulnerable to changes in seawater chemistry and sensitive to moderate excursions in pH. Here we show, from seven fully-coupled Earth system models, that for three out of four RCPs over 17% of the seafloor area below 500 m depth in the North Atlantic sector will experience pH reductions exceeding −0.2 units by 2100. Increased stratification in response to climate change partially alleviates the impact of ocean acidification on deep benthic environment. We report major potential consequences of pH reductions for deep-sea biodiversity hotspots, such as seamounts and canyons. By 2100 and under the high CO2 scenario RCP8.5 pH reductions exceeding −0.2, (respectively −0.3) units are projected in close to 23% (~ 15%) of North Atlantic deep-sea canyons and ~ 8% (3%) of seamounts – including seamounts proposed as sites of marine protected areas. The spatial pattern of impacts reflects the depth of the pH perturbation and does not scale linearly with atmospheric CO2 concentration. Impacts may cause negative changes of the same magnitude or exceeding the current target of 10% of preservation of marine biomes set by the convention on biological diversity implying that ocean acidification may offset benefits from conservation/management strategies relying on the regulation of resource exploitation.

Connections between the interdecadal variability in North Atlantic temperatures and biological cycling have been widely hypothesized. However, it is unclear whether such connections are due to small changes in basin-averaged temperatures indicated by the Atlantic Multidecadal Oscillation (AMO) Index, or whether both biological cycling and the AMO index are causally linked to changes in the Atlantic Meridional Overturning Circulation (AMOC). We examine interdecadal variability in the annual and month-by-month diatom biomass in two Earth System Models with the same formulations of atmospheric, land, sea ice and ocean biogeochemical dynamics but different formulations of ocean physics and thus different AMOC structure and variability. In the isopycnal-layered ESM2G, strong interdecadal changes in surface salinity associated with changes in AMOC produce spatially heterogeneous variability in convection, nutrient supply and thus diatom biomass. These changes also produce changes in ice cover, shortwave absorption and temperature and hence the AMO Index. Off West Greenland, these changes are consistent with observed changes in fisheries and support climate as a causal driver.. In the level-coordinate ESM2M, nutrient supply is much higher and interdecadal changes in diatom biomass are much smaller in amplitude and not strongly linked to the AMO index.

The strength of feedbacks between a changing climate and future CO2 concentrations are uncertain and difficult to predict using Earth System Models (ESMs). We analyzed emission-driven simulations—in which atmospheric CO2 levels were computed prognostically—for historical (1850–2005) and future periods (RCP 8.5 for 2006–2100) produced by 15 ESMs for the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). Comparison of ESM prognostic atmospheric CO2 over the historical period with observations indicated that ESMs, on average, had a small positive bias in predictions of contemporary atmospheric CO2. Weak ocean carbon uptake in many ESMs contributed to this bias, based on comparisons with observations of ocean and atmospheric anthropogenic carbon inventories. We found a significant linear relationship between contemporary atmospheric CO2 biases and future CO2 levels for the multi-model ensemble. We used this relationship to create a contemporary CO2 tuned model (CCTM) estimate of the atmospheric CO2 trajectory for the 21st century. The CCTM yielded CO2 estimates of 600 ± 14 ppm at 2060 and 947 ± 35 ppm at 2100, which were 21 ppm and 32 ppm below the multi-model mean during these two time periods. Using this emergent constraint approach, the likely ranges of future atmospheric CO2, CO2-induced radiative forcing, and CO2-induced temperature increases for the RCP 8.5 scenario were considerably narrowed compared to estimates from the full ESM ensemble. Our analysis provided evidence that much of the model-to-model variation in projected CO2 during the 21st century was tied to biases that existed during the observational era, and that model differences in the representation of concentration-carbon feedbacks and other slowly changing carbon cycle processes appear to be the primary driver of this variability. By improving models to more closely match the long-term time series of CO2 from Mauna Loa, our analysis suggests uncertainties in future climate projections can be reduced.

Air–sea CO2 fluxes over the Pacific Ocean are known to be characterized by coherent large-scale structures that reflect not only ocean subduction and upwelling patterns, but also the combined effects of wind-driven gas exchange and biology. On the largest scales, a large net CO2 influx into the extratropics is associated with a robust seasonal cycle, and a large net CO2 efflux from the tropics is associated with substantial interannual variability. In this work, we have synthesized estimates of the net air–sea CO2 flux from a variety of products, drawing upon a variety of approaches in three sub-basins of the Pacific Ocean, i.e., the North Pacific extratropics (18–66° N), the tropical Pacific (18° S–18° N), and the South Pacific extratropics (44.5–18° S). These approaches include those based on the measurements of CO2 partial pressure in surface seawater (pCO2sw), inversions of ocean-interior CO2 data, forward ocean biogeochemistry models embedded in the ocean general circulation models (OBGCMs), a model with assimilation of pCO2sw data, and inversions of atmospheric CO2 measurements. Long-term means, interannual variations and mean seasonal variations of the regionally integrated fluxes were compared in each of the sub-basins over the last two decades, spanning the period from 1990 through 2009. A simple average of the long-term mean fluxes obtained with surface water pCO2 diagnostics and those obtained with ocean-interior CO2 inversions are −0.47 ± 0.13 Pg C yr−1 in the North Pacific extratropics, +0.44 ± 0.14 Pg C yr−1 in the tropical Pacific, and −0.37 ± 0.08 Pg C yr−1 in the South Pacific extratropics, where positive fluxes are into the atmosphere. This suggests that approximately half of the CO2 taken up over the North and South Pacific extratropics is released back to the atmosphere from the tropical Pacific. These estimates of the regional fluxes are also supported by the estimates from OBGCMs after adding the riverine CO2 flux, i.e., −0.49 ± 0.02 Pg C yr−1 in the North Pacific extratropics, +0.41 ± 0.05 Pg C yr−1 in the tropical Pacific, and −0.39 ± 0.11 Pg C yr−1 in the South Pacific extratropics. The estimates from the atmospheric CO2 inversions show large variations amongst different inversion systems, but their median fluxes are consistent with the estimates from climatological pCO2sw data and pCO2sw diagnostics. In the South Pacific extratropics, where CO2 variations in the surface and ocean interior are severely undersampled, the difference in the air–sea CO2 flux estimates between the diagnostic models and ocean-interior CO2 inversions is larger (0.18 Pg C yr−1). The range of estimates from forward OBGCMs is also large (−0.19 to −0.72 Pg C yr−1). Regarding interannual variability of air–sea CO2 fluxes, positive and negative anomalies are evident in the tropical Pacific during the cold and warm events of the El Niño–Southern Oscillation in the estimates from pCO2sw diagnostic models and from OBGCMs. They are consistent in phase with the Southern Oscillation Index, but the peak-to-peak amplitudes tend to be higher in OBGCMs (0.40 ± 0.09 Pg C yr−1) than in the diagnostic models (0.27 ± 0.07 Pg C yr−1).

The high mountains of Asia, including the Karakoram, Himalayas and Tibetan Plateau, combine to form a region of perplexing hydroclimate changes. Glaciers have exhibited mass stability or even expansion in the Karakoram region1, 2, 3, contrasting with glacial mass loss across the nearby Himalayas and Tibetan Plateau1, 4, a pattern that has been termed the Karakoram anomaly. However, the remote location, complex terrain and multi-country fabric of high-mountain Asia have made it difficult to maintain longer-term monitoring systems of the meteorological components that may have influenced glacial change. Here we compare a set of high-resolution climate model simulations from 1861 to 2100 with the latest available observations to focus on the distinct seasonal cycles and resulting climate change signatures of Asia’s high-mountain ranges. We find that the Karakoram seasonal cycle is dominated by non-monsoonal winter precipitation, which uniquely protects it from reductions in annual snowfall under climate warming over the twenty-first century. The simulations show that climate change signals are detectable only with long and continuous records, and at specific elevations. Our findings suggest a meteorological mechanism for regional differences in the glacier response to climate warming.

The robustness of Transient Climate Response to cumulative Emissions (TCRE) is tested using an Earth System Model (Geophysical Fluid Dynamics Laboratory-ESM2G) forced with seven different constant rates of carbon emissions (2 GtC/yr to 25 GtC/yr), including low emission rates that have been largely unexplored in previous studies. We find the range of TCRE resulting from varying emission pathways to be 0.76 to 1.04°C/TtC. This range, however, is small compared to the uncertainty resulting from varying model physics across the Fifth Coupled Model Intercomparison Project ensemble. TCRE has a complex relationship with emission rates; TCRE is largest for both low (2 GtC/yr) and high (25 GtC/yr) emissions and smallest for present-day emissions (5–10 GtC/yr). Unforced climate variability hinders precise estimates of TCRE for periods shorter than 50 years for emission rates near or smaller than present day values. Even if carbon emissions would stop, the prior emissions pathways will affect the future climate responses.

Understanding the biophysical mechanisms that shape variability in fisheries recruitment is critical for estimating the effects of climate change on fisheries. In this study, we used an Earth System Model (ESM) and a mechanistic individual-based model (IBM) for larval fish to analyze how climate change may impact the growth and survival of larval cod in the North Atlantic. We focused our analysis on five regions that span the current geographical range of cod and are known to contain important spawning populations. Under the SRES A2 (high emissions) scenario, the ESM-projected surface ocean temperatures are expected to increase by >1 °C for 3 of the 5 regions, and stratification is expected to increase at all sites between 1950–1999 and 2050–2099. This enhanced stratification is projected to decrease large (>5 μm ESD) phytoplankton productivity and mesozooplankton biomass at all 5 sites. Higher temperatures are projected to increase larval metabolic costs, which combined with decreased food resources will reduce larval weight, increase the probability of larvae dying from starvation and increase larval exposure to visual and invertebrate predators at most sites. If current concentrations of piscivore and invertebrate predators are maintained, larval survival is projected to decrease at all five sites by 2050–2099. In contrast to past observed responses to climate variability in which warm anomalies led to better recruitment in cold-water stocks, our simulations indicated that reduced prey availability under climate change may cause a reduction in larval survival despite higher temperatures in these regions. In the lower prey environment projected under climate change, higher metabolic costs due to higher temperatures outweigh the advantages of higher growth potential, leading to negative effects on northern cod stocks. Our results provide an important first large-scale assessment of the impacts of climate change on larval cod in the North Atlantic.

We developed a~process model LM3-TAN to assess the combined effects of direct human influences and climate change on Terrestrial and Aquatic Nitrogen (TAN) cycling. The model was developed by expanding NOAA's Geophysical Fluid Dynamics Laboratory land model LM3V-N of coupled terrestrial carbon and nitrogen (C-N) cycling and including new N cycling processes and inputs such as a~soil denitrification, point N sources to streams (i.e. sewage), and stream transport and microbial processes. Because the model integrates ecological, hydrological, and biogeochemical processes, it captures key controls of transport and fate of N in the vegetation-soil-river system in a comprehensive and consistent framework which is responsive to climatic variations and land use changes. We applied the model at 1/8° resolution for a study of the Susquehanna River basin. We simulated with LM3-TAN stream dissolved organic-N, ammonium-N, and nitrate-N loads throughout the river network, and we evaluated the modeled loads for 1986–2005 using data from 15 monitoring stations as well as a reported budget for the entire basin. By accounting for inter-annual hydrologic variability, the model was able to capture inter-annual variations of stream N loadings. While the model was calibrated with the stream N loads only at the last downstream station Marietta (40.02° N, 76.32° W), it captured the N loads well at multiple locations within the basin with different climate regimes, land use types, and associated N sources and transformations in the sub-basins. Furthermore, the calculated and previously reported N budgets agreed well at the level of the whole Susquehanna watershed. Here we illustrate how point and non-point N sources contribute to the various ecosystems are stored, lost, and exported via the river. Local analysis for 6 sub-basins showed combined effects of land use and climate on the soil denitrification rates, with the highest rates in the Lower Susquehanna sub-basin (extensive agriculture; Atlantic coastal climate) and the lowest rates in the West Branch Susquehanna sub-basin (mostly forest; Great Lakes and Midwest climate). In the re-growing secondary forests, most of the N from non-point sources was stored in the vegetation and soil, but in the agricultural lands most N inputs were removed by soil denitrification indicating that anthropogenic N applications could drive substantial increase of N2O emission, an intermediate of the denitrification process.

Efforts to test and improve terrestrial biosphere models (TBMs) using a variety of data sources have become increasingly common. However, geographically extensive forest inventories have been under-exploited in previous model-data fusion efforts. Inventory observations of forest growth, mortality, and biomass integrate processes across a range of time scales, including slow time-scale processes such as species turnover, that are likely to have important effects on ecosystem responses to environmental variation. However, the large number (thousands) of inventory plots precludes detailed measurements at each location, so that uncertainty in climate, soil properties, and other environmental drivers may be large. Errors in driver variables, if ignored, introduce bias into model-data fusion. We estimated errors in climate and soil drivers at U.S. Forest Inventory and Analysis (FIA) plots, and we explored the effects of these errors on model-data fusion with the Geophysical Fluid Dynamics Laboratory LM3V dynamic global vegetation model. When driver errors were ignored or assumed small at FIA plots, responses of biomass production in LM3V to precipitation and soil available water capacity appeared steeper than the corresponding responses estimated from FIA data. These differences became non-significant if driver errors at FIA plots were assumed large. Ignoring driver errors when optimizing LM3V parameter values yielded estimates for fine-root allocation that were larger than biometric estimates, which is consistent with the expected direction of bias. To explore if complications posed by driver errors could be circumvented by relying on intensive study sites where driver errors are small, we performed a power analysis. To accurately quantify the response of biomass production to spatial variation in mean annual precipitation within the eastern U.S. would require at least 40 intensive study sites, which is larger than the number of sites typically available for individual biomes in existing plot networks. Driver errors may be accommodated by several existing model-data fusion approaches, including hierarchical Bayesian methods and ensemble filtering methods; however, these methods are computationally expensive. We propose a new approach, in which the TBM functional response is fit directly to the driver-error-corrected functional response estimated from data, rather than to the raw observations.

Climate warming threatens to increase mass coral bleaching events, and several studies have projected the demise of tropical coral reefs this century. However, recent evidence indicates corals may be able to respond to thermal stress though adaptive processes (e.g., genetic adaptation, acclimatization, and symbiont shuffling). How these mechanisms might influence warming-induced bleaching remains largely unknown. This study compared how different adaptive processes could affect coral bleaching projections. We used the latest bias-corrected global sea surface temperature (SST) output from the NOAA/GFDL Earth System Model 2 (ESM2M) for the preindustrial period through 2100 to project coral bleaching trajectories. Initial results showed that, in the absence of adaptive processes, application of a preindustrial climatology to the NOAA Coral Reef Watch bleaching prediction method overpredicts the present-day bleaching frequency. This suggests that corals may have already responded adaptively to some warming over the industrial period. We then modified the prediction method so that the bleaching threshold either permanently increased in response to thermal history (e.g., simulating directional genetic selection) or temporarily increased for 2–10 years in response to a bleaching event (e.g., simulating symbiont shuffling). A bleaching threshold that changes relative to the preceding 60 years of thermal history reduced the frequency of mass bleaching events by 20–80% compared with the ‘no adaptive response’ prediction model by 2100, depending on the emissions scenario. When both types of adaptive responses were applied, up to 14% more reef cells avoided high-frequency bleaching by 2100. However, temporary increases in bleaching thresholds alone only delayed the occurrence of high-frequency bleaching by ca. 10 years in all but the lowest emissions scenario. Future research should test the rate and limit of different adaptive responses for coral species across latitudes and ocean basins to determine if and how much corals can respond to increasing thermal stress.

“LM3” is a new model of terrestrial water, energy, and carbon, intended for use in global hydrologic analyses and as a component of earth-system and physical-climate models. It is designed to improve upon the performance and extend the scope of the predecessor Land Dynamics (LaD) and LM3V models, by quantifying better the physical controls of climate and biogeochemistry and by relating more directly to components of the global water system that touch human concerns. LM3 includes multi-layer representations of temperature, liquid-water content, and ice content of both snow pack and macroporous soil/bedrock; topography-based description of saturated area and groundwater discharge; and transport of runoff to the ocean via a global river and lake network. Sensible heat transport by water mass is accounted throughout for a complete energy balance. Carbon and vegetation dynamics and biophysics are represented as in the model LM3V. In numerical experiments, LM3 avoids some of the limitations of the LaD model and provides qualitatively (though not always quantitatively) reasonable estimates, from a global perspective, of observed spatial and/or temporal variations of vegetation density, albedo, streamflow, water-table depth, permafrost, and lake levels. Amplitude and phase of annual cycle of total water storage are simulated well. Realism of modeled lake levels varies widely. The water table tends to be consistently too shallow in humid regions. Biophysical properties have an artificial step-wise spatial structure, and equilibrium vegetation is sensitive to initial conditions. Explicit resolution of thick (>100 m) unsaturated zones and permafrost is possible, but only at the cost of long (>>300 y) model spin-up times.

Organic particles sinking from the sunlit surface are oases of food for heterotrophic bacteria living in the deep ocean. Particle-attached bacteria need to solubilize particles, so they produce exoenzymes that cleave bonds to make molecules small enough to be transported through bacterial cell walls. Releasing exoenzymes, which have an energetic cost, to the external environment is risky because there is no guarantee that products of exoenzyme activity, called hydrolysate, will diffuse to the particleattached bacterium that produced the exoenzymes. Strategies used by particle-attached bacteria to counteract diffusive losses of exoenzymes and hydrolysate are investigated in a water column model. We find that production of exoenzymes by particle-attached bacteria is only energetically worthwhile at high bacterial abundances. Quorum sensing provides the means to determine local abundances, and thus the model results support lab and field studies which found that particle-attached bacteria have the ability to use quorum sensing. Additional model results are that particle-attached bacterial production is sensitive to diffusion of hydrolysate from the particle and is enhanced by as much as 15 times when diffusion of exoenzymes and hydrolysate from particles is reduced by barriers of biofilms and particle-attached bacteria. Bacterial colonization rates and activities on particles in both the euphotic and mesopelagic zones impact remineralization length scales. Shoaling or deepening of the remineralization depth has been shown to exert significant influence on the residence time and concentration of carbon in the atmosphere and ocean. By linking variability in remineralization depths to mechanisms governing bacterial colonization of particles and group coordination of exoenzyme production using a model, we quantitatively connect microscale bacteria-particle interactions to the carbon cycle and provide new insights for future observations.

We examine the response of the American Tropics to changes in Atlantic Meridional Overturning Circulation (AMOC) strength using a set of water-hosing experiments with an Earth system model that explicitly simulates the global and regional carbon cycle. We find that a moderate weakening (27%) of the AMOC, induced by a 0.1 Sv (1 Sv ≡ 106 m3 s-1) freshwater addition in the northern North Atlantic, drives small but statistically significant drying in the South American monsoon region. By contrast, a complete shutdown of the AMOC, induced by a 1.0 Sv freshwater addition, acts to considerably shift the ITCZ southward, which changes the seasonal cycle of precipitation over Amazonia. Our results indicate that AMOC weakening can have a significant impact on the terrestrial primary productivity and carbon storage of the American Tropics.

The Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) marine ecosystem model robustly captures large-scale observed patterns in the flow of carbon through the planktonic food web when embedded within a global ocean-ice simulation. The simulation offers holistic, quantitative, and self-consistent estimates of carbon and energy flows across ocean biomes. Results emphasize the importance of small phytoplankton to global productivity. This leads to widespread carnivorous feeding by mesozooplankton and muted cross-biome differences in annual mean mesozooplankton trophic level. Results also support highly distributed respiration across the planktonic food web. In oceanic upwelling regions, shortened food webs, elevated growth efficiencies, and tight consumer-phytoplankton coupling supports 47% of pelagic mesozooplankton production despite these areas accounting for only 21% of ocean area and 33% of net primary production (NPP). In seasonally stratified regions (40% of ocean area and 36% of NPP), weakened phytoplankton-consumer coupling reduces mesozooplankton production to 39% and enhances export such that it accounts for 55% of the global total. In oligotrophic systems (39% of ocean area and 27% of NPP), the dominance of small phytoplankton and low consumer growth efficiencies support only 15% of mesozooplankton production and 14% of export globally. Bacterial production, in contrast, is maintained in constant proportion to primary production across ecosystems. Further diagnosis of simulations elucidates the mechanisms underlying these cross biome contrasts and regularities. Results herein represent a baseline for further exploration of global-scale planktonic food web dynamics within an increasingly mechanistic dynamic global physical-biological framework.

Pronounced projected 21st century trends in regional oceanic net primary production (NPP) raise the prospect of significant redistributions of marine resources. Recent results further suggest that NPP changes may be amplified at higher trophic levels. Here, we elucidate the role of planktonic food web dynamics in driving projected changes in mesozooplankton production (MESOZP) found to be, on average, twice as large as projected changes in NPP by the latter half of the 21st century under a high emissions scenario. Globally, MESOZP was projected to decline by 7.9% but regional MESOZP changes sometimes exceeded 50%. Changes in three planktonic food web properties – zooplankton growth efficiency (ZGE), the trophic level of mesozooplankton (MESOTL), and the fraction of NPP consumed by zooplankton (zooplankton-phytoplankton coupling, ZPC), were demonstrated to be responsible for the projected amplification. Zooplankton growth efficiencies (ZGE) changed with NPP, amplifying both NPP increases and decreases. Negative amplification (i.e., exacerbation) of projected subtropical NPP declines via this mechanism was particularly strong since consumers in the subtropics already have limited surplus energy above basal metabolic costs. Increased mesozooplankton trophic level (MESOTL) resulted from projected declines in large phytoplankton production, the primary target of herbivorous mesozooplankton. This further amplified negative subtropical NPP declines but was secondary to ZGE and, at higher latitudes, was often offset by increased ZPC. Marked ZPC increases were projected for high latitude regions experiencing shoaling of deep winter mixing or decreased winter sea ice – both tending to increase winter zooplankton biomass and enhance grazer control of spring blooms. Increased ZPC amplified projected NPP increases associated with declining sea ice in the Artic and damped projected NPP declines associated with decreased mixing in the Northwest Atlantic and Southern Ocean. Improved understanding of the complex interactions governing these food web properties is essential to further refine estimates of climate-driven productivity changes across trophic levels.

The sensitivity of soil organic carbon (SOC) to changing environmental conditions represents a critical uncertainty in coupled carbon cycle–climate models1. Much of this uncertainty arises from our limited understanding of the extent to which root–microbe interactions induce SOC losses (through accelerated decomposition or ‘priming’2) or indirectly promote SOC gains (via ‘protection’ through interactions with mineral particles3, 4). We developed a new SOC model to examine priming and protection responses to rising atmospheric CO2. The model captured disparate SOC responses at two temperate free-air CO2 enrichment (FACE) experiments. We show that stabilization of ‘new’ carbon in protected SOC pools may equal or exceed microbial priming of ‘old’ SOC in ecosystems with readily decomposable litter and high clay content (for example, Oak Ridge5). In contrast, carbon losses induced through priming dominate the net SOC response in ecosystems with more resistant litters and lower clay content (for example, Duke6). The SOC model was fully integrated into a global terrestrial carbon cycle model to run global simulations of elevated CO2 effects. Although protected carbon provides an important constraint on priming effects, priming nonetheless reduced SOC storage in the majority of terrestrial areas, partially counterbalancing SOC gains from enhanced ecosystem productivity.

Soil is currently thought to be a sink for carbon; however, the response of this sink to increasing levels of atmospheric carbon dioxide and climate change is uncertain. In this study, we analyzed soil organic carbon (SOC) changes from 11 Earth system models (ESMs) under the historical and high radiative forcing (RCP 8.5) scenarios between 1850 and 2100. We used a reduced complexity model based on temperature and moisture sensitivities to analyze the drivers of SOC losses. ESM estimates of SOC change over the 21st century (2090–2099 minus 1997–2006) ranged from a loss of 72 Pg C to a gain 253 Pg C with a multi-model mean gain of 63 Pg C. All ESMs showed cumulative increases in both NPP (15% to 59%) and decreases in SOC turnover times (15% to 28%) over the 21st century. Most of the model-to-model variation in SOC change was explained by initial SOC stocks combined with the relative changes in soil inputs and decomposition rates (R2 = 0.88, p<0.01). Between models, increases in decomposition rate were well explained by a combination of initial decomposition rate, ESM-specific Q10-factors, and changes in soil temperature (R2 = 0.80, p<0.01). All SOC changes depended on sustained increases in NPP with global change (primarily driven by increasing CO2) and conversion of additional plant inputs into SOC. Most ESMs omit potential constraints on SOC storage, such as priming effects, nutrient availability, mineral surface stabilization and aggregate formation. Future models that represent these constraints are likely to estimate smaller increases in SOC storage during the 21st century.

Global climate change is expected to affect the ocean's biological productivity. The most comprehensive information available about the global distribution of contemporary ocean primary productivity is derived from satellite data. Large spatial patchiness and interannual to multidecadal variability in chlorophyll a concentration challenges efforts to distinguish a global, secular trend given satellite records which are limited in duration and continuity. The longest ocean color satellite record comes from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), which failed in December 2010. The Moderate Resolution Imaging Spectroradiometer (MODIS) ocean color sensors are beyond their originally planned operational lifetime. Successful retrieval of a quality signal from the current Visible Infrared Imager Radiometer Suite (VIIRS) instrument, or successful launch of the Ocean and Land Colour Instrument (OLCI) expected in 2014 will hopefully extend the ocean color time series and increase the potential for detecting trends in ocean productivity in the future. Alternatively, a potential discontinuity in the time series of ocean chlorophyll a, introduced by a change of instrument without overlap and opportunity for cross-calibration, would make trend detection even more challenging. In this paper, we demonstrate that there are a few regions with statistically significant trends over the ten years of SeaWiFS data, but at a global scale the trend is not large enough to be distinguished from noise. We quantify the degree to which red noise (autocorrelation) especially challenges trend detection in these observational time series. We further demonstrate how discontinuities in the time series at various points would affect our ability to detect trends in ocean chlorophyll a. We highlight the importance of maintaining continuous, climate-quality satellite data records for climate-change detection and attribution studies.

Diel vertical migration (DVM) of zooplankton and micronekton is widespread in the ocean and forms a fundamental component of the biological pump, but is generally overlooked in global models of the Earth System. We develop a parameterization of DVM in the ocean and integrate it with a size-structured NPZD model. We assess the model's ability to recreate ecosystem and DVM patterns at three well observed Pacific sites, ALOHA, K2 and EQPAC, and use it to estimate the impact of DVM on marine ecosystems and biogeochemical dynamics. Our model includes: (1) a representation of migration dynamics in response to food availability and light intensity, (2) a representation of the digestive and metabolic processes that decouple zooplankton feeding from excretion, egestion and respiration, and (3) a light-dependent parameterization of visual predation on zooplankton. The model captures the first order patterns in plankton biomass and productivity across the biomes, including the biomass of migrating organisms. We estimate that realistic migratory populations sustain active fluxes to the mesopelagic zone equivalent to between 15 and 40 % the particle export, and contribute up to half of the total respiration within the layers affected by migration. The localized active transport has important consequences for the cycling of oxygen, nutrients and carbon. We highlight the importance of decoupling zooplankton feeding and respiration and excretion with depth for capturing the impact of migration on the redistribution of carbon and nutrients in the upper ocean.

Throughout the ocean, countless small animals swim to depth in the daytime, presumably to seek refuge from large predators. These animals return to the surface at night to feed. This substantial diel vertical migration can result in the transfer of significant amounts of carbon and nutrients from the surface to depth. However, its consequences on ocean chemistry at the global scale have remained uncertain. Here, we determine the depths of these diel migrations in the global ocean using a global array of backscatter data from acoustic Doppler current profilers, collected between 1990 and 2011. We show that the depth of diel migration follows coherent large-scale patterns. We find that migration depth is greater where subsurface oxygen concentrations are high, such that seawater oxygen concentration is the best single predictor of migration depth at the global scale. In oxygen minimum zone areas, migratory animals generally descend as far as the upper margins of the low-oxygen waters. Using an ocean biogeochemical model coupled to a general circulation model, we show that by focusing oxygen consumption in poorly ventilated regions of the upper ocean, diel vertical migration intensifies oxygen depletion in the upper margin of oxygen minimum zones. We suggest that future changes in the extent of oxygen minimum zones could alter the migratory depths of marine organisms, with consequences for marine biogeochemistry, food webs and fisheries.

Ocean ecosystems are increasingly stressed by human-induced changes of their physical, chemical and biological environment. Among these changes, warming, acidification, deoxygenation and changes in primary productivity by marine phytoplankton can be considered as four of the major stressors of open ocean ecosystems. Due to rising atmospheric CO2 in the coming decades, these changes will be amplified. Here, we use the most recent simulations performed in the framework of the Coupled Model Intercomparison Project 5 to assess how these stressors may evolve over the course of the 21st century. The 10 Earth System Models used here project similar trends in ocean warming, acidification, deoxygenation and reduced primary productivity for each of the IPCC's representative concentration parthways (RCP) over the 21st century. For the "business-as-usual" scenario RCP8.5, the model-mean changes in 2090s (compared to 1990s) for sea surface temperature, sea surface pH, global O2 content and integrated primary productivity amount to +2.73 °C, −0.33 pH unit, −3.45% and −8.6%, respectively. For the high mitigation scenario RCP2.6, corresponding changes are +0.71 °C, −0.07 pH unit, −1.81% and −2.0% respectively, illustrating the effectiveness of extreme mitigation strategies. Although these stressors operate globally, they display distinct regional patterns. Large decreases in O2 and in pH are simulated in global ocean intermediate and mode waters, whereas large reductions in primary production are simulated in the tropics and in the North Atlantic. Although temperature and pH projections are robust across models, the same does not hold for projections of sub-surface O2 concentrations in the tropics and global and regional changes in net primary productivity.

Phytoplankton bloom phenology has important consequences for marine ecosystems and fisheries. Recent studies have used remotely-sensed ocean color data to calculate metrics associated with the phenological cycle, such as the phytoplankton bloom initiation date, on the regional and global scale. These metrics are often linked to physical or biological forcings. Most studies choose one of several common methods for calculating bloom initiation, leading to questions about whether bloom initiation datescalculated with different methods yield comparable results. Here, we compare three methods for finding the date of phytoplankton bloom initiation in the North Atlantic: a biomass-based threshold method, a rate of change method, and a cumulative biomass-based threshold method. We use these methods to examine whether the onset of positive ocean-atmosphere heat fluxes coincides with subpolar bloom initiation. In several coherent locations, we find differences in the patterns of bloom initiation created by each method and differences in the synchrony between bloom initiation and positive heat fluxes, that likely indicate various physical processes at play in the study region. We also assess the effect of missing data on the chosen methods.

Changes in temperature, oxygen content and other ocean biogeochemical properties directly affect the ecophysiology of marine water-breathing organisms1–3. Previous studies suggest that the most prominent biological responses are changes in distribution4–6, phenology7,8 and productivity9. Both theory and empirical observations also support the hypothesis that warming and reduced oxygen will reduce body size of marine fishes10–12. However, the extent to which such changes would exacerbate the impacts of climate and ocean changes on global marine ecosystems remains unexplored. Here,we employ a model to examine the integrated biological responses of over 600 species of marine fishes due to changes in distribution, abundance and body size. The model has an explicit representation of ecophysiology, dispersal, distribution, and population dynamics3. We show that assemblage-averaged maximum body weight is expected to shrink by 14–24% globally from 2000 to 2050 under a high-emission scenario. About half of this shrinkage is due to change in distribution and abundance, the remainder to changes in physiology. The tropical and intermediate latitudinal areas will be heavily impacted, with an average reduction of more than 20%. Our results provide a new dimension to understanding the integrated impacts of climate change on marine ecosystems.

Decadal-to-century scale trends for a range of marine environmental variables are investigated using results from seven Earth System Models forced by a high greenhouse gas emission scenario. The models as a class represent the observation-based distribution of the fugacity of oxygen (fO₂) and carbon dioxide (fO₂, and the logarithm of their ratio, i.e. the Respiration Index (RI), albeit major mismatches between observation-based and simulated values remain for individual models. All models project an increase in SST between 2 °C and 3 °C by year 2100, a decrease in upper ocean pH and in the saturation state of water with respect to calcium carbonate minerals, and a decrease in the total ocean inventory of dissolved oxygen by 2% to 4%. Projected fO₂ changes in the thermocline show a complex pattern with both increasing and decreasing trends reflecting the subtle balance of different competing factors such as circulation, production, remineralisation, and temperature changes. Projected changes in the total volume of hypoxic and suboxic waters remain relatively small in all models. A widespread increase of fO₂ in the thermocline is projected. The median of the thermocline fO₂ distribution shifts from 350 μatm in year 1990 to 700–800 μatm in year 2100, primarily as a result of the invasion of anthropogenic carbon from the atmosphere and is responsible for the widespread decrease in the RI outside low oxygen regions. The co-occurrence of changes in a range of environmental variables indicates the need to further investigate their synergistic impacts on marine ecosystems and Earth System feedbacks.

We describe carbon system formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate good climate fidelity as described in Part I while incorporating explicit and consistent carbon dynamics. The two models differ almost exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. On land, both ESMs include a revised land model to simulate competitive vegetation distributions and functioning, including carbon cycling among vegetation, soil and atmosphere. In the ocean, both models include new biogeochemical algorithms including phytoplankton functional group dynamics with flexible stoichiometry. Preindustrial simulations are spun up to give stable, realistic carbon cycle means and variability. Significant differences in simulation characteristics of these two models are described. Due to differences in oceanic ventilation rates (Part I) ESM2M has a stronger biological carbon pump but weaker northward implied atmospheric CO2 transport than ESM2G. The major advantages of ESM2G over ESM2M are: improved representation of surface chlorophyll in the Atlantic and Indian Oceans and thermocline nutrients and oxygen in the North Pacific. Improved tree mortality parameters in ESM2G produced more realistic carbon accumulation in vegetation pools. The major advantages of ESM2M over ESM2G are reduced nutrient and oxygen biases in the Southern and Tropical Oceans.

A fundamental aspect of greenhouse-gas-induced warming is a global-scale increase in absolute humidity 1,2 . Under continued warming, this response has been shown to pose increasingly severe limitations on human activity in tropical and midlatitudes during peak months of heat stress 3 . One heat-stress metric with broad occupational health applications 4–6 is wetbulb globe temperature. We combine wet-bulb globe temperatures from global climate historical reanalysis 7 and Earth System Model (ESM2M) projections 8–10 with industrial 4 and military 5 guidelines for an acclimated individual’s occupational capacity to safely perform sustained labour under environmental heat stress (labour capacity)—here defined as a global population-weighted metric temporally fixed at the 2010 distribution. We estimate that environmental heat stress has reduced labour capacity to 90% in peak months over the past few decades. ESM2M projects labour capacity reduction to 80% in peak months by 2050. Under the highest scenario considered (Representative Concentration Pathway 8.5), ESM2M projects labour capacity reduction to less than 40% by 2200 in peak months, with most tropical and mid-latitudes experiencing extreme climatological heat stress. Uncertainties and caveats associated with these projections include climate sensitivity, climate warming patterns, CO2 emissions, future population distributions, and technological and societal change.

Our understanding of Earth's carbon-climate system depends critically upon interactions between rising atmospheric CO₂, changing land use, and nitrogen limitation on vegetation growth. Using a global land model we show how these factors interact locally to generate the global land carbon sink over the past 200 years. Nitrogen constraints were alleviated by N₂ fixation in the tropics and by atmospheric nitrogen deposition in extra-tropical regions. Non-linear interactions between land-use change and land carbon and nitrogen cycling originated from three major mechanisms: (i) a sink foregone that would have occurred without land-use conversion; (ii) an accelerated response of secondary vegetation to CO₂ and nitrogen, and (iii) a compounded clearance loss from deforestation. Over time, these non-linear effects have become increasingly important and reduce the present-day net carbon sink by ~40% or 0.4 PgC yr^-1.

Two comprehensive Earth System Models, identical apart from their oceanic components, are used to estimate the uncertainty in projections of 21st century sea level rise due to representational choices in ocean physical formulation. Most prominent among the formulation differences is that one (ESM2M) uses a traditional z-coordinate ocean model, while the other (ESM2G) uses an isopycnal-coordinate ocean. As evidence of model fidelity, differences in 20th century global-mean steric sea level rise are not statistically significant between either model and observed trends. However, differences between the two models’ 21st century projections are systematic and both statistically and climatically significant. By 2100, ESM2M exhibits 18% higher global steric sea level rise than ESM2G for all four radiative forcing scenarios (28 to 49 mm higher), despite having similar changes between the models in the near-surface ocean for several scenarios. These differences arise primarily from the vertical extent over which heat is taken up and the total heat uptake by the models (9% more in ESM2M than ESM2G). The fact that the spun-up control state of ESM2M is warmer than ESM2G also contributes, by giving thermal expansion coefficients that are about 7% larger in ESM2M than ESM2G. The differences between these models provide a direct estimate of the sensitivity of 21st century sea level rise to ocean model formulation, and, given the span of these models across the observed volume of the ventilated thermocline, may also approximate the sensitivities expected from uncertainties in the characterization of interior ocean physical processes.

To manage marine ecosystems proactively, it is important to identify species at risk and habitats critical for conservation. Climate change scenarios have predicted an average sea surface temperature (SST) rise of 1–6 °C by 2100 (refs 1, 2), which could affect the distribution and habitat of many marine species. Here we examine top predator distribution and diversity in the light of climate change using a database of 4,300 electronic tags deployed on 23 marine species from the Tagging of Pacific Predators project, and output from a global climate model to 2100. On the basis of models of observed species distribution as a function of SST, chlorophyll a and bathymetry, we project changes in species-specific core habitat and basin-scale patterns of biodiversity. We predict up to a 35% change in core habitat for some species, significant differences in rates and patterns of habitat change across guilds, and a substantial northward displacement of biodiversity across the North Pacific. For already stressed species, increased migration times and loss of pelagic habitat could exacerbate population declines or inhibit recovery. The impending effects of climate change stress the urgency of adaptively managing ecosystems facing multiple threats.

Considerable progress has been made in integrating carbon, nutrient, phytoplankton and zooplankton dynamics into global-scale physical climate models. Scientists are exploring ways to extend the resolution of the biosphere within these Earth system models (ESMs) to include impacts on global distribution and abundance of commercially exploited fish and shellfish. This paper compares different methods for modeling fish and shellfish responses to climate change on global and regional scales. Several different modeling approaches are considered including: direct applications of ESM’s, use of ESM output for estimation of shifts in bioclimatic windows, using ESM outputs to force single- and multi-species stock projection models, and using ESM and physical climate model outputs to force regional bio-physical models of varying complexity and mechanistic resolution. We evaluate the utility of each of these modeling approaches in addressing nine key questions relevant to climate change impacts on living marine resources. No single modeling approach was capable of fully addressing each question. A blend of highly mechanistic and less computationally intensive methods is recommended to gain mechanistic insights and to identify model uncertainties.

An existing Ecopath with Ecosim (EwE) model for the Central North Pacific was updated and modified to focus on the area used by the Hawaii-based pelagic longline fishery. The EwE model was combined with output from a coupled NOAA Geophysical Fluid Dynamics Laboratory climate and biogeochemical model to investigate the likely ecosystem impacts of fishing and climate-induced primary productivity changes. Four simulations were conducted based on 2 fishing effort and climate scenarios from 2010 to 2100. Modeled small and large phytoplankton biomass decreased by 10 % and 20 % respectively, resulting in a 10 % decline in the total biomass of all higher trophic level groups combined. Climate impacts also affected the Hawaii longline fishery, with a 25–29 % reduction in modeled target species yield. Climate impacts on the ecosystem and the fishery were partially mitigated by a drop in fishing effort. Scenarios with a 50 % reduction in fishing effort partially restored longline target species yield to current levels, and decreased longline non-target species yield. These model results suggest that a further reduction in fishery landings mortality over time than the 2010 level may be necessary to mitigate climate impacts and help sustain yields of commercially preferred fish species targeted by the Hawaii longline fishery through the 21st century.

A new framework for understanding the macro-scale variations in spring phenology is developed by using new data from the USA National Phenology Network. Changes in spring budburst for the U.S. are predicted by using Coupled Model Intercomparison Project phase 5 outputs. Macro-scale budburst simulations for the coming century indicate that projected warming leads to earlier budburst by up to 17 days. The latitudinal gradient of budburst becomes less pronounced due to spatially-varying sensitivity of budburst to climate change, even in the most conservative emissions scenarios. Currently existing inter-species differences in budburst date are predicted to become smaller, indicating the potential for secondary impacts at the ecosystem level. We expect that these climate-driven changes in phenology will have large effects on the carbon budget of U.S. forests and these controls should be included in dynamic global vegetation models.

The carbon cycle is a crucial earth system component affecting climate and atmospheric composition. The response of natural carbon uptake to CO2 and climate change will determine anthropogenic emissions compatible with a target CO2 pathway. For CMIP5 4 future Representative Concentration Pathways have been generated by Integrated Assessment Models and used as scenarios by state-of-the-art climate models, enabling quantification of compatible carbon emissions for the 4 scenarios by complex, process-based models. Here we present results from 15 such Earth System GCMs for future changes in land and ocean carbon storage and the implications for anthropogenic emissions. The results are consistent with the underlying scenarios, but show substantial model spread. Uncertainty in land carbon uptake due to differences among models is comparable with the spread across scenarios. Model estimates of historical fossil fuel emissions agree well with reconstructions and future projections for RCP2.6 and RCP4.5 are consistent with the IAMs. For high-end scenarios (6.0 and 8.5) GCMs simulate smaller compatible emissions than the IAMs, indicating a larger climate-carbon cycle feedback in the GCMs in these scenarios. For the RCP2.6 mitigation scenario an average reduction of 50% in emissions by 2050 from 1990 levels is required but with very large model spread (14-96%). The models also disagree on both the requirement for sustained negative emissions to achieve the RCP2.6 CO2 concentration and the success of this scenario to restrict global warming below 2°C. All models agree that the future airborne-fraction depends strongly on the emissions profile with higher airborne-fraction for higher emissions scenarios.

The sea-air biological O2 flux assessed from measurements of surface O2 supersaturation in excess of Ar supersaturation (“O2 bioflux”) is increasingly being used to constrain net community production (NCP) in the upper ocean mixed layer. In making these calculations, one generally assumes that NCP is at steady state, mixed-layer depth is constant, and there is no O2 exchange across the base of the mixed layer. The object of this paper is to evaluate the magnitude of errors introduced by violations of these assumptions. Therefore, we examine the differences between the sea-air biological O2 flux and NCP in the Southern Ocean mixed layer as calculated using two ocean biogeochemistry general circulation models. In this approach, NCP is considered a known entity in the prognostic model, whereas O2 bioflux is estimated using the model-predicted O2/Ar ratio to compute the mixed-layer biological O2 saturation and the gas transfer velocity to calculate flux. We find that the simulated biological O2 flux gives an accurate picture of the regional-scale patterns and trends in model NCP. However, on local scales, violations of the assumptions behind the O2/Ar method lead to significant, non-uniform differences between model NCP and biological O2 flux. These errors arise from two main sources. First, venting of biological O2 to the atmosphere can be misaligned from NCP in both time and space. Second, vertical fluxes of oxygen across the base of the mixed layer complicate the relationship between NCP and the biological O2 flux. Our calculations show that low values of O2 bioflux correctly register that NCP is also low (< 10 mmol m-2 day-1), but fractional errors are large when rates are this low. Values between 10 and 40 mmol m-2 day-1 in areas with intermediate mixed-layer depths of 30 to 50 meters have the smallest absolute and relative errors. Areas with O2 bioflux higher than 30 mmol m-2 d-1 and mixed layers deeper than 40 meters tend to underestimate NCP by up to 20 mmol m-2 d-1. Excluding time periods when mixed-layer biological O2 is undersaturated, O2 bioflux underestimates time-averaged NCP by 5% - 15%. If these time periods are included, O2 bioflux underestimates mixed-layer NCP by 20% - 35% in the Southern Ocean. The higher error estimate is relevant if one wants to estimate seasonal NCP, since a significant amount of biological production takes place when mixed layer biological O2 is undersaturated.

We used an end-to-end ecosystem model that incorporates physics, biogeochemistry, and predator−prey dynamics for the Eastern Subarctic Pacific ecosystem to investigate the factors controlling propagation of changes in primary production to higher trophic levels. We found that lower trophic levels respond to increased primary production in unexpected ways due to complex predatory interactions, with small phytoplankton increasing more than large phytoplankton due to relief from predation by microzooplankton, which are kept in check by the more abundant mesozooplankton. We also found that the propagation of production to upper trophic levels depends critically on how nonpredatory mortality is structured in the model, with much greater propagation occurring with linear mortality and much less with quadratic mortality, both of which functional forms are in common use in eco - system models. We used an ensemble simulation approach to examine how uncertainties in model parameters affect these results. When considering the full range of potential responses to enhanced productivity, the effect of uncertainties related to the functional form of non-predatory mortality was often masked by uncertainties in the food-web parameterization. The predicted responses of several commercially important species, however, were significantly altered by non-predatory mortality assumptions.

The impact of climate warming on the upper layer of the Bering Sea is investigated by using a high-resolution coupled global climate model. The model is forced by increasing atmospheric CO2 at a rate of 1% per year until CO2 reaches double its initial value (after 70 years), after which it is held constant. In response to this forcing, the upper layer of the Bering Sea warms by about 2�C in the southeastern shelf and by a little more than 1�C in the western basin. The wintertime ventilation to the permanent thermocline weakens in the western Bering Sea. After CO2 doubling, the southeastern shelf of the Bering Sea becomes almost ice-free in March, and the stratification of the upper layer strengthens in May and June. Changes of physical condition due to the climate warming would impact the pre-condition of spring bio-productivity in the southeastern shelf.

Interannual chlorophyll variability and its driving mechanisms are evaluated in the eastern subtropical North Atlantic, where elevated surface chlorophyll concentrations regularly extend more than 1500 km into the central subtropical North Atlantic and modulate the areal extent of the North Atlantic's lowest chlorophyll waters. We first characterize the considerable interannual variability in the size of the high chlorophyll region using SeaWiFS satellite data. We then evaluate the relationship between satellite chlorophyll and Sea Surface Height (SSH), which are anticorrelated in the study region, most likely as a result of the inverse relationship between SSH and nutricline depth. To put these results in a longer temporal context, we study a hindcast simulation of a global ocean model with biogeochemistry (GFDL's MOM4.1 with TOPAZ biogeochemistry), after evaluating the model's skill at simulating chlorophyll and SSH relative to observations. In the simulation, the variability seen during the satellite era appears to be imbedded in a much larger multidecadal modulation. The drivers of such variability are assessed by evaluating all the terms in the nutrient budget of the euphotic zone. Because diffusive processes are not a dominant control on nutrient supply, stratification is not a good indicator of nutrient supply. Rather, vertical advection of nutrients, strongly tied to Ekman pumping, is the leading driver of variability in the size of the high chlorophyll region and the productivity within the study area.

Consistently with the past decades observations, CMIP5 Earth System Models project highest acidification rates in subsurface waters. Using 7 ESMs, we find that high acidification rates in mode and intermediate waters (MIW) on centennial timescales (-0.0008 ± 4 × 10^–5 yr^–1 to -0.0023 ± 0.0001 yr^–1 depending on the scenario) are predominantly explained by the geochemical effect of increasing atmospheric CO₂, whereas physical and biological climate change feedbacks explain less than 10% of the simulated changes. MIW are characterized by a larger surface area to volume ratio than deep and bottom waters leading to 5 to 10 times larger carbon uptake. In addition, MIW geochemical properties result in a sensitivity to increasing carbon concentration twice largerthan surface waters (Δ[H+] of +1.2 mmol.m^–3 for every mmol.m^–3 of dissolved carbon in MIW vs. +0.6 in surface waters). Low pH transported by mode and intermediate waters are likely to influence surface pH in upwelling regions decades after their isolation from the atmosphere.

Climate models simulate a wide range of climate changes at high northern latitudes in response to increased CO2. They also have substantial disagreement on projected changes of the Atlantic meridional overturning circulation (AMOC). Here we use two pairs of closely related climate models - each containing members with large and small AMOC declines - to explore the influence of AMOC decline on the high latitude response to increased CO2. The models with larger AMOC decline have less high latitude warming and sea ice decline than their small AMOC decline counterpart. By examining differences in the perturbation heat budget of the 40�90�N region, it is shown that AMOC decline diminishes the warming by weakening poleward ocean heat transport and increasing the ocean heat uptake. The cooling impact of this AMOC forced surface heat flux perturbation difference is enhanced by shortwave feedback and diminished by longwave feedback and atmospheric heat transport differences. The magnitude of the AMOC decline within model pairs is positively related to the magnitudes of control climate AMOC and Labrador Sea convection. Because the 40degree 90degree N region accounts for up to 40% of the simulated global ocean heat uptake over one hundred years, the process described here influences the global heat uptake efficiency.

GLACE-CMIP5 is a multi-model experiment investigating the impact of soil moisture-climate feedbacks in CMIP5 projections. We present here first GLACE-CMIP5 results based on five Earth System Models, focusing on impacts of projected changes in regional soil moisture dryness (mostly increases) on late 21st-century climate. Projected soil moisture changes substantially impact climate in several regions in both boreal and austral summer. Strong and consistent effects are found on temperature, especially for extremes (about 1–1.5 K for mean temperature and 2–2.5 K for extreme daytime temperature). In the Northern Hemisphere, effects on mean and heavy precipitation are also found in most models, but the results are less consistent than for temperature. A direct scaling between soil moisture-induced changes in evaporative cooling and resulting changes in temperature mean and extremes is found in the simulations. In the Mediterranean region, the projected soil moisture changes affect about 25% of the projected changes in extreme temperature.

Previous studies have demonstrated the importance of enhanced vegetation growth under future elevated atmospheric CO2 for 21st century climate warming. Surprisingly no study has completed an analogous assessment for the historical period, during which emissions of greenhouse gases increased rapidly and landuse changes (LUC) dramatically altered terrestrial carbon sources and sinks. Using the Geophysical Fluid Dynamics Laboratory comprehensive Earth System Model ESM2G and a reconstruction of the LUC, we estimate that enhanced vegetation growth has lowered the historical atmospheric CO2 concentration by 85 ppm, avoiding an additional 0.31 ± 0.06 °C warming. We demonstrate that without enhanced vegetation growth the total residual terrestrial carbon flux (i.e., the net land flux minus LUC flux) would be a source of 65–82 Gt of carbon (GtC) to atmosphere instead of the historical residual carbon sink of 186–192 GtC, a carbon saving of 251–274 GtC.

Net Arctic Ocean primary production (PP) is expected to increase over this century, due to less perennial sea ice and more available light, but could decrease depending on changes in nitrate (NO3) supply. Here, CMIP5 simulations performed with 11 Earth System Models are analyzed in terms of PP, surface NO3 and sea ice coverage over 1900-2100. Whereas the mean model simulates reasonably well Arctic-integrated PP (511 TgC/yr, 1998-2005) and projects a mild 58 TgC/yr increase by 2080-2099 for the strongest climate change scenario, models do not agree on the sign of future PP change. However, similar mechanisms operate in all models. The perennial ice loss-driven increase in PP is in most models NO3-limited. The Arctic surface NO3 is decreasing over the 21st century (-2.3  1 mmol/m3), associated with shoaling mixed layer and with decreasing NO3 in the nearby North Atlantic and Pacific waters. However, the inter-model spread in the degree of NO3 limitation is initially high, resulting from >1000 yr spin-up simulations. This initial NO3 spread, combined with the trend, causes a large variation in the timing of oligotrophy onset – which directly controls the sign of future PP change. Virtually all models agree in the open ocean zones on more spatially integrated PP and less PP per unit area. The source of model uncertainty is located in the sea ice zone, where a subtle balance between light and nutrient limitations determines the PP change. Hence, it is argued that reducing uncertainty on present Arctic NO3 in the sea ice zone would render Arctic PP projections much more consistent.

We examine the influence of alternative ocean and atmosphere subcomponents on climate model simulation of transient sensitivities by comparing three GFDL climate models used for the CMIP5. The base model ESM2M is closely related to GFDL's CMIP3 climate model CM2.1, and makes use of a depth coordinate ocean component. The second model, ESM2G, is identical to ESM2M but makes use of an isopycnal coordinate ocean model. We compare the impact of this "ocean swap" with an "atmosphere swap" that produces the CM3 climate model by replacing the AM2 atmosphere with AM3 while retaining a depth coordinate ocean model. The atmosphere swap is found to have much larger influence on sensitivities of global surface temperature and Northern Hemisphere sea ice cover. The atmosphere swap also introduces a multi-decadal response timescale through its indirect influence on heat uptake. Despite significant differences in their interior ocean mean states, the ESM2M and ESM2G simulations of these metrics of climate change are very similar, except for an enhanced high latitude salinity response accompanied by temporarily advancing sea ice in ESM2G. In the ESM2G historical simulation this behavior results in the establishment of a strong halocline in the subpolar North Atlantic during the early 20th century and an associated cooling which are counter to observations in that region. The Atlantic meridional overturning declines comparably in all three models.

Output from an earth system model is paired with a size-based food web model to investigate the effects of climate change on the abundance of large fish over the 21st century. The earth system model, forced by the Intergovernmental Panel on Climate Change (IPCC) Special report on emission scenario A2, combines a coupled climate model with a biogeochemical model including major nutrients, three phytoplankton functional groups, and zooplankton grazing. The size-based food web model includes linkages between two size-structured pelagic communities: primary producers and consumers. Our investigation focuses on seven sites in the North Pacific, each highlighting a specific aspect of projected climate change, and includes top-down ecosystem depletion through fishing. We project declines in large fish abundance ranging from 0 to 75.8% in the central North Pacific and increases of up to 43.0% in the California Current (CC) region over the 21st century in response to change in phytoplankton size structure and direct physiological effects. We find that fish abundance is especially sensitive to projected changes in large phytoplankton density and our model projects changes in the abundance of large fish being of the same order of magnitude as changes in the abundance of large phytoplankton. Thus, studies that address only climate-induced impacts to primary production without including changes to phytoplankton size structure may not adequately project ecosystem responses.

Underestimated rainfall over Amazonia was a common problem for the Coupled Model Intercomparison Project phase 3 (CMIP3) models. We investigate whether it still exists in the CMIP phase 5 (CMIP5) models and, if so, what causes these biases? Our evaluation of historical simulations shows that some models still underestimate rainfall over Amazonia. During the dry season, both convective and large-scale precipitation is underestimated in most models. GFDL-ESM2M and IPSL notably show more pentads with no rainfall. During the wet season, large-scale precipitation is still underestimated in most models. In the dry and transition seasons, models with more realistic moisture convergence and surface evapotranspiration generally have more realistic rainfall totals. In some models, overestimates of rainfall are associated with the adjacent tropical and eastern Pacific ITCZs. However, in other models, too much surface net radiation and a resultant high Bowen ratio appears to cause underestimates of rainfall. During the transition season, low pre-seasonal latent heat, high sensible flux, and a weaker influence of cold air incursions contribute to the dry bias. About half the models can capture, but overestimate, the influences of teleconnection. Based on a simple metric, HadGEM2-ES outperforms other models especially for surface conditions and atmospheric circulation. GFDL-ESM2M has the strongest dry bias presumably due to its overestimate of moisture divergence, induced by overestimated ITCZs in adjacent oceans, and reinforced by positive feedbacks between reduced cloudiness, high Bowen ratio and suppression of rainfall during the dry season, and too weak incursions of extratropical disturbances during the transition season.

Oxygen minimum zones (OMZs) are major sites of fixed nitrogen removal from the open ocean. However, commonly-used gridded data sets such as the World Ocean Atlas (WOA) tend to overestimate the concentration of O2 compared to measurements in grids where O2 falls in the suboxic range (O2 < 2 - 10 mmol/m3), thereby underestimating the extent of O2 depletion in OMZs. We evaluate the distribution of the OMZs by (1) mapping high-quality oxygen measurements from the WOCE program, and (2) by applying an empirical correction to the gridded WOA based on in situ observations. The resulting suboxic volumes are a factor 3 larger than in the uncorrected gridded WOA. We combine the new oxygen data sets with estimates of global export and simple models of remineralization to estimate global denitrification and N2O production. We obtain a removal of fixed nitrogen of 70 {plus minus} 50 Tg/year in the open ocean and 198 {plus minus} 64 Tg/year in the sediments, and a global N2O production of 6.2 {plus minus} 3.2 Tg/year. Our results (1) reconcile water column denitrification rates based on global oxygen distributions with previous estimates based on nitrogen isotopes, (2) revise existing estimates of sediment denitrification down by one-third through the use of spatially-explicit fluxes, and (3) provide independent evidence supporting the idea of a historically-balanced oceanic nitrogen cycle. These estimates are most sensitive to uncertainties in the global export production, the oxygen threshold for suboxic processes, and the efficiency of particle respiration under suboxic conditions. Ocean deoxygenation, an expected response to anthropogenic climate change, could increase denitrification by 14 Tg/year of nitrogen per 1 mmol/m3 of oxygen reduction if uniformly distributed, while leaving N2O production relatively unchanged.

We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory’s previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.

We assess the global balance of calcite export through the water column and burial in sediments as it varies regionally. We first drive a comprehensive 1-D model for sediment calcite preservation with globally gridded field observations and satellite-based syntheses. We then reformulate this model into a simpler five-parameter box model, and combine it with algorithms for surface calcite export and water column dissolution for a single expression for the vertical calcite balance. The resulting metamodel is optimized to fit the observed distributions of calcite burial flux. We quantify the degree to which calcite export, saturation state, organic carbon respiration, and lithogenic sedimentation modulate the burial of calcite. We find that 46% of burial and 88% of dissolution occurs in sediments overlain by undersaturated bottom water with sediment calcite burial strongly modulated by surface export. Relative to organic carbon export, we find surface calcite export skewed geographically toward relatively warm, oligotrophic areas dominated by small, prokaryotic phytoplankton. We assess century-scale projected impacts of warming and acidification on calcite export, finding high sensitive to inferred saturation state controls. With respect to long term glacial cycling, our analysis supports the hypothesis that strong glacial abyssal stratification drives the lysocline towards much closer correspondence with the saturation horizon. Our analysis suggests that, over the transition from interglacial to glacial ocean, a resulting ~0.029 PgC a^-1 decrease in deep Atlantic, Indian and Southern Ocean calcite burial leads to slow increase in ocean alkalinity until Pacific mid-depth calcite burial increases to compensate.

The shift in marine resource management from a compartmentalized approach of dealing with resources on a species basis to an approach based on management of spatially defined ecosystems requires an accurate accounting of energy flow. The flow of energy from primary production through the food web will ultimately limit upper trophic-level fishery yields. In this work, we examine the relationship between yield and several metrics including net primary production, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production. We also evaluate the relationship between yield and two additional rate measures that describe the export of energy from the pelagic food web, particle export flux and mesozooplankton productivity. We found primary production is a poor predictor of global fishery yields for a sample of 52 large marine ecosystems. However, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production were positively associated with yields. The latter two measures provide greater mechanistic insight into factors controlling fishery production than chlorophyll concentration alone. Particle export flux and mesozooplankton productivity were also significantly related to yield on a global basis. Collectively, our analyses suggest that factors related to the export of energy from pelagic food webs are critical to defining patterns of fishery yields. Such trophic patterns are associated with temperature and latitude and hence greater yields are associated with colder, high latitude ecosystems.

Global warming is expected to reduce oxygen solubility and vertical exchange in the ocean, changes which would be expected to result in an increase in the volume of hypoxic waters. A simulation made with a full Earth System model with dynamical atmosphere, ocean, sea ice and biogeochemical cycling (the Geophysical Fluid Dynamics Laboratory’s Earth System Model 2.1) shows that this holds true if the condition for hypoxia is set relatively high. However, the volume of the most hypoxic (i.e., suboxic) waters does not increase under global warming, as these waters actually become more oxygenated. We show that the rise in dissolved oxygen in the tropical Pacific is associated with a drop in ventilation time. A term-by-term analysis within the least oxygenated waters shows an increased supply of dissolved oxygen due to lateral diffusion compensating an increase in remineralization within these highly hypoxic waters. This lateral diffusive flux is the result of an increase of ventilation along the Chilean coast, as a drying of the region under global warming opens up a region of wintertime convection in our model. The results highlight the potential sensitivity of suboxic waters to changes in subtropical ventilation as well as the importance of constraining lateral eddy transport of dissolved oxygen in such waters.

In the Northwest Atlantic Ocean cusk (Brosme brosme) has declined dramatically, primarily as a result of fishing activities. These declines have led to concern about its status, which has prompted reviews under the US Endangered Species Act and the Canadian Species at Risk Act. Changes in distribution and abundance of a number of marine fish in the Northwest Atlantic have been linked to climate variability and change, suggesting that both fishing and climate may affect the status of cusk. Our goal was to evaluate potential effects of climate change on Northwest Atlantic cusk distribution. Coupling a species niche model with the output from an ensemble of climate models, we projected cusk distribution in the future. Our results indicate cusk habitat in the region will shrink and fragment, which is a result of a spatial mismatch between high complexity seafloor habitat and suitable temperature. The importance of habitat patch connectivity for cusk is poorly understood, so the population-level consequences of climate-related habitat fragmentation are uncertain. More broadly, climate change may reduce appropriate thermal habitat and increase habitat fragmentation for other cold-water species in the region; thereby, increasing the potential for regional overexploitation and extirpation.

In temperate regions, the budburst date of deciduous trees is mainly regulated by temperature variation, but the exact nature of the temperature dependence has been a matter of debate. One hypothesis is that budburst date depends purely on the accumulation of warm temperature; a competing hypothesis states that exposure to cold temperatures is also important for budburst. In this study, variability in budburst is evaluated using 15 years of budburst data for 17 tree species at Harvard Forest. We compare two budburst hypotheses through reversible jump Markov Chain Monte Carlo. Then, we investigate how uncertainties in budburst date mapped into uncertainties in ecosystem carbon using GFDL's LM3 land model. For 15 of 17 species, we find that more complicated budburst models that account for a chilling period are favored over simpler models that do not include such dependence. LM3 simulations show that the choice of budburst model induces differences in the timing of carbon uptake commencement of ~11 days, in the magnitude of April-May carbon uptake of ~1.03 g C m^-2 day^-1, and in total ecosystem carbon stocks of ~2 kg C m^-2. While the choice of whether to include a chilling period in the budburst model strongly contributes to this variability, another important factor is how the species-dependent field data gets mapped into LM3's single deciduous plant functional type (PFT). We conclude budburst timing has a strong impact on simulated CO₂ fluxes, and uncertainty in the fluxes can be substantially reduced by improving the model's representation of PFT diversity.

With a more-than-doubling in the atmospheric abundance of the potent greenhouse gas methane (CH₄) since preindustrial times, and indications of renewed growth following a leveling off in recent years, questions arise as to future trends and resulting climate and public health impacts from continued growth without mitigation. Changes in atmospheric methane lifetime are determined by factors which regulate the abundance of OH, the primary methane removal mechanism, including changes in CH₄ itself. We investigate the role of emissions of short-lived species and climate in determining the evolution of tropospheric methane lifetime in a suite of historical (1860�2005) and Representative Concentration Pathway (RCP) simulations (2006�2100), conducted with the Geophysical Fluid Dynamics Laboratory (GFDL) fully coupled chemistry-climate model (CM3). From preindustrial to present, CM3 simulates an overall 5% increase in CH₄ lifetime due to a doubling of the methane burden which offsets coincident increases in nitrogen oxide (NO_x) emissions. Over the last two decades, however, the methane lifetime declines steadily, coinciding with the most rapid climate warming and observed slow-down in CH₄ growth rates, reflecting a possible negative feedback through the CH₄ sink. The aerosol indirect effect plays a significant role in the CM3 climate and thus in the future evolution of the methane lifetime, due to the rapid projected decline of aerosols under all four RCPs. In all scenarios, the methane lifetime decreases (by 5�13%) except for the most extreme warming case (RCP8.5), where it increases by 4% due to the near-doubling of the CH₄ abundance, reflecting a positive feedback on the climate system. In the RCP4.5 scenario changes in short-lived climate forcing agents reinforce climate warming and enhance OH, leading to a more-than-doubling of the decrease in methane lifetime from 2006 to 2100 relative to a simulation in which only well-mixed greenhouse gases are allowed to change along the RCP4.5 scenario (13% vs. 5%) Future work should include process-based studies to better understand and elucidate the individual mechanisms controlling methane lifetime.

We provide a modeling framework that fully couples a one-dimensional physical mixed layer model, a biogeochemical model, and an upper trophic level fisheries model. For validation purposes, the model has been parameterized for the pelagic Eastern Pacific Subarctic Gyre ecosystem. This paper presents a thorough description of the model itself, as well as an ensemble-based parameterization process that allows the model to incorporate the high level of uncertainty associated with many upper trophic level predator-prey processes. Through a series of model architecture experiments, we demonstrate that the use of a consistent functional response for all predator-prey interactions, as well as the use of density-dependent mortality rates for planktonic functional groups, are important factors in reproducing annual and seasonal observations. We present the results of a 50-year climatological simulation, which demonstrates that under contemporary physical forcing, the model is capable of reproducing long-term seasonal dynamics in primary production and biogeochemical cycling, while maintaining steady-state coexistence of upper trophic level functional groups at levels consistent with observations.

Climate modes such as the North Atlantic Oscillation (NAO), representing internal variability of the climate system, influence the ocean carbon cycle and may mask trends in the sink of anthropogenic carbon. Here, utilising control runs of six fully coupled Earth System Models, the response of the ocean carbon cycle to the NAO is quantified. The dominating response, a seesaw pattern between the subtropical gyre and the subpolar Northern Atlantic, is instantaneous (B3 months) and dynamically consistent over all models and with observations for a range of physical and biogeochemical variables. All models show asymmetric responses to NAO and NAO forcing, implying non-linearity in the connection between NAO and the ocean carbon cycle. However, model differences in regional expression and magnitude and conflicting results with regard to airsea flux and CO2 partial pressure remain. Typical NAO-driven variations are 910 mmol/m3 in the surface concentration of dissolved inorganic carbon and alkalinity and 98 ppm in the airsea partial pressure difference. The effect on the basin-wide airsea CO2 flux is small due to compensating fluxes on the sub-basin scale. Two models show a reduced carbon sink in the north-eastern North Atlantic during negative NAO phases, qualitatively in accordance with the observed decline during a phase of predominantly negative NAO. The results indicate that wind-driven dynamics are the main driver of the response to the NAO, which  via vertical mixing, upwelling and the associated entrainment of dissolved inorganic carbon and nutrients  leave an imprint on surface pCO2 and the airsea CO2 flux as well as on biological export production, pH and the calcium carbonate saturation state. The biogeochemical response to the NAO is predominantly governed by vertical exchange between the surface and the thermocline; large-scale horizontal transport mechanisms are of minor importance.

Coral reefs are highly vulnerable to bleaching under elevated temperature. Since 2002, NOAA Coral Reef Watch has used a bleaching threshold based on global sea surface temperatures to provide operational bleaching warnings. Recent studies suggest that modifications to the current global bleaching prediction method may result in higher predictive power. Here, we present a method for comparing four bleaching prediction methods at different spatial and temporal resolutions, each calibrated against the global bleaching observational dataset from ReefBase between 1985 and 2005. We identify one method (“MMMmax”) that consistently gives the highest predictive power at all spatial and temporal resolutions examined. An improved bleaching threshold will refine future bleaching projections under climate change and provide more reliable real-time bleaching alerts to international coral reef managers.

The timing and length of burning seasons in different parts of the world depend on climate, land cover characteristics, and human activities. In this study, global fire data from satellite-based instruments are used in conjunction with global gridded distributions of agricultural land cover types (defined as the sum of cropland and pasture area) to separate the seasonality of agricultural burning practices from that of non-agricultural fire. The results presented in this study show that agricultural and non-agricultural land experience broadly different fire seasonality patterns that are not always linked to climate conditions. We highlight these differences on a regional basis, examining variations in both agricultural land cover and associated cultural practices to help explain our results. While we discuss two land cover categories, the methods can be generalized to derive seasonality for any number of land uses or cover types. This will be useful as global fire models evolve to be fully interactive with land use and land cover change in the next generation of Earth system models.

Assessing the potential impacts of climate change on individual species and populations is essential for the stewardship of ecosystems and biodiversity. Critically endangered leatherback turtles in the eastern Pacific Ocean are excellent candidates for such an assessment because their sensitivity to contemporary climate variability has been substantially studied1, 2, 3, 4. If incidental fisheries mortality is eliminated, this population still faces the challenge of recovery in a rapidly changing climate. Here we combined an Earth system model5, climate model projections assessed by the Intergovernmental Panel on Climate Change6 and a population dynamics model to estimate a 7% per decade decline in the Costa Rica nesting population over the twenty-first century. Whereas changes in ocean conditions had a small effect on the population, the ~2.5 °C warming of the nesting beach was the primary driver of the decline through reduced hatching success and hatchling emergence rate. Hatchling sex ratio did not substantially change. Adjusting nesting phenology or changing nesting sites may not entirely prevent the decline, but could offset the decline rate. However, if future observations show a long-term decline in hatching success and emergence rate, anthropogenic climate mitigation of nests (for example, shading, irrigation)7, 8 may be able to preserve the nesting population.

Egg-burying reptiles need relatively stable temperature and humidity in the substrate surrounding their eggs for successful development and hatchling emergence. Here we show that egg and hatchling mortality of leatherback turtles (Dermochelys coriacea) in northwest Costa Rica were affected by climatic variability (precipitation and air temperature) driven by the El Nin˜o Southern Oscillation (ENSO). Drier and warmer conditions associated with El Nin˜o increased egg and hatchling mortality. The fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC) projects a warming and drying in Central America and other regions of the World, under the SRES A2 development scenario. Using projections from an ensemble of global climate models contributed to the IPCC report, we project that egg and hatchling survival will rapidly decline in the region over the next 100 years by ,50–60%, due to warming and drying in northwestern Costa Rica, threatening the survival of leatherback turtles. Warming and drying trends may also threaten the survival of sea turtles in other areas affected by similar climate changes.

The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the-art multi-model dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC). Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long-term” simulations of 20th century climate and projections for the 21st century and beyond. Conventional atmosphere-ocean global climate models (AOGCMs) and Earth System Models of Intermediate Complexity (EMICs) are for the first time being joined by more recently developed Earth System Models (ESMs) under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the long-term experiments, CMIP5 calls for an entirely new suite of “near-term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, limitations of the models and experiment design are described.

Although there has been considerable research on the impacts of individual changes in water temperature, carbonate chemistry, and other variables on species, cumulative impacts of these effects have rarely been studied. Here, we simulate changes in (i) primary productivity, (ii) species range shifts, (iii) zooplankton community size structure, (iv) ocean acidification, and (v) ocean deoxygenation both individually and together using five Ecopath with Ecosim models of the northeast Pacific Ocean. We used a standardized method to represent climate effects that relied on time-series forcing functions: annual multipliers of species productivity. We focused on changes in fisheries landings, biomass, and ecosystem characteristics (diversity and trophic indices). Fisheries landings generally declined in response to cumulative effects and often to a greater degree than would have been predicted based on individual climate effects, indicating possible synergies. Total biomass of fished and unfished functional groups displayed a decline, though unfished groups were affected less negatively. Some functional groups (e.g. pelagic and demersal invertebrates) were predicted to respond favourably under cumulative effects in some regions. The challenge of predicting climate change impacts must be met if we are to adapt and manage rapidly changing marine ecosystems in the 21st century.

Previous global analyses projected shifts in species distributions and maximum fisheries catch potential across ocean basins by 2050 under the Special Report on Emission Scenarios (SRES) A1B. However, these studies did not account for the effects of changes in ocean biogeochemistry and phytoplankton community structure that affect fish and invertebrate distribution and productivity. This paper uses a dynamic bioclimatic envelope model that incorporates these factors to project distribution and maximum catch potential of 120 species of exploited demersal fish and invertebrates in the Northeast Atlantic. Using projections from the US National Oceanic and Atmospheric Administration's (NOAA) Geophysical Fluid Dynamics Laboratory Earth System Model (ESM2.1) under the SRES A1B, we project an average rate of distribution-centroid shift of 52 km decade−1 northwards and 5.1 m decade−1 deeper from 2005 to 2050. Ocean acidification and reduction in oxygen content reduce growth performance, increase the rate of range shift, and lower the estimated catch potentials (10-year average of 2050 relative to 2005) by 20–30% relative to simulations without considering these factors. Consideration of phytoplankton community structure may further reduce projected catch potentials by ∼10%. These results highlight the sensitivity of marine ecosystems to biogeochemical changes and the need to incorporate likely hypotheses of their biological and ecological effects in assessing climate change impacts.

The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol-cloud interactions, chemistry-climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical-system component of earth-system models and models for decadal prediction in the near-term future, for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud-droplet activation by aerosols, sub-grid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with eco-system dynamics and hydrology. Most basic circulation features in AM3 are simulated as realistically, or more so, than in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks and the intensity distributions of precipitation remain problematic, as in AM2. The last two decades of the 20th century warm in CM3 by .32°C relative to 1881-1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of .56°C and .52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol cloud interactions, and its warming by late 20th century is somewhat less realistic than in CM2.1, which warmed .66°C but did not include aerosol cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud-aerosol interactions to limit greenhouse gas warming in a way that is consistent with observed global temperature changes.

Surface ocean iron speciation is simulated using a time-dependent box-model of lightmediated redox cycling over a range of aeolian inputs of soluble iron in the stratified epipelagic ocean. At steady-state, Dissolved iron (DFe) concentration increases with aeolian input of soluble iron up to 0.1 μmol m^-2 d^-1, and is limited by the solubility of ferric hydroxide at higher fluxes which causes the formation of colloidal iron. We demonstrate that even in the presence of ample excess ligand, rapid conversion of dissolved iron between oxidized and reduced forms in the tropical surface ocean exposes DFe to colloid formation and scavenging. This result provides an explanation for the much smaller range of interregional variability in DFe measurements (0.05-0.4 nM) than soluble Fe fluxes (0.01-1 μmol m^-2 d^-1) and dust fluxes (0.1-10 g m^-2 d^-1) predicted by atmospheric models. We incorporate the critical behavior of the full chemical speciation model into a reduced, computationally efficient model suitable for large scale calculations.

The distribution of radiocarbon (¹⁴C) in the ocean and atmosphere has fluctuated on timescales ranging from seasons to millennia. It is thought that these fluctuations partly reflect variability in the climate system, offering a rich potential source of information to help understand mechanisms of past climate change. Here, a long simulation with a new, coupled model is used to explore the mechanisms that redistribute ¹⁴C within the Earth system on inter-annual to centennial timescales. The model, CM2Mc, is a lower-resolution version of the Geophysical Fluid Dynamics Laboratory's CM2M model, uses no flux adjustments, and incorporates a simple prognostic ocean biogeochemistry model including ¹⁴C. The atmospheric ¹⁴C and radiative boundary conditions are held constant, so that the oceanic distribution of ¹⁴C is only a function of internal climate variability. The simulation displays previously-described relationships between tropical sea surface ¹⁴C and the model-equivalents of the El Niño Southern Oscillation and Indonesian Throughflow. Sea surface ¹⁴C variability also arises from fluctuations in the circulations of the subarctic Pacific and Southern Ocean, including North Pacific decadal variability, and episodic ventilation events in the Weddell Sea that are reminiscent of the Weddell Polynya of 1974–1976. Interannual variability in the air-sea balance of ¹⁴C is dominated by exchange within the belt of intense Southern Westerly winds, rather than at the convective locations where the surface ¹⁴C is most variable. Despite significant interannual variability, the simulated impact on air-sea exchange is an order of magnitude smaller than the recorded atmospheric ¹⁴C variability of the past millennium. This result partly reflects the importance of variability in the production rate of ¹⁴C in determining atmospheric ¹⁴C, but may also reflect an underestimate of natural climate variability, particularly in the Southern Westerly winds.

Processes included in earth system models amplify the impact of climate variability on phytoplankton biomass and, therefore, on upper trophic levels. Models predict much larger relative interannual variability in large phytoplankton biomass compared with total phytoplankton biomass, supporting the goal of better constraining size-structured primary production and biomass from remote sensing. The largest modelled variability in annually averaged large phytoplankton biomass is associated with changes in the areal extent of relatively productive regions. Near the equator, changes in the areal extent of the high-productivity zone are driven by large-scale shifts in nutrient fields, as well as changes in currents. Along the poleward edge of the Subtropical Gyres, changes in physical mixing dominate. Finally, models indicate that high-latitude interannual variability in large phytoplankton biomass is highest during spring. Mechanisms for producing such variability differ across biomes with internal ocean processes, such as convection complicating efforts to link ecosystem variability to climate modes defined using sea surface temperature alone. In salinity-stratified subpolar regions, changes in bloom timing driven by salinity can produce correlations between low surface temperatures and high productivity, supporting the potential importance of using coupled atmosphere–ocean reanalyses, rather than simple forced ocean reanalyses, for attributing past ecosystem shifts.

In preparation for the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), the international community is developing new advanced Earth System Models (ESMs) to assess the combined effects of human activities (e.g. land use and fossil fuel emissions) on the carbon-climate system. In addition, four Representative Concentration Pathway (RCP) scenarios of the future (2005–2100) are being provided by four Integrated Assessment Model (IAM) teams to be used as input to the ESMs for future carbon-climate projections (Moss et al. 2010). The diversity of approaches and requirements among IAMs and ESMs for tracking land-use change, along with the dependence of model projections on land-use history, presents a challenge for effectively passing data between these communities and for smoothly transitioning from the historical estimates to future projections. Here, a harmonized set of land-use scenarios are presented that smoothly connects historical reconstructions of land use with future projections, in the format required by ESMs. The land-use harmonization strategy estimates fractional land-use patterns and underlying land-use transitions annually for the time period 1500–2100 at 0.5° × 0.5° resolution. Inputs include new gridded historical maps of crop and pasture data from HYDE 3.1 for 1500–2005, updated estimates of historical national wood harvest and of shifting cultivation, and future information on crop, pasture, and wood harvest from the IAM implementations of the RCPs for the period 2005–2100. The computational method integrates these multiple data sources, while minimizing differences at the transition between the historical reconstruction ending conditions and IAM initial conditions, and working to preserve the future changes depicted by the IAMs at the grid cell level. This study for the first time harmonizes land-use history data together with future scenario information from multiple IAMs into a single consistent, spatially gridded, set of land-use change scenarios for studies of human impacts on the past, present, and future Earth system.

The second phase of the Global Land-Atmosphere Coupling Experiment (GLACE-2) is a multi-institutional numerical modeling experiment focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the experiment and model behavior at the global scale is described here, along with a determination and characterization of multi-model “consensus” skill. The models show modest but significant skill in predicting air temperatures, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forecast skill is much weaker than that for air temperature. The skill for predicting air temperature, and to some extent precipitation, increases with the magnitude of the initial soil moisture anomaly. GLACE-2 results are examined further to provide insight into the asymmetric impacts of wet and dry soil moisture initialization on skill.

A climate model that includes a coupled ocean biogeochemistry model is used to define large oceanic biomes in the North Pacific Ocean and describe their changes over the 21st century in response to the IPCC Special Report on Emission Scenario A2 future atmospheric CO₂ emissions scenario. Driven by enhanced stratification and a northward shift in the mid-latitude westerlies under climate change, model projections demonstrated that between 2000 and 2100, the area of the subtropical biome expands by ~30% by 2100, whereas the area of temperate and equatorial upwelling (EU) biomes decreases by ~34 and 28%, respectively, by 2100. Over the century, the total biome primary production and fish catch is projected to increase by 26% in the subtropical biome and decrease by 38 and 15% in the temperate and the equatorial biomes, respectively. Although the primary production per unit area declines slightly in the subtropical and the temperate biomes, it increases 17% in the EU biome. Two areas where the subtropical biome boundary exhibits the greatest movement is in the northeast Pacific, where it moves northwards by as much as 1000 km per 100 years and at the equator in the central Pacific, where it moves eastwards by 2000 km per 100 years. Lastly, by the end of the century, there are projected to be more than 25 million km² of water with a mean sea surface temperature of 31°C in the subtropical and EU biomes, representing a new thermal habitat. The projected trends in biome carrying capacity and fish catch suggest resource managers might have to address long-term trends in fishing capacity and quota levels.

The dynamic vegetation and carbon cycling component, LM3V, of the Geophysical Fluid Dynamics Laboratory (GFDL) prototype Earth System Model (ESM2.1), has been designed to simulate the effects of land use on terrestrial carbon pools, including secondary vegetation regrowth. Because of the long time scales associated with the carbon adjustment, special consideration is required when initializing the Earth System Model (ESM) when “historical” simulations are conducted. Starting from an equilibrated, preindustrial climate and potential vegetation state in an “offline” land only model (LM3V), estimates of historical land use are instantaneously applied in five experiments beginning in calendar years: 1500, 1600, 1700, 1750 and 1800. This application results in the land carbon pools experiencing an abrupt change – a “carbon shock”- and the secondary vegetation needs time to regrow into consistency with the harvesting history. We find that it takes approximately 100 years for the vegetation to recover from the carbon shock, while soils take at least 150 years to recover. The vegetation carbon response is driven primarily by land-use history, while the soil carbon response is affected by both land-use history and the geographic pattern of soil respiration rates. Based on these results, we recommend the application of historical land-use scenarios in 1700 to provide sufficient time for the land carbon in ESMs with secondary vegetation to equilibrate to adequately simulate carbon stores at the start of the historical integrations (i.e., 1860) in a computationally efficient manner.

A 1D ecosystem model, driven by surface heat and wind forcing and relaxed toward observed salinity profiles, was applied to simulate the interannual and decadal scale variability of phytoplankton blooms and plankton production from 1984 to 2007 in the Nova Scotian Shelf (NSS) and Gulf of Maine (GoM) region. The model captured the mean observed timing and magnitude of the spring (SPB) and fall phytoplankton bloom (FPB) in both systems, as well as observed interannual variations in SPB peak timing. Model simulations for both the GoM and NSS exhibited marked interannual variability in SPB and FPB timing (±2 to 3 wk) and magnitude (up to ~1 mg chlorophyll m–3). Earlier SPBs and delayed FPBs are linked to enhanced water column stability generated by less saline surface water or sharper salinity gradients over the top 50 m of the water column. The modeled variation in annual primary productivity, mesozooplankton productivity, and particle export flux was modest (<10% of the mean). Years with high primary production were weakly associated with early SPBs (GoM: r = –0.205; NSS: r = –0.51), but there was no significant relationship with water column stability. This suggests that variation in annual productivity in the GoM and NSS reflects a combination of variation in light limitation (which is alleviated by increased water column stability) and nutrient limitation (which is exacerbated by increased water column stability) that offset and are of near equal importance when averaged over the year. Interannual variations in fisheries production due to changes in annual productivity are thus likely secondary to profound shifts in fisheries recruitment and production that have been linked to variations in SPB and FPB timing.

The study of climate impacts on Living Marine Resources (LMRs) has increased rapidly in recent years with the availability of climate model simulations contributed to the assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Collaboration between climate and LMR scientists and shared understanding of critical challenges for such applications are essential for developing robust projections of climate impacts on LMRs. This paper assesses present approaches for generating projections of climate impacts on LMRs using IPCC-class climate models, recommends practices that should be followed for these applications, and identifies priority developments that could improve current projections. Understanding of the climate system and its representation within climate models has progressed to a point where many climate model outputs can now be used effectively to make LMR projections. However, uncertainty in climate model projections (particularly biases and inter-model spread at regional to local scales), coarse climate model resolution, and the uncertainty and potential complexity of the mechanisms underlying the response of LMRs to climate limit the robustness and precision of LMR projections. A variety of techniques including the analysis of multi-model ensembles, bias corrections, and statistical and dynamical downscaling can ameliorate some limitations, though the assumptions underlying these approaches and the sensitivity of results to their application must be assessed for each application. Developments in LMR science that could improve current projections of climate impacts on LMRs include improved understanding of the multi-scale mechanisms that link climate and LMRs and better representations of these mechanisms within more holistic LMR models. These developments require a strong baseline of field and laboratory observations including long time-series and measurements over the broad range of spatial and temporal scales over which LMRs and climate interact. Priority developments for IPCC-class climate models include improved model accuracy (particularly at regional and local scales), inter-annual to decadal-scale predictions, and the continued development of earth system models capable of simulating the evolution of both the physical climate system and biosphere. Efforts to address these issues should occur in parallel and be informed by the continued application of existing climate and LMR models.

The observed acceleration of outlet glaciers and ice flows in Greenland and Antarctica is closely linked to ocean warming, especially in the subsurface layer. Accurate projections of ice-sheet dynamics and global sea-level rise therefore require information of future ocean warming in the vicinity of the large ice sheets. Here we use a set of 19 state-of-the-art climate models to quantify this ocean warming in the next two centuries. We find that in response to a mid-range increase in atmospheric greenhouse-gas concentrations, the subsurface oceans surrounding the two polar ice sheets at depths of 200–500 m warm substantially compared with the observed changes thus far6, 7, 8. Model projections suggest that over the course of the twenty-first century, the maximum ocean warming around Greenland will be almost double the global mean, with a magnitude of 1.7–2.0 °C. By contrast, ocean warming around Antarctica will be only about half as large as global mean warming, with a magnitude of 0.5–0.6 °C. A more detailed evaluation indicates that ocean warming is controlled by different mechanisms around Greenland and Antarctica. We conclude that projected subsurface ocean warming could drive significant increases in ice-mass loss, and heighten the risk of future large sea-level rise.

A simple model of the temperature-dependent biological decay of dissolved oil is embedded in an ocean climate circulation model and used to simulate underwater plumes of dissolved and suspended oil originating from a point source in the northern Gulf of Mexico. Plumes at different source depths are considered and the behavior at each depth is found to be determined by the combination of sheared current strength and vertical profile of decay rate. An upper bound on the supply rate of dissolved and suspended oil is estimated for the interior water column from contemporary analysis of the Deepwater Horizon blowout. For all plume scenarios, toxic levels of dissolved oil are found to remain confined to the northern Gulf of Mexico, and abate within a few weeks after the spill stops. An estimate of oxygen consumption due to microbial oxidation of oil suggests that the presence of oil alone will not lead to hypoxia, but a deep plume of oil and methane (which dissolves readily in water) does lead to localized regions of persistent hypoxia and anoxia in the vicinity of the source.

Laboratory and field studies have revealed that iron has multiple roles in phytoplankton physiology, with particular importance for light-harvesting cellular machinery. However, although iron-limitation is explicitly included in numerous biogeochemical/ecosystem models, its implementation varies, and its effect on the efficiency of light harvesting is often ignored. Given the complexity of the ocean environment, it is difficult to predict the consequences of applying different iron limitation schemes. Here we explore the interaction of iron and nutrient cycles in an ocean general circulation model using a new, streamlined model of ocean biogeochemistry. Building on previously published parameterizations of photoadaptation and export production, the Biogeochemistry with Light Iron Nutrients and Gasses (BLING) model is constructed with only three explicit tracers but including macronutrient and micronutrient limitation, light limitation, and an implicit treatment of community structure. The structural simplicity of this computationally inexpensive model allows us to clearly isolate the global effect that iron availability has on maximum light-saturated photosynthesis rates vs. the effect iron has on photosynthetic efficiency. We find that the effect on light-saturated photosynthesis rates is dominant, negating the importance of photosynthetic efficiency in most regions, especially the cold waters of the Southern Ocean. The primary exceptions to this occur in iron-rich regions of the Northern Hemisphere, where high light-saturated photosynthesis rates allow photosynthetic efficiency to play a more important role. In other words, the ability to efficiently harvest photons has little effect in regions where light-saturated growth rates are low. Additionally, we speculate that the small phytoplankton cells dominating iron-limited regions tend to have relatively high photosynthetic efficiency, due to reduced packaging effects. If this speculation is correct, it would imply that natural communities of iron-stressed phytoplankton may tend to harvest photons more efficiently than would be inferred from iron limitation experiments with larger phytoplankton. We suggest that iron limitation of photosynthetic efficiency has a relatively small impact on global biogeochemistry, though it is expected to impact the seasonal cycle of plankton as well as the vertical structure of primary production.

Global anthropogenic changes in carbon (C) and nitrogen (N) cycles call for modeling tools that are able to address and quantify essential interactions between N, C, and climate in terrestrial ecosystems. Here we introduce a prognostic N cycle within the Princeton–Geophysical Fluid Dynamic Laboratory (GFDL) LM3V land model. The model captures mechanisms essential for N cycling and their feedbacks on C cycling: N limitation of plant productivity, the N dependence of C decomposition and stabilization in soils, removal of available N by competing sinks, ecosystem losses that include dissolved organic and volatile N, and ecosystem inputs through biological N fixation. Our model captures many essential characteristics of C-N interactions and is capable of broadly recreating spatial and temporal variations in N and C dynamics. The introduced N dynamics improve the model's short-term NPP response to step changes in CO2. Consistent with theories of successional dynamics, we find that physical disturbance induces strong C-N feedbacks, caused by intermittent N loss and subsequent N limitation. In contrast, C-N interactions are weak when the coupled model system approaches equilibrium. Thus, at steady state, many simulated features of the carbon cycle, such as primary productivity and carbon inventories, are similar to simulations that do not include C-N feedbacks.

Global climate change is predicted to alter the ocean's biological productivity. But how will we recognise the impacts of climate change on ocean productivity? The most comprehensive information available on its global distribution comes from satellite ocean colour data. Now that over ten years of satellite-derived chlorophyll and productivity data have accumulated, can we begin to detect and attribute climate change-driven trends in productivity? Here we compare recent trends in satellite ocean colour data to longer-term time series from three biogeochemical models (GFDL, IPSL and NCAR). We find that detection of climate change-driven trends in the satellite data is confounded by the relatively short time series and large interannual and decadal variability in productivity. Thus, recent observed changes in chlorophyll, primary production and the size of the oligotrophic gyres cannot be unequivocally attributed to the impact of global climate change. Instead, our analyses suggest that a time series of similar to 40 years length is needed to distinguish a global warming trend from natural variability. In some regions, notably equatorial regions, detection times are predicted to be shorter (similar to 20-30 years). Analysis of modelled chlorophyll and primary production from 2001-2100 suggests that, on average, the climate change-driven trend will not be unambiguously separable from decadal variability until similar to 2055. Because the magnitude of natural variability in chlorophyll and primary production is larger than, or similar to, the global warming trend, a consistent, decades-long data record must be established if the impact of climate change on ocean productivity is to be definitively detected.

Local sea level can deviate from mean global sea level because of both dynamic sea level (DSL) effects, resulting from oceanic and atmospheric circulation and temperature and salinity distributions, and changes in the static equilibrium (SE) sea level configuration, produced by the gravitational, elastic, and rotational effects of mass redistribution. Both effects will contribute to future sea level change. To compare their magnitude, we simulated the effects of Greenland Ice Sheet (GIS) melt by conducting idealized North Atlantic “water-hosing” experiments in a climate model unidirectionally coupled to a SE sea level model. At current rates of GIS melt, we find that geographic SE patterns should be challenging but possible to detect above dynamic variability. At higher melt rates, we find that DSL trends are strongest in the western North Atlantic, while SE effects will dominate in most of the ocean when melt exceeds ~20 cm equivalent sea level.

The second phase of the Global Land-Atmosphere Coupling Experiment (GLACE-2) is aimed at quantifying, with a suite of long-range forecast systems, the degree to which realistic land surface initialization contributes to the skill of subseasonal precipitation and air temperature forecasts. Results, which focus here on North America, show significant contributions to temperature prediction skill out to two months across large portions of the continent. For precipitation forecasts, contributions to skill are much weaker but are still significant out to 45 days in some locations. Skill levels increase markedly when calculations are conditioned on the magnitude of the initial soil moisture anomaly.

Efforts to test and improve terrestrial biosphere models (TBMs) using a variety of data sources have become increasingly common. However, geographically extensive forest inventories have been under-exploited in previous model-data fusion efforts. Inventory observations of forest growth, mortality, and biomass integrate processes across a range of time scales, including slow time-scale processes such as species turnover, that are likely to have important effects on ecosystem responses to environmental variation. However, the large number (thousands) of inventory plots precludes detailed measurements at each location, so that uncertainty in climate, soil properties, and other environmental drivers may be large. Errors in driver variables, if ignored, introduce bias into model-data fusion. We estimated errors in climate and soil drivers at U.S. Forest Inventory and Analysis (FIA) plots, and we explored the effects of these errors on model-data fusion with the Geophysical Fluid Dynamics Laboratory LM3V dynamic global vegetation model. When driver errors were ignored or assumed small at FIA plots, responses of biomass production in LM3V to precipitation and soil available water capacity appeared steeper than the corresponding responses estimated from FIA data. These differences became non-significant if driver errors at FIA plots were assumed large. Ignoring driver errors when optimizing LM3V parameter values yielded estimates for fine-root allocation that were larger than biometric estimates, which is consistent with the expected direction of bias. To explore if complications posed by driver errors could be circumvented by relying on intensive study sites where driver errors are small, we performed a power analysis. To accurately quantify the response of biomass production to spatial variation in mean annual precipitation within the eastern U.S. would require at least 40 intensive study sites, which is larger than the number of sites typically available for individual biomes in existing plot networks. Driver errors may be accommodated by several existing model-data fusion approaches, including hierarchical Bayesian methods and ensemble filtering methods; however, these methods are computationally expensive. We propose a new approach, in which the TBM functional response is fit directly to the driver-error-corrected functional response estimated from data, rather than to the raw observations.

Advances in the science and observation of climate change are providing a clearer understanding of the inherent variability of Earth’s climate system and its likely response to human and natural influences. The implications of climate change for the environment and society will depend not only on the response of the Earth system to changes in radiative forcings, but also on how humankind responds through changes in technology, economies, lifestyle and policy. Extensive uncertainties exist in future forcings of and responses to climate change, necessitating the use of scenarios of the future to explore the potential consequences of different response options. To date, such scenarios have not adequately examined crucial possibilities, such as climate change mitigation and adaptation, and have relied on research processes that slowed the exchange of information among physical, biological and social scientists. Here we describe a new process for creating plausible scenarios to investigate some of the most challenging and important questions about climate change confronting the global community.

A leading hypothesis relating productivity with climate variability in the California Current Ecosystem (CCE) describes an alternation between warmer, well-stratified periods of low productivity and cooler periods of high productivity. This empirical relationship suggests that productivity will decline with global warming. Here, we explore the response of productivity to future climate change in the CCE using an earth system model. This model projects increases in nitrate supply and productivity in the CCE during the 21st century despite increases in stratification and limited change in wind-driven upwelling. We attribute the increased nitrate supply to enrichment of deep source waters entering the CCE resulting from decreased ventilation of the North Pacific. Decreases in dissolved-oxygen concentration and increasing acidification accompany projected increases in nitrate. This analysis illustrates that anthropogenic climate change may be unlike past variability; empirical relationships based on historical observations may be inappropriate for projecting ecosystem responses to future climate change.

The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ 14C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models' ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-a was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-a time series were available.

While nutrient depletion scenarios have long shown that the high-latitude High Nutrient Low Chlorophyll (HNLC) regions are the most effective for sequestering atmospheric carbon dioxide, recent simulations with prognostic biogeochemical models have suggested that only a fraction of the potential drawdown can be realized. We use a global ocean biogeochemical general circulation model developed at GFDL and Princeton to examine this and related issues. We fertilize two patches in the North and Equatorial Pacific, and two additional patches in the Southern Ocean HNLC region north of the biogeochemical divide and in the Ross Sea south of the biogeochemical divide. We evaluate the simulations using observations from both artificial and natural iron fertilization experiments at nearby locations. We obtain by far the greatest response to iron fertilization at the Ross Sea site, where sea ice prevents escape of sequestered CO2 during the wintertime, and the CO2 removed from the surface ocean by the biological pump is carried into the deep ocean by the circulation. As a consequence, CO2 remains sequestered on century time-scales and the efficiency of fertilization remains almost constant no matter how frequently iron is applied as long as it is confined to the growing season. The second most efficient site is in the Southern Ocean. The North Pacific site has lower initial nutrients and thus a lower efficiency. Fertilization of the Equatorial Pacific leads to an expansion of the suboxic zone and a striking increase in denitrification that causes a sharp reduction in overall surface biological export production and CO2 uptake. The impacts on the oxygen distribution and surface biological export are less prominent at other sites, but nevertheless still a source of concern. The century time scale retention of iron in this model greatly increases the long-term biological response to iron addition as compared with simulations in which the added iron is rapidly scavenged from the ocean.

Remotely sensed ocean color data and numerical modeling have been used to study the phenology of both spring and fall phytoplankton blooms (FPBs) in the Nova Scotian Shelf (NSS)–Gulf of Maine (GoM) region. The ocean color data reveal a general pattern of westward progression of the spring phytoplankton bloom (SPB), and an eastward progression of the FPB in the NSS–GoM region. The spatial pattern of mean chlorophyll concentration in spring is similar to that in fall, with a lower concentration in the NSS and higher in the GoM. Interannually, there is a weak but significant tendency for years with earlier (delayed) SPBs to be followed by delayed (earlier) FPBs, but the mean chlorophyll concentrations during SPBs are not correlated with those during FPBs. The interannual variability of SPB timing is significantly correlated with sea surface salinity (SSS), but the FPB timing is correlated with both SSS and sea surface temperature. The process-oriented numerical modeling experiments suggest that (i) salinity is the main factor influencing the bloom timing and magnitude in the NSS–GoM region, especially for the timing of SPBs; (ii) compared to buoyancy forcing induced by vertical salinity gradients, the impact of surface heating and surface wind stress on the blooms variability is much weaker; and (iii) the nutrient level controls the bloom magnitude, but only has a minor effect on bloom timing. This study provides a quantitative estimation of relationship between changes in local/ remote environmental forcing and phytoplankton phenological shifts, thus improving our understanding on the possible impact of climate change on coastal/shelf ecosystems.

An ecosystem model was used to (1) determine the extent to which global trends in the ratio of mesozooplankton production to primary production (referred to herein as the “z-ratio”) can be explained by nutrient enrichment, temperature, and euphotic zone depth, and (2) quantitatively diagnose the mechanisms driving these trends. Equilibrium model solutions were calibrated to observed and empirically derived patterns in phytoplankton biomass and growth rates, mesozooplankton biomass and growth rates, and the fraction of phytoplankton that are large (>5 μm ESD). This constrained several otherwise highly uncertain model parameters. Most notably, half-saturation constants for zooplankton feeding were constrained by the biomass and growth rates of their prey populations, and low zooplankton basal metabolic rates were required to match observations from oligotrophic ecosystems. Calibrated model solutions had no major biases and produced median z-ratios and ranges consistent with estimates. However, much of the variability around the median values in the calibration dataset (72 points) could not be explained. Model results were then compared with an extended global compilation of z-ratio estimates (>10 000 points). This revealed a modest yet significant (r=0.40) increasing trend in z-ratios from values 0.01–0.04 to 0.1–0.2 with increasing primary productivity, with the transition from low to high z-ratios occurring at lower primary productivity in cold-water ecosystems. Two mechanisms, both linked to increasing phytoplankton biomass, were responsible: (1) zooplankton gross growth efficiencies increased as their ingestion rates became much greater than basal metabolic rates and (2) the trophic distance between primary producers and mesozooplankton shortened as primary production shifted toward large phytoplankton. Mechanism (1) was most important during the transition from low to moderate productivity ecosystems and mechanism (2) was responsible for a relatively abrupt transition to values >0.1 in high productivity ecosystems. Substantial z-ratio variations overlying these mean trends remained unexplained by these mechanisms. Potential sources of this variability include zooplankton patchiness, unresolved effects of advection and unsteady dynamics, unresolved shifts in mesozooplankton sizes and species, and unresolved aspects of zooplankton bioenergetics. Comparison of the modeled z-ratio patterns and mechanisms diagnosed herein with those obtained using models with expanded biological dynamics embedded in global circulation models will help further elucidate the causes of this variation.

The unphysical virtual salt flux (VSF) formulation widely used in the ocean component of climate models has the potential to cause systematic and significant biases in modeling the climate system and projecting its future evolution. Here a freshwater flux (FWF) and a virtual salt flux version of the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1) are used to evaluate and quantify the uncertainties induced by the VSF formulation. Both unforced and forced runs with the two model versions are performed and compared in detail. It is found that the differences between the two versions are generally small or statistically insignificant in the unforced control runs and in the runs with a small external forcing. In response to a large external forcing, however, some biases in the VSF version become significant, especially the responses of regional salinity and global sea level. However, many fundamental aspects of the responses differ only quantitatively between the two versions. An unexpected result is the distinctly different ENSO responses. Under a strong external freshwater forcing, the great enhancement of the ENSO variability simulated by the FWF version does not occur in the VSF version and is caused by the overexpansion of the top model layer. In summary, the principle assumption behind using virtual salt flux is not seriously violated and the VSF model has the ability to simulate the current climate and project near-term climate evolution. For some special studies such as a large hosing experiment, however, both the VSF formulation and the use of the FWF in the geopotential coordinate ocean model could have some deficiencies and one should be cautious to avoid them.

A set of state-of-the-science climate models are used to investigate global sea level rise (SLR) patterns induced by ocean dynamics in twenty-first-century climate projections. The identified robust features include bipolar and bihemisphere seesaws in the basin-wide SLR, dipole patterns in the North Atlantic and North Pacific, and a beltlike pattern in the Southern Ocean. The physical and dynamical mechanisms that cause these patterns are investigated in detail using version 2.1 of the Geophysical Fluid Dynamics Laboratory (GFDL) Coupled Model (CM2.1). Under the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario, the steric sea level changes relative to the global mean (the local part) in different ocean basins are attributed to differential heating and salinity changes of various ocean layers and associated physical processes. As a result of these changes, water tends to move from the ocean interior to continental shelves. In the North Atlantic, sea level rises north of the Gulf Stream but falls to the south. The dipole pattern is induced by a weakening of the meridional overturning circulation. This weakening leads to a local steric SLR east of North America, which drives more waters toward the shelf, directly impacting northeastern North America. An opposite dipole occurs in the North Pacific. The dynamic SLR east of Japan is linked to a strong steric effect in the upper ocean and a poleward expansion of the subtropical gyre. In the Southern Ocean, the beltlike pattern is dominated by the baroclinic process during the twenty-first century, while the barotropic response of sea level to wind stress anomalies is significantly delayed.

We present a new methodology for database-driven ecosystem model generation and apply the methodology to the world's 66 currently defined Large Marine Ecosystems. The method relies on a large number of spatial and temporal databases, including FishBase, SeaLifeBase, as well as several other databases developed notably as part of the Sea Around Us project. The models are formulated using the freely available Ecopath with Ecosim (EwE) modeling approach and software. We tune the models by fitting to available time series data, but recognize that the models represent only a first-generation of database-driven ecosystem models. We use the models to obtain a first estimate of fish biomass in the world's LMEs. The biggest hurdles at present to further model development and validation are insufficient time series trend information, and data on spatial fishing effort.

Depth-integrated primary productivity (PP) estimates obtained from satellite ocean color-based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BOGCMs) represent a key resource for biogeochemical and ecological studies at global as well as regional scales. Calibration and validation of these PP models are not straightforward, however, and comparative studies show large differences between model estimates. The goal of this paper is to compare PP estimates obtained from 30 different models (21 SatPPMs and 9 BOGCMs) to a tropical Paci fic PP database consisting of ~1000 ¹⁴C measurements spanning more than a decade (1983–1996). Primary findings include: skill varied significantly between models, but performance was not a function of model complexity or type (i.e. SatPPM vs. BOGCM); nearly all models underestimated the observed variance of PP, specifically yielding too few low PP (<0.2 g Cm^-2 d^-1) values; more than half of the total root-mean-squared model–data differences associated with the satellite-based PP models might be accounted for by uncertainties in the input variables and/or the PP data; and the tropical Pacific database captures a broad scale shift from low biomass normalized productivity in the 1980s to higher biomass-normalized productivity in the 1990s, which was not successfully captured by any of the models. This latter result suggests that interdecadal and global changes will be a significant challenge for both SatPPMs and BOGCMs. Finally, average root-mean-squared differences between in situ PP data on the equator at 140°W and PP estimates from the satellite-based productivity models were 58% lower than analogous values computed in a previous PP model comparison 6 years ago. The success of these types of comparison exercises is illustrated by the continual modification and improvement of the participating models and the resulting increase in model skill.

The interannual to decadal variability in the timing and magnitude of the North Atlantic phytoplankton bloom is examined using a combination of satellite data and output from an ocean biogeochemistry general circulation model. The timing of the bloom as estimated from satellite chlorophyll data is used as a novel metric for validating the model's skill. Maps of bloom timing reveal that the subtropical bloom begins in winter and progresses northward starting in May in subpolar regions. A transition zone, which experiences substantial interannual variability in bloom timing, separates the two regions. Time series of the modeled decadal (1959–2004) variability in bloom timing show no long‐term trend toward earlier or delayed blooms in any of the three regions considered here. However, the timing of the subpolar bloom does show distinct decadal‐scale periodicity, which is found to be correlated with the North Atlantic Oscillation (NAO) index. The mechanism underpinning the relationship is identified as anomalous wind‐driven mixing conditions associated with the NAO. In positive NAO phases, stronger westerly winds result in deeper mixed layers, delaying the start of the subpolar spring bloom by 2–3 weeks. The subpolar region also expands during positive phases, pushing the transition zone further south in the central North Atlantic. The magnitude of the bloom is found to be only weakly dependent on bloom timing, but is more strongly correlated with mixed layer depth. The extensive interannual variability in the timing of the bloom, particularly in the transition region, is expected to strongly impact the availability of food to higher trophic levels.

Assessing the skill of biogeochemical models to hindcast past variability is challenging, yet vital in order to assess their ability to predict biogeochemical change. However, the validation of decadal variability is limited by the sparsity of consistent, long-term biological datasets. The Phytoplankton Colour Index (PCI) product from the Continuous Plankton Recorder survey, which has been sampling the North Atlantic since 1948, is an example of such a dataset. Converting the PCI to chlorophyll values using SeaWiFS data allows a direct comparison with model output. Here we validate decadal variability in chlorophyll from the GFDL TOPAZ model. The model demonstrates skill at reproducing interannual variability, but cannot simulate the regime shifts evident in the PCI data. Comparison of the model output, data and climate indices highlights under-represented processes that it may be necessary to include in future biogeochemical models in order to accurately simulate decadal variability in ocean ecosystems.

A new field of study, “decadal prediction,” is emerging in climate science. Decadal prediction lies between seasonal/interannual forecasting and longer-term climate change projections, and focuses on time-evolving regional climate conditions over the next 10–30 yr. Numerous assessments of climate information user needs have identified this time scale as being important to infrastructure planners, water resource managers, and many others. It is central to the information portfolio required to adapt effectively to and through climatic changes. At least three factors influence time-evolving regional climate at the decadal time scale: 1) climate change commitment (further warming as the coupled climate system comes into adjustment with increases of greenhouse gases that have already occurred), 2) external forcing, particularly from future increases of greenhouse gases and recovery of the ozone hole, and 3) internally generated variability. Some decadal prediction skill has been demonstrated to arise from the first two of these factors, and there is evidence that initialized coupled climate models can capture mechanisms of internally generated decadal climate variations, thus increasing predictive skill globally and particularly regionally. Several methods have been proposed for initializing global coupled climate models for decadal predictions, all of which involve global time-evolving three-dimensional ocean data, including temperature and salinity. An experimental framework to address decadal predictability/prediction is described in this paper and has been incorporated into the coordinated Coupled Model Intercomparison Model, phase 5 (CMIP5) experiments, some of which will be assessed for the IPCC Fifth Assessment Report (AR5). These experiments will likely guide work in this emerging field over the next 5 yr.

Here we use observations and ocean models to identify mechanisms driving large seasonal to interannual variations in dissolved inorganic carbon (DIC) and dissolved oxygen (O₂) in the upper ocean. We begin with observations linking variations in upper ocean DIC and O₂ inventories with changes in the physical state of the ocean. Models are subsequently used to address the extent to which the relationships derived from short-timescale (6 months to 2 years) repeat measurements are representative of variations over larger spatial and temporal scales. The main new result is that convergence and divergence (column stretching) attributed to baroclinic Rossby waves can make a first-order contribution to DIC and O₂ variability in the upper ocean. This results in a close correspondence between natural variations in DIC and O₂ column inventory variations and sea surface height (SSH) variations over much of the ocean. Oceanic Rossby wave activity is an intrinsic part of the natural variability in the climate system and is elevated even in the absence of significant interannual variability in climate mode indices. The close correspondence between SSH and both DIC and O₂ column inventories for many regions suggests that SSH changes (inferred from satellite altimetry) may prove useful in reducing uncertainty in separating natural and anthropogenic DIC signals (using measurements from Climate Variability and Predictability's CO₂/Repeat Hydrography program). Correction: 10.1029/2009JC005835

We have developed a dynamic land model (LM3V) able to simulate ecosystem dynamics and exchanges of water, energy, and CO2 between land and atmosphere. LM3V is specifically designed to address the consequences of land use and land management changes including cropland and pasture dynamics, shifting cultivation, logging, fire, and resulting patterns of secondary regrowth. Here we analyze the behavior of LM3V, forced with the output from the Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric model AM2, observed precipitation data, and four historic scenarios of land use change for 1700–2000. Our analysis suggests a net terrestrial carbon source due to land use activities from 1.1 to 1.3 GtC/a during the 1990s, where the range is due to the difference in the historic cropland distribution. This magnitude is substantially smaller than previous estimates from other models, largely due to our estimates of a secondary vegetation sink of 0.35 to 0.6 GtC/a in the 1990s and decelerating agricultural land clearing since the 1960s. For the 1990s, our estimates for the pastures' carbon flux vary from a source of 0.37 to a sink of 0.15 GtC/a, and for the croplands our model shows a carbon source of 0.6 to 0.9 GtC/a. Our process-based model suggests a smaller net deforestation source than earlier bookkeeping models because it accounts for decelerated net conversion of primary forest to agriculture and for stronger secondary vegetation regrowth in tropical regions. The overall uncertainty is likely to be higher than the range reported here because of uncertainty in the biomass recovery under changing ambient conditions, including atmospheric CO2 concentration, nutrients availability, and climate.

Sulfate aerosols resulting from strong volcanic explosions last for 2–3 years in the lower stratosphere. Therefore it was traditionally believed that volcanic impacts produce mainly short-term, transient climate perturbations. However, the ocean integrates volcanic radiative cooling and responds over a wide range of time scales. The associated processes, especially ocean heat uptake, play a key role in ongoing climate change. However, they are not well constrained by observations, and attempts to simulate them in current climate models used for climate predictions yield a range of uncertainty. Volcanic impacts on the ocean provide an independent means of assessing these processes. This study focuses on quantification of the seasonal to multidecadal time scale response of the ocean to explosive volcanism. It employs the coupled climate model CM2.1, developed recently at the National Oceanic and Atmospheric Administration's Geophysical Fluid Dynamics Laboratory, to simulate the response to the 1991 Pinatubo and the 1815 Tambora eruptions, which were the largest in the 20th and 19th centuries, respectively. The simulated climate perturbations compare well with available observations for the Pinatubo period. The stronger Tambora forcing produces responses with higher signal-to-noise ratio. Volcanic cooling tends to strengthen the Atlantic meridional overturning circulation. Sea ice extent appears to be sensitive to volcanic forcing, especially during the warm season. Because of the extremely long relaxation time of ocean subsurface temperature and sea level, the perturbations caused by the Tambora eruption could have lasted well into the 20th century.nd sea level, the perturbations caused by the Tambora eruption could last well into the 20th century.

Human-induced climate change is expected to cause sea-level rise globally as well as regionally. An analysis of state-of-the-art climate models indicates that the northeastern US coast is particularly likely to experience substantial rises in regional sea level as a result of the projected slowdown of the Atlantic meridional overturning circulation.

The east lobe of Lake Bonney, a permanently ice-covered lake in the McMurdo Dry Valleys, Antarctica, has a mid-depth maximum N₂O concentration of 43.3 µmol N L^-1 (>700,000% saturation with respect to air), representing one of the highest concentrations reported for a natural aquatic system. ¹⁵N and ¹⁸O measurements indicate that this is the most isotopically depleted N₂O yet observed in a natural environment (minimum ¹⁵N-N₂O of -79.6‰ vs. air-N₂; minimum ¹⁸O-N₂O of -4.7‰ vs. Vienna standard mean ocean water), providing new end points for these parameters in natural systems. The extremely depleted nitrogen and oxygen isotopes, together with nitrogen isotopic isomer data for N₂O, imply that most of the N₂O was produced via incomplete nitrification and has undergone virtually no subsequent consumption. However, molecular evidence provides little support for metabolically active nitrifying populations at depths where the maximal N₂O concentrations occur and contemporary biogeochemical reactions cannot explain the extreme excesses of N₂O in Lake Bonney. The gas appears to be a legacy of past biogeochemical conditions within the lake, and in the absence of a significant sink and the presence of a highly stable water column, gradients in N₂O produced by past microbial activity could persist in the cold saline waters of Lake Bonney for >10⁴ years.

The chemical characteristics of aggregating material in the marine environment are largely unknown. We investigated neutral aldose (NA) abundance and composition in aggregation of marine snow and other organic matter (OM) size fractions in the field. Four sample sets were fractionated using membrane filtration and ultrafiltration into the following size fractions: particulate material, high-molecular-weight (HMW) material, and low-molecular-weight (LMW) material. We also collected three sample sets of marine-snow aggregates. Each sample set contained small, medium, and large aggregate size fractions and each size fraction consisted of 25–50 aggregates. For 7 marine-snow samples and for each water-sample size fraction, we determined monomeric and polymeric NA concentration, NA yield (amount of NA-C normalized to organic carbon), and composition; total organic carbon (TOC) concentration; transparent exopolymer particles (TEP) concentration, and TEP propensity (TEP concentration after inducing TEP formation in filtered samples). This is the first study to include compound-specific NA determinations on these four marine OM size fractions. The mass balances of organic carbon and NA indicated that there were no serious contamination or loss problems. Concentrations, yields, and NA mol fractions in water samples were similar to results from other studies. Glucose and galactose had the highest relative abundance in all size fractions. The NA yield increased with increasing molecular weight or particle size for all fractions except marine snow. The NA yield increased in the order: LMW< marine snow< HMW< particles. Marine snow had a higher average NA yield than the LMW fraction, but lower than particle and HMW-fractions. This indicates that OM in marine snow could have been diagenetically derived from particulate and HMW-fractions, that is, marine snow may include material from the particulate and the colloidal phase. TEP concentration or TEP propensity was positively correlated with concentrations of all individual NAs as well as the sum NA concentrations, indicating that TEP contains neutral sugars in addition to the acidic polysaccharides stained in the determination of TEP concentrations. Despite the relatively low NA yield in marine snow, marine snow was enriched in NA when compared with seawater, with enrichment factors of 34–225 (average 125). By combining data from this study with data from other studies, we estimate that < 10% of carbohydrates in marine snow comprise NAs. There was no clear correlation between marine-snow aggregate size and NA yield, that is, there appears to be no general age difference between small and large marine-snow aggregates. NA composition was similar among different marine-snow size fracions collected during the same day, indicating that aggregation/disaggregation reactions resulted in homogenizing NA composition in marine-snow aggregates of all sizes. The NA composition of marine snow was different from that of other OM size fractions, indicating either that bacterial degradation has modified the composition of marine snow to a larger extent than other OM size fractions or that marine snow is formed through the aggregation of selected subcomponents of OM.

A size-structured plankton dynamics model is developed and used to explore the effects of variations in bottom-up and top-down forcing upon the biomass spectrum, size-structured patterns in primary production, and the flux of energy from primary producers to fish. Parameters and mechanisms controlling the steady-state model response to bottom-up forcing via nutrient enrichment and top-down forcing via fluctuations in planktivorous fish are first diagnosed. Results are then compared with mean observed biomass spectra from three ecosystems spanning a broad range of productivity. Solutions using parameters within empirical ranges can recreate trends in the biomass spectrum across these systems. The zooplankton gross growth efficiency is critical for matching the steady-state slopes of the spectra. Variability in export sources and zooplankton half-saturation constants both provide ways of matching the mean biomass. Results support the model's potential to provide mechanistic insights and testable quantitative hypotheses for the dynamics underlying observed biomass spectra.