Catalano, Katrina A., Elizabeth J Drenkard, Enrique N Curchitser, Allison C Dedrick, Michelle R Stuart, Humberto R Montes Jr, and Malin L Pinsky, October 2024: The contribution of nearshore oceanography to temporal variation in larval dispersal. Ecology, 105(10), DOI:10.1002/ecy.4412. Abstract
Patterns of population connectivity shape ecological and evolutionary phenomena from population persistence to local adaptation and can inform conservation strategy. Connectivity patterns emerge from the interaction of individual behavior with a complex and heterogeneous environment. Despite ample observation that dispersal patterns vary through time, the extent to which variation in the physical environment can explain emergent connectivity variation is not clear. Empirical studies of its contribution promise to illuminate a potential source of variability that shapes the dynamics of natural populations. We leveraged simultaneous direct dispersal observations and oceanographic transport simulations of the clownfish Amphiprion clarkii in the Camotes Sea, Philippines, to assess the contribution of oceanographic variability to emergent variation in connectivity. We found that time-varying oceanographic simulations on both annual and monsoonal timescales partly explained the observed dispersal patterns, suggesting that temporal variation in oceanographic transport shapes connectivity variation on these timescales. However, interannual variation in observed mean dispersal distance was nearly 10 times the expected variation from biophysical simulations, revealing that additional biotic and abiotic factors contribute to interannual connectivity variation. Simulated dispersal kernels also predicted a smaller scale of dispersal than the observations, supporting the hypothesis that undocumented abiotic factors and behaviors such as swimming and navigation enhance the probability of successful dispersal away from, as opposed to retention near, natal sites. Our findings highlight the potential for coincident observations and biophysical simulations to test dispersal hypotheses and the influence of temporal variability on metapopulation persistence, local adaptation, and other population processes.
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.
Smith, James A., Mercedes Pozo Buil, Barbara A Muhling, Desiree Tommasi, Stephanie Brodie, Timothy H Frawley, Jerome Fiechter, Stefan Koenigstein, Amber Himes-Cornell, Michael A Alexander, Steven J Bograd, Nathalí Cordero-Quirós, Larry B Crowder, Enrique N Curchitser, Stephanie J Green, Natasha A Hardy, Alan C Haynie, Elliot L Hazen, Kirstin Holsman, Gwendal Le Fol, Nerea Lezama-Ochoa, Ryan R Rykaczewski, Charles A Stock, Stephen Stohs, Jonathan Sweeney, Heather Welch, and Michael G Jacox, February 2023: Projecting climate change impacts from physics to fisheries: A view from three California Current fisheries. Progress in Oceanography, 211, 102973, DOI:10.1016/j.pocean.2023.102973. Abstract
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.
Clark, Suzanna, Katherine A Hubbard, David K Ralston, Dennis J McGillicuddy, Jr, Charles A Stock, Michael A Alexander, and Enrique N Curchitser, June 2022: Projected effects of climate change on Pseudo-nitzschia bloom dynamics in the Gulf of Maine. Journal of Marine Systems, 230, DOI:10.1016/j.jmarsys.2022.103737. Abstract
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.
Cordero-Quirós, Nathalí, Arthur J Miller, Yunchun Pan, Lawrence Balitaan, Enrique N Curchitser, and Raphael Dussin, January 2022: Physical-ecological response of the California Current System to ENSO events in ROMS-NEMURO. Ocean Dynamics, 72, DOI:10.1007/s10236-021-01490-921-36. Abstract
We analyze the bottom-up El Niño/Southern Oscillation (ENSO) driven physical-biological response of the California Current System (CCS) in a high-resolution, “eddy-scale” ocean model with multiple classes of phytoplankton and zooplankton forced with observed winds over the time period 1959–2007. The response of the sea surface temperature anomalies over the CCS is asymmetrical, with La Niña events being more consistently cold than El Niño events are consistently warm, which is in agreement with previous studies. The biogeochemical and ecological response is represented by ENSO composite anomalies, lag correlations with an ENSO index, and histograms for ENSO years. The results show trophic level interactions during El Niño and La Niña events in which the larger components (diatoms, euphausiids, and copepods) are suppressed in the coastal upwelling zones during El Niño, while the smaller components (flagellates and ciliates) are enhanced. In addition, standing eddies of the CCS modulate the latitudinal structure of the ecological response to ENSO. The results point towards future research to understand how bottom-up changes may lead to variability of patterns in ecological response, including fish populations and top predators.
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.
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.
Pozo Buil, Mercedes, Michael G Jacox, Jerome Fiechter, Michael A Alexander, Steven J Bograd, Enrique N Curchitser, Christopher A Edwards, Ryan R Rykaczewski, and Charles A Stock, April 2021: A dynamically downscaled ensemble of future projections for the California Current System. Frontiers in Marine Science, 8, DOI:10.3389/fmars.2021.612874. Abstract
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.
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.
Hauri, Claudine, Cristina Schultz, Katherine Hedstrom, Seth Danielson, Brita Irving, Scott C Doney, Raphael Dussin, Enrique N Curchitser, David F Hill, and Charles A Stock, July 2020: A regional hindcast model simulating ecosystem dynamics, inorganic carbon chemistry and ocean acidification in the Gulf of Alaska. Biogeosciences, 17, DOI:10.5194/bg-17-3837-20203837-3857. Abstract
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.
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.
We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations.
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.
Tsujino, Hiroyuki, Shogo Urakawa, Hideyuki Nakano, J Small, W M Kim, Stephen G Yeager, Gokhan Danabasoglu, Tatsuo Suzuki, J L Bamber, M Bentsen, C Böning, A Bozec, Eric P Chassignet, Enrique N Curchitser, Fabio Boeira Dias, Paul J Durack, and Stephen M Griffies, et al., October 2018: JRA-55 based surface dataset for driving ocean–sea-ice models (JRA55-do). Ocean Modelling, 130, DOI:10.1016/j.ocemod.2018.07.002. Abstract
We present a new surface-atmospheric dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis (JRA-55), referred to here as JRA55-do. The JRA55-do dataset aims to replace the CORE interannual forcing version 2 (hereafter called the CORE dataset), which is currently used in the framework of the Coordinated Ocean-ice Reference Experiments (COREs) and the Ocean Model Intercomparison Project (OMIP). A major improvement in JRA55-do is the refined horizontal grid spacing ( ∼ 55 km) and temporal interval (3 hr). The data production method for JRA55-do essentially follows that of the CORE dataset, whereby the surface fields from an atmospheric reanalysis are adjusted relative to reference datasets. To improve the adjustment method, we use high-quality products derived from satellites and from several other atmospheric reanalysis projects, as well as feedback on the CORE dataset from the ocean modelling community. Notably, the surface air temperature and specific humidity are adjusted using multi-reanalysis ensemble means. In JRA55-do, the downwelling radiative fluxes and precipitation, which are affected by an ambiguous cloud parameterisation employed in the atmospheric model used for the reanalysis, are based on the reanalysis products. This approach represents a notable change from the CORE dataset, which imported independent observational products. Consequently, the JRA55-do dataset is more self-contained than the CORE dataset, and thus can be continually updated in near real-time. The JRA55-do dataset extends from 1958 to the present, with updates expected at least annually. This paper details the adjustments to the original JRA-55 fields, the scientific rationale for these adjustments, and the evaluation of JRA55-do. The adjustments successfully corrected the biases in the original JRA-55 fields. The globally averaged features are similar between the JRA55-do and CORE datasets, implying that JRA55-do can suitably replace the CORE dataset for use in driving global ocean–sea-ice models.
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.
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.
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.
Griffies, Stephen M., Gokhan Danabasoglu, Paul J Durack, Alistair Adcroft, V Balaji, C Böning, Eric P Chassignet, Enrique N Curchitser, Julie Deshayes, H Drange, Baylor Fox-Kemper, Peter J Gleckler, Jonathan M Gregory, Helmuth Haak, Robert Hallberg, Helene T Hewitt, David M Holland, Tatiana Ilyina, J H Jungclaus, Y Komuro, John P Krasting, William G Large, S J Marsland, S Masina, Trevor J McDougall, A J George Nurser, James C Orr, Anna Pirani, Fangli Qiao, Ronald J Stouffer, Karl E Taylor, A M Treguier, Hiroyuki Tsujino, P Uotila, M Valdivieso, Michael Winton, and Stephen G Yeager, September 2016: OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project. Geoscientific Model Development, 9(9), DOI:10.5194/gmd-9-3231-2016. Abstract
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.
The seasonal variability of the mean kinetic energy (MKE) and eddy kinetic energy (EKE) of the Gulf Stream (GS) is examined using high-resolution regional ocean model simulations. A set of three numerical experiments with different surface wind and buoyancy forcing is analyzed to investigate the mechanisms governing the seasonal cycle of upper ocean energetics. In the GS along-coast region, MKE has a significant seasonal cycle that peaks in summer, while EKE has two comparable peaks in May and September near the surface; The May peak decays rapidly with depth. In the off-coast region, MKE has a weak seasonal cycle that peaks in summer, while EKE has a dominant peak in May and a secondary peak in September near the surface. The May peak also decays with depth leaving the September peak as the only seasonal signal below 100m. An analysis of the three numerical experiments suggests that the seasonal variability in the local wind forcing significantly impacts the September peak of the along-coast EKE through a local-flow barotropic instability process. Alternatively, the seasonal buoyancy forcing primarily impacts the flow baroclinic instability and is consequently related to the May peak of the upper ocean EKE in both regions. The analysis results indicate that the seasonal cycle of the along-coast MKE is influenced by both local energy generation by wind and the advection of energy from upstream regions. Finally, the MKE cycle and the September peak of EKE in the off-coast region are mainly affected by advection of energy from remote regions, giving rise to correlations with the seasonal cycle of remote winds.
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.