Findell, Kirsten L., and Zun Yin, et al., February 2024: Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output. Geoscientific Model Development, 17(4), DOI:10.5194/gmd-17-1869-20241869–1883. Abstract
Land–atmosphere (L–A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, and other land-centered climate anomalies. Local L–A coupling (LoCo) metrics capture relevant L–A processes, highlighting the impact of soil and vegetation states on surface flux partitioning and the impact of surface fluxes on boundary layer (BL) growth and development and the entrainment of air above the BL. A primary goal of the Climate Process Team in the Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) project is parameterizing and characterizing the impact of subgrid heterogeneity in global and regional Earth system models (ESMs) to improve the connection between land and atmospheric states and processes. A critical step in achieving that aim is the incorporation of L–A metrics, especially LoCo metrics, into climate model diagnostic process streams. However, because land–atmosphere interactions span timescales of minutes (e.g., turbulent fluxes), hours (e.g., BL growth and decay), days (e.g., soil moisture memory), and seasons (e.g., variability in behavioral regimes between soil moisture and latent heat flux), with multiple processes of interest happening in different geographic regions at different times of year, there is not a single metric that captures all the modes, means, and methods of interaction between the land and the atmosphere. And while monthly means of most of the LoCo-relevant variables are routinely saved from ESM simulations, data storage constraints typically preclude routine archival of the hourly data that would enable the calculation of all LoCo metrics.
We describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Land Model version 4.1 (LM4.1), which builds on component and coupled model developments over 2013–2019 for the coupled carbon-chemistry-climate Earth System Model Version 4.1 (ESM4.1) simulation as part of the sixth phase of the Coupled Model Intercomparison Project. Analysis of ESM4.1/LM4.1 is focused on biophysical and biogeochemical processes and interactions with climate. Key features include advanced vegetation dynamics and multi-layer canopy energy and moisture exchanges, daily fire, land use representation, and dynamic atmospheric dust coupling. We compare LM4.1 performance in the GFDL Earth System Model (ESM) configuration ESM4.1 to the previous generation component LM3.0 in the ESM2G configuration. ESM4.1/LM4.1 provides significant improvement in the treatment of ecological processes from GFDL's previous generation models. However, ESM4.1/LM4.1 likely overestimates the influence of land use and land cover change on vegetation characteristics, particularly on pasturelands, as it overestimates the competitiveness of grasses versus trees in the tropics, and as a result, underestimates present-day biomass and carbon uptake in comparison to observations.
Changes in tropical (30 S–30 N) land hydroclimate following CO2-induced global warming are organized according to climatological aridity index (AI) and daily soil moisture (SM) percentiles. The transform from geographical space to this novel process-oriented phase space allows for interpretation of local, daily mechanistic relationships between key hydroclimatic variables in the context of time-mean and/or global-mean energetic constraints and the wet-get-wetter/dry-get-drier paradigm. Results from 16 CMIP models show coherent patterns of change in the AI/SM phase space that are aligned with the established soil-moisture/evapotranspiration regimes. We introduce an active-rain regime as a special case of the energy-limited regime. Rainfall shifts toward larger rain totals in this active-rain regime, with less rain on other days, resulting in an overall SM reduction. Consequently, the regimes where SM constrains evapotranspiration become more frequently occupied, and corresponding hydroclimatic changes align with the position of the critical SM value in the AI/SM phase space.
Findell, Kirsten L., et al., January 2023: Explaining and predicting earth system change: A World Climate Research Programme call to action. Bulletin of the American Meteorological Society, 104(1), DOI:10.1175/BAMS-D-21-0280.1E325-E339. Abstract
The World Climate Research Programme (WCRP) envisions a world “that uses sound, relevant, and timely climate science to ensure a more resilient present and sustainable future for humankind.” This bold vision requires the climate science community to provide actionable scientific information that meets the evolving needs of societies all over the world. To realize its vision, WCRP has created five Lighthouse Activities to generate international commitment and support to tackle some of the most pressing challenges in climate science today. The overarching goal of the Lighthouse Activity on Explaining and Predicting Earth System Change is to develop an integrated capability to understand, attribute, and predict annual to decadal changes in the Earth system, including capabilities for early warning of potential high impact changes and events. This article provides an overview of both the scientific challenges that must be addressed, and the research and other activities required to achieve this goal. The work is organized in three thematic areas: (i) monitoring and modeling Earth system change; (ii) integrated attribution, prediction, and projection; and (iii) assessment of current and future hazards. Also discussed are the benefits that the new capability will deliver. These include improved capabilities for early warning of impactful changes in the Earth system, more reliable assessments of meteorological hazard risks, and quantitative attribution statements to support the Global Annual to Decadal Climate Update and State of the Climate reports issued by the World Meteorological Organization.
Stephens, Graeme L., Jan Polcher, Xubin Zeng, Peter van Oevelen, Germán Poveda, Michael Bosilovich, Myoung-Hwan Ahn, Gianpaolo Balsamo, Qingyun Duan, Gabriele Hegerl, Christian Jakob, Benjamin Lamptey, L Ruby Leung, Maria Piles, Zhongbo Su, Paul A Dirmeyer, Kirsten L Findell, Anne Verhoef, Michael Ek, Tristan L'Ecuyer, Rémy Roca, Ali Nazemi, Francina Dominguez, Daniel Klocke, and Sandrine Bony, January 2023: The first 30 years of GEWEX. Bulletin of the American Meteorological Society, 104(1), DOI:10.1175/BAMS-D-22-0061.1E126–E157. Abstract
The Global Energy and Water Cycle Exchanges (GEWEX) project was created more than 30 years ago within the framework of the World Climate Research Programme (WCRP). The aim of this initiative was to address major gaps in our understanding of Earth’s energy and water cycles given a lack of information about the basic fluxes and associated reservoirs of these cycles. GEWEX sought to acquire and set standards for climatological data on variables essential for quantifying water and energy fluxes and for closing budgets at the regional and global scales. In so doing, GEWEX activities led to a greatly improved understanding of processes and our ability to predict them. Such understanding was viewed then, as it remains today, essential for advancing weather and climate prediction from global to regional scales. GEWEX has also demonstrated over time the importance of a wider engagement of different communities and the necessity of international collaboration for making progress on understanding and on the monitoring of the changes in the energy and water cycles under ever increasing human pressures. This paper reflects on the first 30 years of evolution and progress that has occurred within GEWEX. This evolution is presented in terms of three main phases of activity. Progress toward the main goals of GEWEX is highlighted by calling out a few achievements from each phase. A vision of the path forward for the coming decade, including the goals of GEWEX for the future, are also described.
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.
Zhou, Sha, Bofu Yu, Benjamin R Lintner, Kirsten L Findell, and Yao Zhang, May 2023: Projected increase in global runoff dominated by land surface changes. Nature Climate Change, 13, DOI:10.1038/s41558-023-01659-8442-449. Abstract
Increases in atmospheric CO2 concentration affect continental runoff through radiative and physiological forcing. However, how climate and land surface changes, and their interactions in particular, regulate changes in global runoff remains largely unresolved. Here we develop an attribution framework that integrates top-down empirical and bottom-up modelling approaches to show that land surface changes account for 73–81% of projected global runoff increases. This arises from synergistic effects of physiological responses of vegetation to rising CO2 concentration and responses of land surface—for example, vegetation cover and soil moisture—to radiatively driven climate change. Although climate change strongly affects regional runoff changes, it plays a minor role (19–27%) in the global runoff increase, due to cancellation of positive and negative contributions from different regions. Our findings highlight the importance of accurate model representation of land surface processes for reliable projections of global runoff to support sustainable management of water resources.
Findell, Kirsten L., Rowan Sutton, and Nico Caltabiano, July 2022: Explaining and predicting Earth system change: A World Climate Research Programme call to action. GEWEX Quarterly, 32(4), 5-7.
Smith, Doug, Nathan P Gillett, Isla Simpson, Panos Athanasiadis, J Baehr, Ingo Bethke, Tarkan Bilge, Rémy Bonnet, Olivier Boucher, and Kirsten L Findell, et al., September 2022: Attribution of multi-annual to decadal changes in the climate system: The Large Ensemble Single Forcing Model Intercomparison Project (LESFMIP). Frontiers in Climate, 4:955414, DOI:10.3389/fclim.2022.955414. Abstract
Multi-annual to decadal changes in climate are accompanied by changes in extreme events that cause major impacts on society and severe challenges for adaptation. Early warnings of such changes are now potentially possible through operational decadal predictions. However, improved understanding of the causes of regional changes in climate on these timescales is needed both to attribute recent events and to gain further confidence in forecasts. Here we document the Large Ensemble Single Forcing Model Intercomparison Project that will address this need through coordinated model experiments enabling the impacts of different external drivers to be isolated. We highlight the need to account for model errors and propose an attribution approach that exploits differences between models to diagnose the real-world situation and overcomes potential errors in atmospheric circulation changes. The experiments and analysis proposed here will provide substantial improvements to our ability to understand near-term changes in climate and will support the World Climate Research Program Lighthouse Activity on Explaining and Predicting Earth System Change.
Verhoef, Anne, and Kirsten L Findell, July 2022: Report on the GEWEX 2022 GLASS Panel Meeting. GEWEX Quarterly, 32(4), 14-16.
Zhou, Sha, A Park Williams, Benjamin R Lintner, Kirsten L Findell, Trevor F Keenan, Yao Zhang, and Pierre Gentine, September 2022: Diminishing seasonality of subtropical water availability in a warmer world dominated by soil moisture–atmosphere feedbacks. Nature Communications, 13, 5756, DOI:10.1038/s41467-022-33473-9. Abstract
Global warming is expected to cause wet seasons to get wetter and dry seasons to get drier, which would have broad social and ecological implications. However, the extent to which this seasonal paradigm holds over land remains unclear. Here we examine seasonal changes in surface water availability (precipitation minus evaporation, P–E) from CMIP5 and CMIP6 projections. While the P–E seasonal cycle does broadly intensify over much of the land surface, ~20% of land area experiences a diminished seasonal cycle, mostly over subtropical regions and the Amazon. Using land–atmosphere coupling experiments, we demonstrate that 63% of the seasonality reduction is driven by seasonally varying soil moisture (SM) feedbacks on P–E. Declining SM reduces evapotranspiration and modulates circulation to enhance moisture convergence and increase P–E in the dry season but not in the wet season. Our results underscore the importance of SM–atmosphere feedbacks for seasonal water availability changes in a warmer climate.
Ek, Michael, Kirsten L Findell, and Anne Verhoef, May 2021: 2020 GLASS Panel Meeting. GEWEX Quarterly, 31(2), 14-18. Abstract
Jakob, Christian, Peter Bauer, Sandrine Bony, Daniel Klocke, Kirsten L Findell, Anne Verhoef, Francina Dominguez, Ali Nazemi, and Jan Polcher, July 2021: The WCRP Digital Earths Lighthouse Activity–An opportunity for the GEWEX community. GEWEX Quarterly, 31(4), 7-9.
Climate models often show errors in simulating and predicting tropical cyclone (TC) activity, but the sources of these errors are not well understood. This study proposes an evaluation framework and analyzes three sets of experiments conducted using a seasonal prediction model developed at the Geophysical Fluid Dynamics Laboratory (GFDL). These experiments apply the nudging technique to the model integration and/or initialization to estimate possible improvements from nearly perfect model conditions. The results suggest that reducing sea surface temperature (SST) errors remains important for better predicting TC activity at long forecast leads—even in a flux-adjusted model with reduced climatological biases. Other error sources also contribute to biases in simulated TC activity, with notable manifestations on regional scales. A novel finding is that the coupling and initialization of the land and atmosphere components can affect seasonal TC prediction skill. Simulated year-to-year variations in June land conditions over North America show a significant lead correlation with the North Atlantic large-scale environment and TC activity. Improved land–atmosphere initialization appears to improve the Atlantic TC predictions initialized in some summer months. For short-lead predictions initialized in June, the potential skill improvements attributable to land–atmosphere initialization might be comparable to those achievable with perfect SST predictions. Overall, this study delineates the SST and non-oceanic error sources in predicting TC activity and highlights avenues for improving predictions. The nudging-based evaluation framework can be applied to other models and help improve predictions of other weather extremes.
Duan, Suqin Q., Kirsten L Findell, and Jonathon S Wright, December 2020: Three Regimes of Temperature Distribution Change over Dry Land, Moist Land and Oceanic Surfaces. Geophysical Research Letters, 47(24), DOI:10.1029/2020GL090997. Abstract
Climate model simulations project different regimes of summertime temperature distribution changes under a quadrupling of CO2 for dry land, moist land, and oceanic surfaces. The entire temperature distribution shifts over dry land surfaces, while moist land surfaces feature an elongated upper tail of the distribution, with extremes increasing more than the corresponding means by ∼20% of the global mean warming. Oceanic surfaces show weaker warming relative to land surfaces, with no significant elongation of the upper tail. Dry land surfaces show little change in turbulent sensible (SH) or latent (LH) fluxes, with new balance reached with compensating adjustments among downwelling and upwelling radiative fluxes. By contrast, moist land surfaces show enhanced partitioning of turbulent flux toward SH, while oceanic surfaces show enhanced partitioning toward LH. Amplified warming of extreme temperatures over moist land surfaces is attributed to suppressed evapotranspiration and larger Bowen ratios.
Findell, Kirsten L., P W Keys, R J van der Ent, Benjamin R Lintner, Alexis Berg, and John P Krasting, November 2019: Rising Temperatures Increase Importance of Oceanic Evaporation as a Source for Continental Precipitation. Journal of Climate, 32(22), DOI:10.1175/JCLI-D-19-0145.1. Abstract
Understanding vulnerabilities of continental precipitation to changing climatic conditions is of critical importance to society at large. Terrestrial precipitation is fed by moisture originating as evaporation from oceans and from recycling of water evaporated from continental sources. In this study, continental precipitation and evaporation recycling processes in the earth system model GFDL-ESM2G are shown to be consistent with estimates from two different reanalysis products. The GFDL-ESM2G simulations of historical and future climate also show that values of continental moisture recycling ratios were systematically higher in the past and will be lower in the future. Global mean recycling ratios decrease 2-3% with each degree of temperature increase, indicating increased importance of oceanic evaporation for continental precipitation. Theoretical arguments for recycling changes stem from increasing atmospheric temperatures and evaporative demand that drive more rapid increases in evaporation over oceans than over land as a result of terrestrial soil moisture limitations. Simulated recycling changes are demonstrated to be consistent with these theoretical arguments. A simple prototype describing this theory effectively captures the zonal mean behavior of GFDL-ESM2G. Implications of such behavior are particularly serious in rain-fed agricultural regions where crop yields will become increasingly soil moisture limited.
Green, J K., Sonia I Seneviratne, Alexis Berg, and Kirsten L Findell, et al., January 2019: Large influence of soil moisture on long-term terrestrial carbon uptake. Nature, 565(7740), DOI:10.1038/s41586-018-0848-x. Abstract
Although the terrestrial biosphere absorbs about 25 per cent of anthropogenic carbon dioxide (CO2) emissions, the rate of land carbon uptake remains highly uncertain, leading to uncertainties in climate projections1,2. Understanding the factors that limit or drive land carbon storage is therefore important for improving climate predictions. One potential limiting factor for land carbon uptake is soil moisture, which can reduce gross primary production through ecosystem water stress3,4, cause vegetation mortality5 and further exacerbate climate extremes due to land–atmosphere feedbacks6. Previous work has explored the impact of soil-moisture availability on past carbon-flux variability3,7,8. However, the influence of soil-moisture variability and trends on the long-term carbon sink and the mechanisms responsible for associated carbon losses remain uncertain. Here we use the data output from four Earth system models9 from a series of experiments to analyse the responses of terrestrial net biome productivity to soil-moisture changes, and find that soil-moisture variability and trends induce large CO2 fluxes (about two to three gigatons of carbon per year; comparable with the land carbon sink itself1) throughout the twenty-first century. Subseasonal and interannual soil-moisture variability generate CO2 as a result of the nonlinear response of photosynthesis and net ecosystem exchange to soil-water availability and of the increased temperature and vapour pressure deficit caused by land–atmosphere interactions. Soil-moisture variability reduces the present land carbon sink, and its increase and drying trends in several regions are expected to reduce it further. Our results emphasize that the capacity of continents to act as a future carbon sink critically depends on the nonlinear response of carbon fluxes to soil moisture and on land–atmosphere interactions. This suggests that the increasing trend in carbon uptake rate may not be sustained past the middle of the century and could result in accelerated atmospheric CO2 growth.
Herrara-Estrada, J E., J A Martinez, Francina Dominguez, and Kirsten L Findell, et al., May 2019: Reduced moisture transport linked to drought propagation across North America. Geophysical Research Letters, 46(10), DOI:10.1029/2019GL082475. Abstract
Droughts can have devastating societal impacts. Yet, we do not fully understand the mechanisms that control their development, possibly affecting our ability to predict them. Here we run a moisture‐tracking analytical model using reanalysis data between 1980‐2016 to explore the role of reduced moisture transport in drought propagation. We find that agricultural droughts in multiple sub‐regions across North America may be amplified by decreased moisture transport from upwind land areas, which we link to reduced evapotranspiration and dry soil moisture upwind. We also find that decreases in precipitation recycling are correlated with decreases in moisture arriving from upwind areas. We estimate that decreases in moisture contributions from land areas accounted for 62% of the precipitation deficit during the 2012 Midwest drought. Our results suggest that the land‐surface may contain useful information for drought prediction, and highlight the importance of sustainable land‐use and of regional cooperation for drought risk management.
Santanello, J A., Paul A Dirmeyer, Craig Ferguson, and Kirsten L Findell, et al., June 2018: Land-Atmosphere Interactions: The LoCo Perspective. Bulletin of the American Meteorological Society, 99(6), DOI:10.1175/BAMS-D-17-0001.1. Abstract
Metrics derived by the LoCo working group have matured and begun to enter the mainstream, signaling the success of the GEWEX approach to foster grassroots participation. In this article, LoCo’s researchers discuss past, present and planned efforts.
Land-atmosphere (L-A) interactions are a main driver of Earth’s surface water and energy budgets; as such, they modulate near-surface climate, including clouds and precipitation, and can influence the persistence of extremes such as drought. Despite their importance, the representation of L-A interactions in weather and climate models remains poorly constrained, as they involve a complex set of processes that are difficult to observe in nature. In addition, a complete understanding of L-A processes requires interdisciplinary expertise and approaches that transcend traditional research paradigms and communities. To address these issues, the international Global Energy and Water Exchanges project (GEWEX) Global Land-Atmosphere System Study (GLASS) panel has supported ‘L-A coupling’ as one of its core themes for well over a decade. Under this initiative, several successful land surface and global climate modeling projects have identified hotspots of L-A coupling and helped quantify the role of land surface states in weather and climate predictability. GLASS formed the Local L-A Coupling (‘LoCo’) project and working group to examine L-A interactions at the process level, focusing on understanding and quantifying these processes in nature and evaluating them in models. LoCo has produced an array of L-A coupling metrics for different applications and scales, and has motivated a growing number of young scientists from around the world. This article provides an overview of the LoCo effort, including metric and model applications, along with scientific and programmatic developments and challenges.
Berg, Alexis, Benjamin R Lintner, Kirsten L Findell, and A Giannini, April 2017: Soil Moisture Influence on Seasonality and Large-Scale Circulation in Simulations of the West African Monsoon. Journal of Climate, 30(7), DOI:10.1175/JCLI-D-15-0877.1. Abstract
Prior studies have highlighted West Africa as a regional hotspot of land–atmosphere coupling. This study focuses on the large-scale influence of soil moisture variability on the mean circulation and precipitation in the West African monsoon. A suite of six models from the Global Land–Atmosphere Coupling Experiment (GLACE)-CMIP5 is analyzed. In this experiment, model integrations were performed with soil moisture prescribed to a specified climatological seasonal cycle throughout the simulation, which severs the two-way coupling between soil moisture and the atmosphere. Comparison with the control (interactive soil moisture) simulations indicates that mean June–September monsoon precipitation is enhanced when soil moisture is prescribed. However, contrasting behavior is evident over the seasonal cycle of the monsoon, with core monsoon precipitation enhanced with prescribed soil moisture but early-season precipitation reduced, at least in some models. These impacts stem from the enhancement of evapotranspiration at the dry poleward edge of the monsoon throughout the monsoon season, when soil moisture interactivity is suppressed. The early-season decrease in rainfall with prescribed soil moisture is associated with a delayed poleward advancement of the monsoon, which reflects the relative cooling of the continent from enhanced evapotranspiration, and thus a reduced land–ocean thermal contrast, prior to monsoon onset. On the other hand, during the core/late monsoon season, surface evaporative cooling modifies meridional temperature gradients and, through these gradients, alters the large-scale circulation: the midlevel African easterly jet is displaced poleward while the low-level westerlies are enhanced; this enhances precipitation. These results highlight the remote impacts of soil moisture variability on atmospheric circulation and precipitation in West Africa.
Berg, Alexis, Benjamin R Lintner, Kirsten L Findell, and A Giannini, June 2017: Uncertain soil moisture feedbacks in model projections of Sahel precipitation. Geophysical Research Letters, 44(12), DOI:10.1002/2017GL073851. Abstract
Given the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semi-arid region is crucial. This study investigates how long-term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differ across the models. These results demonstrate that reducing uncertainties across model projections of the WAM requires, among other factors, improved mechanistic understanding and constraint of simulated land-atmosphere feedbacks, even at the large spatial scales considered here.
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.
Berg, Alexis, Kirsten L Findell, Benjamin R Lintner, A Giannini, Sonia I Seneviratne, Bart van den Hurk, R Lorenz, A J Pitman, S Hagemann, A Meier, F Cheruy, A Ducharne, Sergey Malyshev, and P C D Milly, September 2016: Land–atmosphere feedbacks amplify aridity increase over land under global warming. Nature Climate Change, 6(9), DOI:10.1038/nclimate3029. Abstract
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.
Berg, Alexis, Benjamin R Lintner, Kirsten L Findell, Sonia I Seneviratne, Bart van den Hurk, A Ducharne, F Cheruy, S Hagemann, David Lawrence, and Sergey Malyshev, et al., February 2015: Interannual coupling between summertime surface temperature and precipitation over land: processes and implications for climate change. Journal of Climate, 28(3), DOI:10.1175/JCLI-D-14-00324.1. Abstract
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.
Findell, Kirsten L., Pierre Gentine, Benjamin R Lintner, and B P Guillod, August 2015: Data Length Requirements for Observational Estimates of Land-Atmosphere Coupling Strength. Journal of Hydrometeorology, 16(4), DOI:10.1175/JHM-D-14-0131.1. Abstract
Multiple metrics have been developed in recent years to characterize the strength of land-atmosphere coupling in regional and global climate models. Evaluation of these metrics against observations has proven challenging because of limited observations and/or metric definitions based on model experimental designs that are not replicable with observations. Additionally, because observations are limited in time, with only a single realization of the earth’s climate available, metrics of land-atmosphere coupling strength typically assume stationarity and ergodicity, so that an observed time series (or set of time series) can be used in place of an ensemble mean of multiple realizations. The present study evaluates the observational data requirements necessary for robust quantification of a suite of land-atmosphere coupling metrics previously described in the literature. We demonstrate that the amount of data required to obtain robust estimates of metrics assessing relationships between variables is greater than that necessary to constrain means of directly-measured observables. Moreover, while the addition of unbiased noise does not significantly alter the mean of a directly observable quantity, inclusion of such noise degrades metrics based on connections between variables, yielding a unidirectional and negative impact on metric strength estimates. This analysis suggests that longer records of surface observations are required to correctly estimate land-atmosphere coupling strength than are required to estimate mean values of the observed quantities.
Lintner, Benjamin R., Pierre Gentine, Kirsten L Findell, and G D Salvucci, May 2015: The Budyko and complementary relationships in an idealized model of large-scale land–atmosphere coupling. Hydrology and Earth System Sciences, 19(5), DOI:10.5194/hess-19-2119-2015. Abstract
Expressions corresponding to two well-known relationships in hydrology and hydrometeorology, the Budyko and complementary relationships, are derived within an idealized prototype representing the physics of large-scale land–atmosphere coupling. These relationships are shown to hold on long (climatologic) time scales because of the tight coupling that exists between precipitation, atmospheric radiation, moisture convergence and advection. The slope of the complementary relationship is shown to be dependent the Clausius–Clapeyron relationship between saturation specific humidity and temperature, with important implications for the continental hydrologic cycle in a warming climate, e.g., one consequence of this dependence is that the complementary relationship may be expected to become more asymmetric with warming, as higher values of the slope imply a larger change in potential evaporation for a given change in evapotranspiration. In addition, the transparent physics of the prototype permits diagnosis of the sensitivity of the Budyko and complementary relationships to various atmospheric and land surface processes. Here, the impacts of anthropogenic influences, including large-scale irrigation and global warming, are assessed.
Aires, F, Pierre Gentine, Kirsten L Findell, Benjamin R Lintner, and Christopher Kerr, March 2014: Neural network-based sensitivity analysis of summertime convection over the continental US. Journal of Climate, 27(5), DOI:10.1175/JCLI-D-13-00161.1. Abstract
Although land-atmosphere coupling is thought to play a role in shaping the mean climate and its variability, it remains difficult to quantify precisely. The present study aims to isolate relationships between early morning surface turbulent fluxes partitioning (i.e., evaporative fraction, EF), and subsequent afternoon convective precipitation frequency and intensity. A general approach involving statistical relationships among input and output variables, known as Sensitivity Analysis (SA), is used to develop a reduced complexity meta-model of the linkage between EF and convective precipitation. Two additional quantities characterizing the early morning convective environment, convective triggering potential (CTP) and low-level humidity (HIlow) deficit, are included. The SA approach is applied to the North American Regional Reanalysis (NARR) for June-July-August (JJA) conditions over the entire continental United States, Mexico, and Central America domain. Five land-atmosphere coupling regimes are objectively characterized based on CTP, HIlow and EF. Two western regimes are largely atmospherically controlled, with a positive link to CTP and a negative link to HIlow. The other three regimes occupy Mexico and the eastern half of the domain and show positive links to EF and negative links to HIlow, suggesting that both surface fluxes and atmospheric humidity play a role in the triggering of rainfall in these regions. The regimes associated with high mean EF also tend to have high sensitivity of rainfall frequency to variations in EF. While these results may be sensitive to the choice of dataset, the approach can be applied across observational, reanalysis, and model datasets and thus represents a potentially powerful tool for inter-comparison and validation as well as to characterize land-atmosphere interactions regimes.
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.
Guillod, B P., B Orlowsky, D Miralles, A J Teuling, P D Blanken, N Buchmann, Philippe Ciais, Michael Ek, and Kirsten L Findell, et al., August 2014: Land surface controls on afternoon precipitation diagnosed from observational data: uncertainties, confounding factors and the possible role of vegetation interception. Atmospheric Chemistry and Physics, 14(16), DOI:10.5194/acp-14-8343-2014. Abstract
The feedback between soil moisture and precipitation has long been a topic of interest due to its potential for improving weather and seasonal forecasts. The generally proposed mechanism assumes a control of soil moisture on precipitation via the partitioning of the surface turbulent heat fluxes, as assessed via the Evaporative Fraction, EF, i.e. the ratio of latent heat to the sum of latent and sensible heat, in particular under convective conditions. Our study investigates the poorly understood link between EF and precipitation by investigating the impact of before-noon EF on the frequency of afternoon precipitation over the contiguous US, using a statistical analysis of the relationship between multiple datasets of EF and precipitation. We analyze remote sensing data products (EF from GLEAM, Global Land Evaporation: the Amsterdam Methodology, based on satellite observations; and radar precipitation from NEXRAD, the NEXt generation weather RADar system), FLUXNET station data, and the North American Regional Reanalysis (NARR). While most datasets agree on the existence of regions of positive relationship between between EF and precipitation in the Eastern and Southwestern US, observation-based estimates (GLEAM, NEXRAD and to some extent FLUXNET) also indicate a strong relationship in the Central US which is not found in NARR. Investigating these differences, we find that much of these relationships can be explained by precipitation persistence alone, with ambiguous results on the additional role of EF in causing afternoon precipitation. Regional analyses reveal contrasting mechanisms over different regions. Over the Eastern US, our analyses suggest that the apparent EF-precipitation coupling takes place on a short day-to-day time scale and is either atmospherically controlled (from precipitation persistence and potential evaporation) or driven by vegetation interception and subsequent re-evaporation (rather than soil moisture and related plant transpiration/bare soil evaporation), in line with the high forest cover and the wet regime of that region. Over the Central and Southwestern US, the impact of EF on convection triggering is additionally linked to soil moisture variations, owing to the soil moisture–limited climate regime.
“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.
Rochetin, Nicolas, Benjamin R Lintner, Kirsten L Findell, Adam H Sobel, and Pierre Gentine, December 2014: Radiative–Convective Equilibrium over a Land Surface. Journal of Climate, 27(23), DOI:10.1175/JCLI-D-13-00654.1. Abstract
Radiative–convective equilibrium (RCE) describes an idealized state of the atmosphere in which the vertical temperature profile is determined by a balance between radiative and convective fluxes. While RCE has been applied extensively over oceans, its application over the land surface has been limited. The present study explores the properties of RCE over land using an atmospheric single-column model (SCM) from the Laboratoire de Météorologie Dynamique–Zoom, version 5B (LMDZ5B) general circulation model coupled in temperature and moisture to a land surface model using a simplified bucket model with finite moisture capacity. Given the presence of a large-amplitude diurnal heat flux cycle, the resultant RCE exhibits multiple equilibria when conditions are neither strictly water nor energy limited. By varying top-of-atmosphere insolation (through changes in latitude), total system water content, and initial temperature conditions the sensitivity of the land RCE states is assessed, with particular emphasis on the role of clouds. Based on this analysis, it appears that a necessary condition for the model to exhibit multiple equilibria is the presence of low-level clouds coupled to the diurnal cycle of radiation. In addition the simulated surface precipitation rate varies nonmonotonically with latitude as a result of a tradeoff between in-cloud rain rate and subcloud rain reevaporation, thus underscoring the importance of subcloud layer processes and unsaturated downdrafts. It is shown that clouds, especially at low levels, are key elements of the internal variability of the coupled land–atmosphere system through their feedback on radiation.
Berg, Alexis, Kirsten L Findell, Benjamin R Lintner, Pierre Gentine, and Christopher Kerr, June 2013: Precipitation sensitivity to surface heat fluxes over North America in reanalysis and model data. Journal of Hydrometeorology, 14(3), DOI:10.1175/JHM-D-12-0111.1. Abstract
A new methodology for assessing the impact of surface heat fluxes on precipitation is applied to data from the North American Regional Reanalysis (NARR) and to output from the Geophysical Fluid Dynamics Laboratory’s model AM2.1. The method assesses the sensitivity of afternoon convective rainfall frequency and intensity to the late-morning partitioning of latent and sensible heating, quantified in terms of evaporative fraction (EF). Over North America, both NARR and AM2.1 indicate sensitivity of convective rainfall triggering to EF but no appreciable influence of EF on convective rainfall amounts. Functional relationships between the triggering feedback strength (TFS) metric and mean EF demonstrate the occurrence of stronger coupling for mean EF in the range of 0.6 to 0.8. To leading order, AM2.1 exhibits spatial distributions and seasonality of the EF impact on triggering resembling those seen in NARR: rainfall probability increases with higher EF over the Eastern US and Mexico and peaks in Northern Hemisphere summer. Over those regions, the impact of EF variability on afternoon rainfall triggering in summer can explain up to 50% of seasonal rainfall variability. However, the AM2.1 metrics also exhibit some features not present in NARR, e.g., strong coupling extending northwest from the central Great Plains into Canada. Sources of disagreement may include model hydroclimatic biases that affect the mean patterns and variability of surface flux partitioning, with EF variability typically much lower in NARR. Finally, we also discuss the consistency of our results with other assessments of land-precipitation coupling obtained from different methodologies.
Gentine, Pierre, A K Betts, Benjamin R Lintner, and Kirsten L Findell, et al., June 2013: A probabilistic-bulk model of mixed layer and convection: 1) Clear-sky case. Journal of the Atmospheric Sciences, 70(6), DOI:10.1175/JAS-D-12-0145.1. Abstract
A new bulk model of the convective boundary layer, the probabilistic bulk convection model (PBCM), is presented. Unlike prior bulk approaches that have modeled the mixed-layer-top buoyancy flux as a constant fraction of the surface buoyancy flux, PBCM implements a new mixed-layer-top entrainment closure based on the mass flux of updrafts overshooting the inversion. This mass flux is related to the variability of the surface state (potential temperature θ and specific humidity q) of an ensemble of updraft plumes. We evaluate the model against observed clear-sky weak and strong inversion cases and show that PBCM performs well. The height, state and timing of the boundary layer growth are accurately reproduced. Sensitivity studies are performed highlighting the role of the main parameters (surface variances, lateral entrainment). The model is weakly sensitive to the exact specification of the variability at the surface and is most sensitive to the lateral entrainment of environmental air into the rising plumes. Apart from allowing time-dependent top-of-the boundary-layer entrainment rates expressed in terms of surface properties, which can be observed in situ, PBCM naturally takes into account the transition to the shallow convection regime, as described in a companion paper. Thus, PBCM represents an important step towards a unified framework bridging parameterizations of mixed layer entrainment velocity in both clear-sky and moist convective boundary layers.
Gentine, Pierre, A K Betts, Benjamin R Lintner, and Kirsten L Findell, et al., June 2013: A probabilistic-bulk model of coupled mixed layer and convection: 2) Shallow convection case. Journal of the Atmospheric Sciences, 70(16), DOI:10.1175/JAS-D-12-0146.1. Abstract
The probabilistic bulk convection model (PBCM) developed in a companion paper is here extended to shallow non-precipitating convection. The PBCM unifies the clear-sky and shallow convection boundary layer regimes, by obtaining mixed-layer growth, cloud fraction and convective inhibition from a single parameterization based on physical principles. The evolution of the shallow convection PBCM is based on the statistical distribution of the surface thermodynamic state of convective plumes.
The entrainment velocity of the mixed layer is related to the mass flux of the updrafts overshooting the dry inversion capping the mixed layer. The updrafts overcoming the convective inhibition generate active cloud base mass flux, which is the boundary condition for the shallow cumulus scheme. The subcloud layer entrainment velocity is directly coupled to the cloud base mass flux through the distribution of vertical velocity and fractional cover of the updrafts.
Comparisons of the PBCM against large-eddy simulations from the Barbados Oceanographic and Meteorological Experiment (BOMEX) and from the Southern Great Plains Atmospheric Radiation Measurement (ARM) facility demonstrate good agreement in terms of thermodynamic structure, cloud base mass flux and cloud top.
The equilibrium between the cloud base mass flux and rate of growth of the mixed layer determines the equilibrium convective inhibition and cloud cover. This process is an important new insight on the coupling between the mixed-layer and cumulus dynamics. Given its relative simplicity and transparency, the PBCM represents a powerful tool for developing process-based understanding and intuition about the physical processes involved in boundary layer-convection interactions, as well as a testbed for diagnosing and validating shallow convection parameterizations.
Lintner, Benjamin R., Pierre Gentine, and Kirsten L Findell, et al., April 2013: An idealized prototype for large-scale land-atmosphere coupling. Journal of Climate, 26(7), DOI:10.1175/JCLI-D-11-00561.1. Abstract
A process-based, semi-analytic prototype model for understanding large-scale land-atmosphere coupling is developed here. The metric for quantifying the coupling is the sensitivity of precipitation (P) to soil moisture (W), defined as . For a range of prototype parameters typical of conditions found over tropical or summertime continents, the sensitivity measure exhibits a broad minimum at intermediate soil moisture values. This minimum is attributed to a tradeoff between evaporation (or evapotranspiration) E and large-scale moisture convergence across the range of soil moisture states. For low soil moisture, water-limited conditions, is dominated by evaporative sensitivity , reflecting high potential evaporation (Ep) arising from relatively warm surface conditions and a moisture-deficient atmospheric column under dry surface conditions. By contrast, under high soil moisture (or energy-limited) conditions, becomes slightly negative as Ep decreases. However, because convergence and precipitation increase strongly with decreasing (drying) moisture advection, while soil moisture slowly saturates, is large. Variation of key parameters is shown to impact the magnitude of , e.g., increasing the timescale for deep convective adjustment lowers at a given W, especially on the moist side of the profile where convergence dominates. While the prototype applicability’s for direct quantitative comparison to either observations or models is clearly limited, it nonetheless demonstrates how the complex interplay of surface turbulent and column radiative fluxes, deep convection, and horizontal and vertical moisture transport influences the coupling of the land surface and atmosphere that may be expected to occur in either more realistic models or observations.
Seneviratne, Sonia I., Alexis Berg, Kirsten L Findell, and Sergey Malyshev, et al., October 2013: Impact of soil moisture-climate feedbacks on CMIP5 projections: First results from the GLACE-CMIP5 experiment. Geophysical Research Letters, 40(19), DOI:10.1002/grl.50956. Abstract
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.
Su, Hua, R Dickinson, Kirsten L Findell, and Benjamin R Lintner, June 2013: How are spring snow conditions in central Canada related to early warm season precipitation?Journal of Hydrometeorology, 14(3), DOI:10.1175/JHM-D-12-029.1. Abstract
The response of the warm season atmosphere to antecedent snow anomalies has long been an area of study. This paper explores how the spring snow depth relates to subsequent precipitation in central Canada using ground observations, reanalysis datasets and offline land surface model estimates. After removal of low-frequency ocean influences, April snow depth is found to correlate negatively with early warm season (May-June) precipitation across a large portion of the study area. A chain of mechanisms is hypothesized to account for this observed negative relation: (1) a snow depth anomaly leads to a soil moisture anomaly; (2) the subsequent soil moisture anomaly affects ground turbulent fluxes; and (3) the atmospheric vertical structure allows dry soil to promote local convection. A detailed analysis supports this chain of mechanisms for those portions of the domain manifesting statistically significant negative snow-precipitation correlation. For a portion of the study area, large-scale atmospheric circulation patterns also affect the early warm season rainfall, indicating that the snow-precipitation feedback may depend on large-scale atmospheric dynamical features. This analysis suggests that spring snow conditions can contribute to warm-season precipitation predictability on a sub-seasonal to seasonal scale, but that the strength of such predictability varies geographically as it depends on the interplay of hydro-climatological conditions across multiple spatial scales.
Gentine, Pierre, T J Troy, Benjamin R Lintner, and Kirsten L Findell, March 2012: Scaling in Surface Hydrology: Progress and Challenges. Journal of Contemporary Water Research & Education, 147(1), DOI:10.1111/j.1936-704X.2012.03105.x. Abstract
This paper presents a review of the challenges in spatial and temporal scales in surface hydrology. Fundamental issues and gaps in our understanding of hydrologic scaling are highlighted and shown to limit predictive skill, with heterogeneities, nonlinearities, and non-local transport processes among the most significant difficulties faced in scaling. The discrepancy between the physical process scale and the measurement scale has played a major role in restricting the development of theories, for example, relating observational scales to scales of climate and weather models. Progress in our knowledge of scaling in hydrology requires systematic determination of critical scales and scale invariance of physical processes. In addition, viewing the surface hydrologic system as composed of interacting dynamical subsystems should facilitate the definition of scales observed in nature. Such an approach would inform the development of careful, resolution-dependent, physical law formulation based on mathematical techniques and physical laws.
Lintner, Benjamin R., M Biasutti, N S Diffenbaugh, J E Lee, M J Niznik, and Kirsten L Findell, June 2012: Amplification of wet and dry month occurrence over tropical land regions in response to global warming. Journal of Geophysical Research: Atmospheres, 117, D11106, DOI:10.1029/2012JD017499. Abstract
Quantifying how global warming impacts the spatiotemporal distribution of precipitation represents a key scientific challenge with profound implications for human systems. Utilizing monthly precipitation data from Coupled Model Intercomparison Project (CMIP3) climate change simulations, the results here show that the occurrence of very dry (<0.5 mm/day) and very wet (>10 mm/day) months comprises a straightforward, robust metric of anthropogenic warming on tropical land region rainfall. In particular, differencing tropicswide precipitation frequency histograms for 25-year periods over the late 21st and 20th centuries shows increased late-21st-century occurrence of both histogram extremes in the model ensemble and across individual models. Mechanistically, such differences are consistent with the view of enhanced tropical precipitation spatial gradients. Similar diagnostics are calculated for two 15-year subperiods over 1979-2008 for the CMIP3 models and three observational precipitation products to assess whether the signature of late-21st-century warming has already emerged in response to recent warming. While both the observations and CMIP3 ensemble-mean hint at similar amplification in the warmer (1994-2008) subinterval, the changes are not robust, as substantial differences are evident among the observational products and the intraensemble spread is large. Comparing histograms computed from the warmest and coolest years of the observational period further demonstrates effects of internal variability, notably the El Niño/Southern Oscillation, which appear to oppose the impact quasi-uniform anthropogenic warming on the wet tail of the monthly precipitation distribution. These results identify the increase of very dry and wet occurrences in monthly precipitation as a potential signature of anthropogenic global warming but also highlight the continuing dominance of internal climate variability on even bulk measures of tropical rainfall.
Findell, Kirsten L., Pierre Gentine, Benjamin R Lintner, and Christopher Kerr, June 2011: Probability of afternoon precipitation in eastern United States and Mexico enhanced by high evaporation. Nature Geoscience, 4(7), DOI:10.1038/ngeo1174. Abstract
Moisture and heat fluxes from the land surface to the atmosphere form a critical nexus between surface hydrology and atmospheric processes, particularly those relevant to precipitation. Although current theory suggests that soil moisture generally has a positive impact on subsequent precipitation, individual studies have shown support both for and against this positive feedback. Broad assessment of the coupling between soil moisture and evapotranspiration, and evapotranspiration and precipitation, has been limited by a lack of large-scale observations. Quantification of the influence of evapotranspiration on precipitation remains particularly uncertain. Here, we develop and apply physically based, objective metrics for quantifying the impacts of surface evaporative and sensible heat fluxes on the frequency and intensity of convective rainfall during summer, using North American reanalysis data. We show that high evaporation enhances the probability of afternoon rainfall east of the Mississippi and in Mexico. Indeed, variations in surface fluxes lead to changes in afternoon rainfall probability of between 10 and 25% in these regions. The intensity of rainfall, by contrast, is largely insensitive to surface fluxes. We suggest that local surface fluxes represent an important trigger for convective rainfall in the eastern United States and Mexico during the summer, leading to a positive evaporation–precipitation feedback.
Santanello, J A., Craig Ferguson, Michael Ek, Paul A Dirmeyer, O Tuinenburg, C Jacobs, Chiel C van Heerwaarden, and Kirsten L Findell, et al., November 2011: Local land-atmosphere coupling (LoCo) research: Status and results. GEWEX News, 21(4), 7-9. Abstract
Climate model simulations run as part of the Climate Variability and Predictability (CLIVAR) Drought Working Group initiative were analyzed to determine the impact of three patterns of sea surface temperature (SST) anomalies on drought and pluvial frequency and intensity around the world. The three SST forcing patterns include a global pattern similar to the background warming trend, a pattern in the Pacific, and a pattern in the Atlantic. Five different global atmospheric models were forced by fixed SSTs to test the impact of these SST anomalies on droughts and pluvials relative to a climatologically forced control run.
The five models generally yield similar results in the locations of drought and pluvial frequency changes throughout the annual cycle in response to each given SST pattern. In all of the simulations, areas with an increase in the mean drought (pluvial) conditions tend to also show an increase in the frequency of drought (pluvial) events. Additionally, areas with more frequent extreme events also tend to show higher intensity extremes. The cold Pacific anomaly increases drought occurrence in the United States and southern South America and increases pluvials in Central America and northern and central South America. The cold Atlantic anomaly increases drought occurrence in southern Central America, northern South America, and central Africa and increases pluvials in central South America. The warm Pacific and Atlantic anomalies generally lead to reversals of the drought and pluvial increases described with the corresponding cold anomalies. More modest impacts are seen in other parts of the world. The impact of the trend pattern is generally more modest than that of the two other anomaly patterns.
Findell, Kirsten L., A J Pitman, Matthew H England, and P J Pegion, June 2009: Regional and global impacts of land cover change and sea surface temperature anomalies. Journal of Climate, 22(12), DOI:10.1175/2008JCLI2580.1. Abstract
The atmospheric and land components of the Geophysical Fluid Dynamics Laboratory’s climate model CM2.1 is used with climatological sea surface temperatures (SSTs) to investigate the relative climatic impacts of historical anthropogenic land cover change (LCC) and realistic SST anomalies. The SST forcing anomalies used are analogous to signals induced by an El Nino-Southern Oscillation (ENSO), a North Atlantic Oscillation (NAO), and the background trend. Coherent areas of LCC are represented throughout much of central and eastern Europe, northern India, southeastern China, and on either side of the ridge of the Appalachian Mountains in North America. Smaller areas of change are present in various tropical regions. The land cover changes in the model are almost exclusively a conversion of forests to grasslands.
Model results show that LCC has a negligible impact on the global scale, while the SST anomalies—particularly the ENSO-like signal—have a statistically significant global impact. However, in the regions where the land surface has been altered, the impact of LCC can be equally or more important than the SST forcing patterns in determining the seasonal cycle of the surface water and energy balance. LCC also perturbs the local air temperature and rainfall at a similar level of statistical significance as the SST anomalies. This suggests that proper representation of land cover conditions is essential in the design of climate model experiments, particularly if results are to be used for regional-scale assessments of climate change impacts.
Schubert, S D., Thomas L Delworth, and Kirsten L Findell, et al., October 2009: A US CLIVAR project to assess and compare the responses of global climate models to drought-related SST forcing patterns: Overview and results. Journal of Climate, 22(19), DOI:10.1175/2009JCLI3060.1. Abstract
The U.S. Climate Variability and Predictability (CLIVAR) working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land–atmosphere feedbacks on regional drought. The runs were carried out with five different atmospheric general circulation models (AGCMs) and one coupled atmosphere–ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Niño–Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic multidecadal oscillation (AMO), and a global trend pattern.
One of the key findings is that all of the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the United States tends to occur when the two oceans have anomalies of opposite signs. Further highlights of the response over the United States to the Pacific forcing include precipitation signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. The response to the positive SST trend forcing pattern is an overall surface warming over the world’s land areas, with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all of the models.
It is hoped that these early results, as well as those reported in the other contributions to this special issue on drought, will serve to stimulate further analysis of these simulations, as well as suggest new research on the physical mechanisms contributing to hydroclimatic variability and change throughout the world.
This study examines the impact of
projected changes (A1B “marker” scenario) in emissions of four short-lived
air pollutants (ozone, black carbon, organic carbon, and sulfate) on future
climate. Through year 2030, simulated climate is only weakly dependent on
the projected levels of short-lived air pollutants, primarily the result of
a near cancellation of their global net radiative forcing. However, by year
2100, the projected decrease in sulfate aerosol (driven by a 65% reduction
in global sulfur dioxide emissions) and the projected increase in black
carbon aerosol (driven by a 100% increase in its global emissions)
contribute a significant portion of the simulated A1B surface air warming
relative to the year 2000: 0.2°C (Southern Hemisphere), 0.4°C globally,
0.6°C (Northern Hemisphere), 1.5–3°C (wintertime Arctic), and 1.5–2°C (∼40%
of the total) in the summertime United States. These projected changes are
also responsible for a significant decrease in central United States late
summer root zone soil water and precipitation. By year 2100, changes in
short-lived air pollutants produce a global average increase in radiative
forcing of ∼1 W/m2; over east Asia it exceeds 5 W/m2.
However, the resulting regional patterns of surface temperature warming do
not follow the regional patterns of changes in short-lived species
emissions, tropospheric loadings, or radiative forcing (global pattern
correlation coefficient of −0.172). Rather, the regional patterns of warming
from short-lived species are similar to the patterns for well-mixed
greenhouse gases (global pattern correlation coefficient of 0.8) with the
strongest warming occurring over the summer continental United States,
Mediterranean Sea, and southern Europe and over the winter Arctic.
Delworth, Thomas L., and Kirsten L Findell, 2007: Decadal to centennial scale changes in summer continental hydrology In Climate Variability and Change: Past, Present, and Future, John E. Kutzbach Symposium, Gisela Kutzbach, Ed., Madison, WI, Ctr. of Climatic Research, U. Wisconsin-Madison, 49-56. Abstract
Past
studies have suggested that increasing atmospheric CO2 will lead
to a substantial reduction of soil moisture during summer in the
extratropics. We revisit this topic using a new climate model developed at
NOAA's Geophysical Fluid Dynamics Laboratory. The new model has a horizontal
resolution of 2.5° longitude by 2.0° latitude, with 24 vertical levels, and
has both a diurnal and seasonal cycle of insolation. The model incorporates
substantially updated physics relative to previous versions.
Results from
earlier studies showed, among other things, an increase in wintertime
rainfall over most mid-latitude continental regions when CO2 is
doubled, an earlier snowmelt season and onset of springtime evaporation, and
a higher ratio of evaporation to precipitation in summer. These factors led
to large-scale increases in soil moisture in winter and decreases in summer
in mid-latitude in doubled-CO2 experiments. The new model shows
similar results, and the processes discussed above are important in this
model as well. In addition, we find that changes in atmospheric circulation
play an important role in regional hydrologic changes. Additional
experiments have been run to probe the causes of the circulation changes.
These simulations show that global scale sea surface temperature increases
caused by the CO2 doubling explain the majority of the
atmospheric circulation changes, while positive feedbacks from the land
surface have a secondary impact. These results highlight the importance of
global scale sea surface temperature changes for future regional hydrology
changes.
Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory’s climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments.
The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation.
The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved.
Two versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2° latitude × 2.5° longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1° in latitude and longitude, with meridional resolution equatorward of 30° becoming progressively finer, such that the meridional resolution is 1/3° at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments.
The control simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and the land model, both of which act to increase the net surface shortwave radiation in CM2.1, thereby reducing an overall cold bias present in CM2.0; and 3) a reduction of ocean lateral viscosity in the extratropics in CM2.1, which reduces sea ice biases in the North Atlantic.
Both models have been used to conduct a suite of climate change simulations for the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment report and are able to simulate the main features of the observed warming of the twentieth century. The climate sensitivities of the CM2.0 and CM2.1 models are 2.9 and 3.4 K, respectively. These sensitivities are defined by coupling the atmospheric components of CM2.0 and CM2.1 to a slab ocean model and allowing the model to come into equilibrium with a doubling of atmospheric CO2. The output from a suite of integrations conducted with these models is freely available online (see http://nomads.gfdl.noaa.gov/).
Manuscript received 8 December 2004, in final form 18 March 2005
The Geophysical Fluid Dynamics Laboratory atmosphere–land model version 2 (AM2/LM2) coupled to a 50-m-thick slab ocean model has been used to investigate remote responses to tropical deforestation. Magnitudes and significance of differences between a control run and a deforested run are assessed through comparisons of 50-yr time series, accounting for autocorrelation and field significance. Complete conversion of the broadleaf evergreen forests of South America, central Africa, and the islands of Oceania to grasslands leads to highly significant local responses. In addition, a broad but mild warming is seen throughout the tropical troposphere (<0.2°C between 700 and 150 mb), significant in northern spring and summer. However, the simulation results show very little statistically significant response beyond the Tropics. There are no significant differences in any hydroclimatic variables (e.g., precipitation, soil moisture, evaporation) in either the northern or the southern extratropics. Small but statistically significant local differences in some geopotential height and wind fields are present in the southeastern Pacific Ocean. Use of the same statistical tests on two 50-yr segments of the control run show that the small but significant extratropical differences between the deforested run and the control run are similar in magnitude and area to the differences between nonoverlapping segments of the control run. These simulations suggest that extratropical responses to complete tropical deforestation are unlikely to be distinguishable from natural climate variability.
Past studies have suggested that increasing atmospheric CO2 will lead to a significant reduction of soil moisture during summer in the extratropics. These studies showed an increase in wintertime rainfall over most mid-latitude continental regions when CO2 is doubled, an earlier snowmelt season and onset of springtime evaporation, and a higher ratio of evaporation to precipitation in summer. These factors led to large-scale increases in soil moisture in winter and decreases in summer. We find that the above processes are important in simulated summer drying in a newly developed climate model. In addition to these thermodynamic processes, we find that changes in atmospheric circulation play an important role in regional hydroclimatic changes. Additional experiments show that the atmospheric circulation changes are forced by the CO2-induced warming of the ocean, particularly the tropical ocean. These results highlight the importance of sea surface temperature changes for regional hydroclimatic changes.
The Sahel, the transition zone between the Saharan desert and the rainforests of Central Africa and the Guinean Coast, experienced a severe drying trend from the 1950s to the 1980s, from which there has been partial recovery. Continuation of either the drying trend or the more recent ameliorating trend would have far-ranging implications for the economy and ecology of the region. Coupled atmosphere/ocean climate models being used to simulate the future climate have had difficulty simulating Sahel rainfall variations comparable to those observed, thus calling into question their ability to predict future climate change in this region. We describe simulations using a new global climate model that capture several aspects of the 20th century rainfall record in the Sahel. An ensemble mean over eight realizations shows a drying trend in the second half of the century of nearly half of the observed amplitude. Individual realizations can be found that display striking similarity to the observed time series and drying pattern, consistent with the hypothesis that the observations are a superposition of an externally forced trend and internal variability. The drying trend in the ensemble mean of the model simulations is attributable to anthropogenic forcing, partly to an increase in aerosol loading and partly to an increase in greenhouse gases. The model projects a drier Sahel in the future, due primarily to increasing greenhouse gases.
Findell, Kirsten L., and E A B Eltahir, 2003: Atmospheric controls on soil moisture-boundary layer interactions. Part I: Framework development. Journal of Hydrometeorology, 4(3), 552-569. Abstract PDF
This paper investigates the influence of soil moisture on the development and triggering of convection in different early-morning atmospheric conditions. A one-dimensional model of the atmospheric boundary layer (BL) is initialized with atmospheric sounding data from Illinois and with the soil moisture set to either extremely wet (saturated) or extremely dry (20% of saturation) conditions. Two measures are developed to assess the low-level temperature and humidity structure of the early-morning atmosphere. These two measures are used to distinguish between four types of soundings, based on the likely outcome of the model: 1) those soundings favoring deep convection over dry soils, 2) those favoring deep convection over wet soils, 3) those unlikely to convect over any land surface, and 4) those likely to convect over any land surface. Examples of the first two cases are presented in detail.
The early-morning atmosphere is characterized in this work by the newly developed convective triggering potential (CTP) and a low-level humidity index, HIlow . The CTP measures the departure from a moist adiabatic temperature lapse rate in the region between 100 and 300 mb (about 1-3 km) above the ground surface (AGS). This region is the critical interface between the near-surface region, which is almost always incorporated into the growing BL, and free atmospheric air, which is almost never incorporated into the BL. Together, these two measures form the CTP-HIlow framework for analyzing atmospheric controls on soil moisture-boundary layer interactions.
Results show that in Illinois deep convection is trigged in the model 22% of the time over wet soils and only 13% of the time over dry soils. Additional testing varying the radiative conditions in Illinois and also using the 1D model with soundings from four additional stations confirm that the CTP-HIlow framework is valid for regions far removed from Illinois.
Findell, Kirsten L., and E A B Eltahir, 2003: Atmospheric controls on soil moisture-boundary layer interactions. Part II: Feedbacks within the continental United States. Journal of Hydrometeorology, 4(3), 570-583. Abstract PDF
The CTP-HIlow framework for describing atmospheric controls on soil moisture-boundary layer interactions is described in a companion paper, Part I . In this paper, the framework is applied to the continental United States to investigate how differing atmospheric regimes influence local feedbacks between the land surface and the atmosphere. The framework was developed with a one-dimensional boundary layer model and is based on two measures of atmospheric thermodynamic properties: the convective triggering potential (CTP), a measure of the temperature lapse rate between approximately 1 and 3 km above the ground surface, and a low-level humidity index, HIlow. These two measures are used to distinguish between three types of early-morning atmospheric conditions: those favoring moist convection over dry soils, those favoring moist convection over wet soils, and those that will allow or prevent deep convective activity, independent of the surface flux partitioning.
Findell, Kirsten L., and E A B Eltahir, 2003: Atmospheric controls on soil moisture-boundary layer interactions: Three-dimensional wind effects. Journal of Geophysical Research, 108(D8), 8385, DOI:10.1029/2001JD001515. Abstract PDF
This paper expands the one-dimensionally based CTP-HIlow framework for describing atmospheric controls on soil moisture-boundary layer interactions [Findell and Eltahir, 2003] to three dimensions by including low-level wind effects in the analysis. The framework is based on two measures of atmospheric thermodynamic properties: the convective triggering potential (CTP), a measure of the temperature lapse rate between approximately 1 and 3 km above the ground surface, and a low-level humidity index, HIlow. These two measures are used to distinguish between three types of early morning soundings: those favoring rainfall over dry soils, those favoring rainfall over wet soils, and those whose convective potential is unaffected by the partitioning of fluxes at the surface. The focus of this paper is the additional information gained by incorporating information about low-level winds into the CTP-HIlowframework. Three-dimensional simulations using MM5 and an analysis of observations from the FIFE experiment within this framework highlight the importance of the winds in determining the sensitivity of convection to fluxes from the land surface. A very important impact of the 3D winds is the potential for low-level backing or unidirectional winds with great shear to suppress convective potential. Because of this suppression of convection in certain wind conditions, far fewer simulations produced rain than would be anticipated based solely on the 1D framework of understanding. However, when the winds allowed, convection occurred in a manner consistent with the 1D-based expectations. Generally speaking, in the regime where dry soils were expected to have an advantage, convection was triggered over dry soils more often than over wet; in the regime where wet soils were expected to have an advantage, convection was more frequently triggered over wet soils than over dry. Additionally, when rainfall occurred in both simulations with wet soils and simulations with dry soils for a given day, rainfall depths were typically greater in the simulations with wet soils. Similarly, the FIFE data showed numerous days with convective potential but no rainfall: each of these days had low-level backing or strongly shearing winds. Four days with high humidity deficits and veering winds in the lowest 300 mbar did have rain, highlighting the enhanced buoyancy effects of low-level veering winds.
