Drought in the United States - Publications
The following is a collection of citations for thirteen GMAO drought-related publications, with summaries of each provided.
Koster, R. D., S. P. P. Mahanama, B. Livneh, D. P. Lettenmaier, R. H. Reichle, 2010: Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow. Nature Geoscience, 3, 613–616. doi: 10.1038/NGEO944
The accurate prediction of streamflow a season in advance would have obvious societal benefits, particularly in the realm of water resources planning. In the American west, streamflow prediction is generally tied to snowpack amount—a larger snowpack at the height of the snow season implies a greater streamflow during the spring melt season. The soil moisture content below the snow, however, can also be used as a predictor. If the soil below the snow is dry, snowmelt water may infiltrate the soil and be lost eventually to evaporation, whereas if it is wet, the snowmelt water will more likely run off the surface into streams and reservoirs.
Under this reasoning, knowledge of snow and soil moisture conditions during winter can both contribute to skill in forecasts of melt season streamflow. In this paper, we quantify their separate contributions to skill. Using a suite of state-of-the-art large-scale land surface process models, we perform a broad series (covering multiple decades) of March-July streamflow forecasts for the western United States in which skill is derived solely from the initialization of snow on January 1. We then perform a second series that derives skill solely from the January 1 initialization of soil moisture, and then a third that derives skill from both. Initialization values are obtained with offline integrations of the models using observed meteorological forcing up to the start of each forecast period. Skill is evaluated against measured (and naturalized—i.e., with human impacts removed) streamflow values in several large western U.S. basins. Our results show that snow information provides substantial amounts of skill in mountainous northwestern basins. Soil moisture information, however, provides a surprisingly significant amount of skill further south, sometimes (e.g., in the Colorado River Basin) more than that of snow.
In addition to isolating and quantifying these contributions, this study provides a more general, and in some ways more important, result. Streamflow forecasting today often focuses on April initialization and relies largely on systems calibrated to small basins with access to local in situ data. The present study demonstrates that today's large-scale land surface modeling systems are able to produce, without calibration, skillful forecasts of streamflow at seasonal leads.
Koster, R. D., S. D. Schubert, M. J. Suarez, 2009: Analyzing the Concurrence of Meteorological Droughts and Warm Periods, with Implications for the Determination of Evaporative Regime. J. Climate, 22, 3331–3341. doi: 10.1175/2008JCLI2718.1
A reduction of rain over the warm (growing) season can have substantial economic impacts, with costs associated with droughts sometimes extending into the billions of dollars. If a warmer-than-average period coincides with the rainfall reduction, drought-induced costs can increase further: concurrent heating leads to higher energy costs (e.g., increased air conditioning) and lower crop yields (through increased heat stress on crops). Soil moisture itself could be reduced even further, since higher temperatures promote higher evaporation; this could hamper drought recovery.
A survey of multi-decadal precipitation and temperature observations shows that in some areas—but not in others—so-called meteorological droughts (periods of reduced rainfall) do indeed tend to lead to warmer temperatures at the seasonal timescale. Our paper takes a look at this phenomenon, with the goal of explaining the geographical variations in the strength of the drought/warmth connection. A consideration of basic hydrological concepts along with an extensive analysis of numerical climate simulations shows that the observed geographical variations can indeed be explained. Simply put, warm periods do not generally accompany dry periods in wet climates (e.g., the eastern United States), because in these climates, evaporation is not sensitive to soil moisture variations, and evaporation variations represent the key source of temperature variability . more evaporation implies a greater cooling of the land surface. Warm periods are also not generally concurrent with drier-than-average periods in dry climates because soil moisture variations there are never large enough to produce sizable evaporation variations at the seasonal timescale. The dry/warmth connection is largest in the transition zone between dry and wet climates. The numerical climate model shows this pattern clearly, and the pattern matches the observational pattern very well.
A side benefit of this analysis is the identification of the areas of the globe for which evaporation is sensitive to soil moisture. To our knowledge, this represents the first time these areas have been mapped from observational data alone.
Koster, R. D., H. Wang, S. D. Schubert, M. J. Suarez, S. Mahanama, 2009: Drought-Induced Warming in the Continental United States under Different SST Regimes. J. Climate, 22, 5385–5400. doi: 10.1175/2009JCLI3075.1
A reduction of rain over the warm (growing) season can have substantial economic impacts, with costs associated with droughts sometimes extending into the billions of dollars. If a warmer-than-average period coincides with the rainfall reduction, drought-induced costs can increase further: concurrent heating leads to higher energy costs (e.g., increased air conditioning) and lower crop yields (through increased heat stress on crops).
In a previous study, through a detailed analysis of modeling results and observations, we provided a sensible explanation for why drought-induced warming might occur in some places but not in others. In the present paper, we extend the analysis by taking advantage of a number of numerical modeling experiments performed by the US-CLIVAR Drought Working Group, experiments addressing the impacts of different sea surface temperature (SST) distributions on climate in the United States. This new analysis shows that cold Pacific SSTs encourage drought-induced warming in the central United States in two distinctly different ways, relative to warm Pacific SSTs. First, the cold Pacific SSTs induce generally lower rainfall rates, and the corresponding drier conditions lead to reduced evaporation and thus higher air temperatures. Second, the drier conditions force evaporation to be more sensitive to year-to-year variations in soil moisture. That is, any given set of SSTs will produce a range of seasonal precipitation rates, some drier (by chance) than others, and for a cold Pacific, the aforementioned higher sensitivity means that the drier-by-chance values lead to greater relative warming than the drier-by-chance values produced under warm Pacific conditions. A supplemental analysis of observational data supports strongly the results of the US-CLIVAR analysis.
Koster, R. D., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 1138–1140. doi: 10.1126/science.1100217
A wetter-than-usual soil may lead to higher-than usual evaporation, which in turn may lead to increased precipitation. This soil moisture - precipitation connection, if verified and properly utilized, would contribute significantly to seasonal forecasting efforts. Seasonal forecasters could then take advantage of the fact that initialized soil moisture anomalies can persist for months.
The problem with verifying the soil moisture - precipitation connection with observational data is that the required data on the large scale do not exist and are logistically impossible to obtain. Climatologists have thus relied instead on modeling studies to quantify the connection. These modeling studies have their own limitations, however; most notably, the results can be strongly model dependent.
GLACE is an international intercomparison project designed to quantify the strength of the soil moisture - precipitation connection (the "coupling strength") across a broad range of atmospheric general circulation models. Through GLACE, we find that the different models do indeed show a broad disparity in coupling strength distribution. GLACE, however, also provides an intriguing result. Despite the intermodel disparity, certain areas of the Earth show a large coupling strength in many models, suggesting that the existence of significant coupling strength in these areas is not so model-dependent. Given the lack of observational data, such a multi-model determination of areas with strong coupling strength is arguably the best estimate of such areas attainable by any method.
To highlight these areas objectively, we average the coupling strength distributions across the twelve models participating in GLACE. The areas that survive the averaging process—i.e., the areas that are arguably not model-dependent—lie in the Great Plains of the United States, in the Sahel, and in northern India. Additional regions with lower coupling strength appear in central Asia and just south of the Amazon. If the soil moisture - precipitation connection in nature is mostly local, these "hotspots" of coupling show where soil moisture measurement with in situ or satellite sensors would provide the most benefit to seasonal forecasts.
Mahanama, S., B. Livneh, R. Koster, D. Lettenmaier, R. Reichle, 2012: Soil moisture, snow, and seasonal streamflow forecasts in the United States. J. Hydrometeorology, 13, 189–203. doi: 10.1175/JHM-D-11-046.1
The accurate prediction of streamflow a season in advance would have obvious societal benefits, particularly in the realm of water resources planning. In the American west, streamflow prediction is generally tied to snowpack amount—a larger snowpack at the height of the snow season implies a greater streamflow during the spring melt season. The soil moisture content below the snow, however, can also be used as a predictor. If the soil below the snow is dry, snowmelt water may infiltrate the soil and be lost eventually to evaporation, whereas if it is wet, the snowmelt water will more likely run off the surface into streams and reservoirs.
In a 2010 Nature Geosciences paper, we quantified the separate contributions of wintertime snow and soil moisture conditions to skill in forecasts of melt season streamflow. Using a suite of state-of-the-art large-scale land surface process models, a broad series (covering multiple decades) of March-July streamflow forecasts for the western United States were performed in which skill was derived solely from the initialization of snow on January 1. A second series was then performed that derived skill solely from the January 1 initialization of soil moisture, and a third was performed that derived skill from both. Forecast skill was evaluated against measured (and naturalized—i.e., with human impacts removed) streamflow values in several large western U.S. basins.
Here, in the present study, we expand considerably on the 2010 paper by generating forecasts across a wider array of basins and for a full complement of forecast start dates. With these expanded forecasts, we find that while spring forecast skill mostly stems from snow initialization, the contribution of soil moisture to skill dominates in other seasons. Forecasts for streamflow 5 or 6 months into the future can extract some skill from the initialization. A statistical analysis is performed that has the net effect of quantifying the potential for useful skill outside our measured basins.
Schubert, S., H. Wang, M. Suarez, R. Koster, 2011: Understanding and Predicting Drought on Subseasonal to Decadal and Longer Time Scales. WCRP Workshop on Drought Predictability and Prediction in a Changing Climate: Assessing Current Knowledge and Capabilities, User Requirements and Research Priorities. Barcelona, Spain, World Climate Research Programme. (Available online at http://drought.wcrp-climate.org/workshop/Talks/Schubert.pdf)
Drought is fundamentally the result of an extended period of reduced precipitation lasting anywhere from a few weeks to decades, and even longer. As such, addressing drought predictability and prediction in a changing climate requires foremost that we make progress on the ability to predict precipitation anomalies on subseasonal and longer time scales. From the perspective of the users of drought forecasts and information, drought is however most directly viewed through its impacts (e.g. on soil moisture, streamflow, crop yields). As such, the question of the predictability of drought must extend to those quantities as well.
Summary report for the WCRP Workshop on Drought Predictability and Prediction in a Changing Climate: http://drought.wcrp-climate.org/workshop/ICPO_161_WCRP_Report.pdf
Schubert, S., and Coauthors, 2009: A U.S. CLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results. J. Climate, 22, 5251–5272. doi: http://dx.doi.org/10.1175/2009JCLI3060.1
In recognition of the profound societal impact of drought in many regions of the world the United States Climate Variability and Predictability (U.S. CLIVAR) program recently formed a drought working group with the aim of accelerating progress in the understanding and prediction of long-term (multi-year) drought over North America and other drought-prone regions of the world, including an assessment of the impact of climate change. A key focus of the working group was to address a number of uncertainties about the manner in which long-term changes in sea surface temperatures (SSTs) in the different ocean basins affect regional drought and the extent to which land processes can act to magnify droughts. In order to accomplish this, the working group initiated a series of global climate model simulations, in which the models were driven (forced) by the leading patterns of year-to-year SST variability in the Pacific and Atlantic, and a global trend pattern. The runs were carried out with five different atmospheric general circulation models (AGCMs), and one coupled atmosphere-ocean model. This paper provides an overview of the results as well as information about how to access the data for those interested in carrying out further analysis of the model simulations.
One of the key findings is that all the AGCMs produce broadly similar 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 U.S. tends to occur when the two oceans have anomalies of opposite sign. That is, a cold Pacific and warm Atlantic tend to produce the largest precipitation reductions, whereas a warm Pacific and cold Atlantic tend to produce the greatest precipitation enhancements. 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. Such regional differences among the models in the response to the trend forcing highlight the challenge of predicting regional impacts of global warming.
This paper is slated to be part of a special issue of the Journal of Climate on drought. It is hoped that the early results from this study, as well as those reported in the other contributions to the special issue 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.
Schubert, S. D., M. J. Suarez, P. J. Pegion, R. D. Koster, J. T. Bacmeister, 2006: Potential predictability of long-term drought and pluvial conditions in the United States Great Plains. J. Climate, 21, 802–816. doi: http://dx.doi.org/10.1175/2007JCLI1741.1
In this study we investigate the reasons for why droughts seem to be less predictable than wet conditions over the United States Great Plains. At least that is what the results of century-long simulations of past climate variability with an atmospheric general circulation model tell us. In particular we find that, in an ensemble of model runs forced with the 20th century observed sea surface temperatures, periods of drought are less reproducible than periods of wet conditions.
We examine several possible reasons for this, including the differing impact of El Niño/Southern Oscillation's on the large scale circulation, the possible role of Atlantic sea surface temperatures in forcing changes in the Bermuda high and the associated influx of moisture into the continent, and differences in how soil moisture changes feed back on the atmosphere during wet and dry soil conditions. We find that the changes in predictability are primarily driven by changes in the strength of the land-atmosphere coupling, such that under dry conditions a given change in soil moisture produces a larger change in evaporation and hence precipitation than the same change in soil moisture would produce under wet soil conditions. The above changes in predictability are associated with a distinctive change in the probability distribution (negative skewness) in the seasonal mean precipitation during the warm season—something that is also found in the observations, though to a lesser degree.
Schubert, S. D., M. J. Suarez, P. J. Pegion, R. D. Koster, J. T. Bacmeister, 2004: On the cause of the 1930s dust bowl. Science, 303, 1855–1859. doi: 10.1126/science.1095048
The 1930s was characterized by a decade of rainfall deficits and high temperatures that desiccated much of the United States Great Plains. Numerous dust storms created one of the most severe environmental catastrophes in U.S. history and led to the popular characterization of much of the southern Great Plains as the "Dust Bowl." In this study, we show that the origin of the drought was in the anomalous tropical sea surface temperatures that occurred during that decade. We further show that interactions between the atmosphere and the land surface were essential to the development of the severe drought conditions. The results are based on simulations with the NASA Seasonal-to-Interannual Prediction Project general circulation model forced with observed and idealized sea surface temperatures. We contrast the 1930s drought with other major droughts of the 20th century, and speculate on the possibility of another Dust Bowl developing in the foreseeable future.
Schubert, S. D., M. J. Suarez, P. J. Pegion, R. D. Koster, J. T. Bacmeister, 2004: Causes of long-term drought in the U.S. Great Plains. J. Climate, 17, 485–503. doi: 10.1175/1520-0442(2004)017<0485:COLDIT>2.0.CO;2
The United States Great Plains experienced a number of long-term droughts during the last century, most notably the droughts of the 1930s and 1950s. In this study, we examined the causes of such droughts using long-term (70-year, 1930–1999) simulations of the global atmosphere using an atmosphere/land general circulation model (AGCM) developed as part of the NASA Seasonal-to-Interannual Prediction Project. The AGCM is forced during the 70-year integration with the observed sea surface temperatures (SSTs), and our interest is in how the atmosphere and land respond to that forcing on long (multi-year) time scales. To do this we actually carry out several (nine) different 70-year simulations with exactly the same SST forcing but where each run starts out from slight different atmospheric/land initial conditions. From these runs, we are able to determine what part of the variations in, for example, precipitation, are forced by the SST (the average of the nine runs), and what part of the variations are not forced by the SST (the internally-generated variability determined from the deviations about the average of the nine runs).
Wang, H., S. Schubert, M. Suarez, R. Koster, 2010: The Physical Mechanisms by Which the Leading Patterns of SST Variability Impact U.S. Precipitation. J. Climate, 23, 1815–1836. doi: 10.1175/2009JCLI3188.1
This study uses the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) AGCM to investigate the physical mechanisms by which the leading patterns of annual mean SST variability impact U.S. precipitation. The focus is on a cold Pacific pattern and a warm Atlantic pattern that exert significant drought conditions over the U.S. continent. The precipitation response to the cold Pacific is characterized by persistent deficits over the Great Plains that peak in summer with a secondary peak in spring, and weakly pluvial conditions in summer over the Southeast (SE). The precipitation response to the warm Atlantic is dominated by persistent deficits over the Great Plains with the maximum deficit occurring in late summer. The precipitation response to the warm Atlantic is overall similar to the response to the cold Pacific with, however, considerably weaker amplitude.
An analysis of the atmospheric moisture budget combined with a stationary wave model diagnosis of the associated atmospheric circulation anomalies is conducted to investigate mechanisms of the precipitation responses. A key result is that, while the cold Pacific and warm Atlantic are two spatially distinct SST patterns, they nevertheless produce similar diabatic heating anomalies over the Gulf of Mexico during the warm season. In the case of the Atlantic forcing, the heating anomalies are a direct response to the SST anomalies, whereas in the case of Pacific forcing they are a secondary response to circulation anomalies forced from the tropical Pacific. The diabatic heating anomalies in both cases force an anomalous low-level cyclonic flow over the Gulf of Mexico that leads to reduced moisture transport into the central United States and increased moisture transport into the eastern United States. The precipitation deficits over the Great Plains in both cases are greatly amplified by the strong soil moisture feedback in the NSIPP-1 AGCM. In contrast, the response over the SE to the cold Pacific during spring is primarily associated with an upper-tropospheric high anomaly over the southern United States that is remotely forced by tropical Pacific diabatic heating anomalies, leading to greatly reduced stationary moisture flux convergences and anomalous subsidence in that region. Moderately reduced evaporation and weakened transient moisture flux convergences play secondary roles. It is only during spring that these three terms are all negative and constructively contribute to produce the maximum dry response in spring.
The above findings based on the NSIPP-1 AGCM are generally consistent with observations, as well as with four other AGCMs included in the U.S. Climate Variability and Predictability (CLIVAR) project.
Wang, A., T. J. Bohn, D. P. Lettenmaier, S. P. P. Mahanama, R. D. Koster, 2008: Multi-model ensemble reconstruction of drought over the continental United States. J. Climate, 22, 2694–2712. doi: 10.1175/2008JCLI2586.1
This study examines the "agricultural droughts" (i.e., the soil moisture deficits) produced by six different land surface models over the continental United States when they are driven for over 80 years with observations-based meteorological forcing. All six models are found to produce reasonable representations of known historical droughts, with plausible spatial extents and severities. The models showed many disagreements regarding details, however, with more disagreements in the west than in the east. The results serve to provide insight into how to develop a real-time system for monitoring soil moisture conditions using such a suite of land surface models.
Weaver, S. J., S. Schubert, H. Wang, 2009: Warm Season Variations in the Low-Level Circulation and Precipitation over the Central United States in Observations, AMIP Simulations, and Idealized SST Experiments. J. Climate, 22, 5401–5420. doi: 10.1175/2009JCLI2984.1
The central U.S. is a hydroclimatically and economically sensitive region given its agricultural prominence and significant warm season precipitation variability. The proximity of this region to the Rocky Mountains, Gulf of Mexico, and Atlantic and Pacific Oceans provides a unique combination of potential climate influences. As such, the central U.S. is prone to drought and pluvial conditions, highlighted most recently by the flooding during the spring of 2008. Given the recent evidence for SST variability in producing precipitation anomalies over the Great Plains on seasonal to interannual timescales, it is necessary to understand the mechanisms through which slowly varying SST modes generate regional hydroclimate variability. In this initial study we focus on an important mechanism for central U.S. warm season precipitation, the Great Plains low-level jet (GPLLJ).
