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Despite the key importance of soil moisture-evapotranspiration (ET) coupling in the climate system, limited availability of soil moisture and ET observations poses a major impediment for investigation of this coupling regarding spatiotemporal characteristics and potential modifications under climate change. To better understand and quantify soil moisture-ET coupling and relevant processes, this study takes advantage of in situ soil moisture observations from the U.S. Climate Reference Network (USCRN) for the time period of 2010-17 and a satellite-derived version of the evapotranspiration stress index (ESI), which represents anomalies in a normalized ratio of actual to reference ET. The analyses reveal strong seasonality and regional characteristics of the ESI-land surface interactions across the United States, with the strongest control of soil moisture on the ESI found in the southern Great Plains during spring, and in the north-central United States, the northern Great Plains, and the Pacific Northwest during summer. In drier climate regions such as the northern Great Plains and north-central United States, soil moisture control on the ESI is confined to surface soil layers, with subsurface soil moisture passively responding to changes in the ESI. The soil moisture-ESI interaction is more uniform between surface and subsurface soils in wetter regions with higher vegetation cover. These results provide a benchmark for simulation of soil moisture-ET coupling and are useful for projection of associated climate processes in the future. [ABSTRACT FROM AUTHOR]

Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation-Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5-3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded. [ABSTRACT FROM AUTHOR]

Increased atmospheric evaporative demand has important implications for humans and ecosystems in water-scarce lands. While temperature plays a significant role in driving evaporative demand and its trend, other climate variables are also influential and their contributions to recent trends in evaporative demand are unknown. We address this gap with an assessment of recent (1980-2020) trends in annual reference evapotranspiration (ETo) and its drivers across the continental United States based on five gridded datasets. In doing so, we characterize the structural uncertainty of ETo trends and decompose the relative influences of temperature, wind speed, solar radiation, and humidity. Results highlight large and robust changes in ETo across much of the western United States, centered on the Rio Grande region where ETo increased 135-235 mm during 1980-2020. The largest uncertainties in ETo trends are in the central and eastern United States and surrounding the Upper Colorado River. Trend decomposition highlights the strong and widespread influence of temperature, which contributes to 57% of observed ETo trends, on average. ETo increases are mitigated by increases in specific humidity in non-water-limited regions, while small decreases in specific humidity and increases in wind speed and solar radiation magnify ETo increases across the West. Our results show increases in ETo across the West that are already emerging outside the range of variability observed 20-40 years ago. Our results suggest that twenty-first-century land and water managers need to plan for an already increasing influence of evaporative demand on water availability and wildfire risks. [ABSTRACT FROM AUTHOR]

Extreme daily precipitation contributes to flooding that can cause significant economic damages, and so is important to properly capture in gridded meteorological datasets. This work examines precipitation extremes, the mean precipitation on wet days, and fraction of wet days in two widely used gridded datasets over the conterminous United States. Compared to the underlying station observations, the gridded data show a 27% reduction in annual 1-day maximum precipitation, 25% increase in wet day fraction, 1.5–2.5 day increase in mean wet spell length, 30% low bias in 20-yr return values of daily precipitation, and 25% decrease in mean precipitation on wet days. It is shown these changes arise primarily from the time adjustment applied to put the precipitation gauge observations into a uniform time frame, with the gridding process playing a lesser role. A new daily precipitation dataset is developed that omits the time adjustment (as well as extending the gridded data by 7 years) and is shown to perform significantly better in reproducing extreme precipitation metrics. When the new dataset is used to force a land surface model, annually averaged 1-day maximum runoff increases 38% compared to the original data, annual mean runoff increases 17%, evapotranspiration drops 2.3%, and fewer wet days leads to a 3.3% increase in estimated solar insolation. These changes are large enough to affect portrayals of flood risk and water balance components important for ecological and climate change applications across the CONUS. [ABSTRACT FROM AUTHOR]

The Mississippi River basin (MRB) is a flash flood hotspot receiving the most frequent flash floods and highest average rainfall accumulation of any region in the United States. Given the destruction flash floods cause in the current climate in the MRB, it is critical to understand how they will change in a future, warmer climate in order to prepare for these impacts. Recent work utilizing convection-permitting climate simulations to analyze future precipitation changes in flash flood--producing storms in the United States shows that the MRB experiences the greatest future increase in flash flood rainfall. This result motivates the goal of the present study to better understand the changes to precipitation characteristics and vertical velocity in flash flood--producing storms in the MRB. Specifically, the variations in flash flood--producing storm characteristics related to changes in vertical velocity in the MRB are examined by identifying 484 historical flash flood--producing storms from 2002 and 2013 and studying how they change in a future climate using 4-km convection-permitting simulations under a pseudo--global warming framework. In a future climate, precipitation and runoff increase by 17% and 32%, respectively, in flash flood--producing storms in the MRB. While rainfall increases in all flash flood--producing storms due to similar increases in moisture, it increases the most in storms with the strongest vertical velocity, suggesting that storm dynamics might modulate future changes in rainfall. These results are necessary to predict and prepare for the multifaceted impacts of climate change on flash flood--producing storms in order to create more resilient communities. [ABSTRACT FROM AUTHOR]

Flash floods are high-impact events that can result in massive destruction, such as the May 2010 flash floods in the south-central United States that resulted in over $2 billion of damage. While floods in the current climate are already destructive, future flood risk is projected to increase based on work using global climate models. However, global climate models struggle to resolve precipitation structure, intensity, and duration, which motivated the use of convection-permitting climate models that more accurately depict these precipitation processes on a regional scale due to explicit representation of convection. These high-resolution convection-permitting simulations have been used to examine future changes to rainfall, but not explicitly floods. This study aims to fill this gap by examining future changes to rainfall characteristics and runoff in flash flood-producing storms over the United States using convection-permitting models under a pseudo-global warming framework. Flash flood accumulated rainfall increases on average by 21% over the United States in a future climate. Stormgenerated runoff increases by 50% on average, suggesting increased runoff efficiency in future flash flood-producing storms. In addition to changes in nonmeteorological factors, which were not explored in this study, increased future runoff is possible due to the 7.5% K-1 increase in future hourly maximum rain rates. Though this median change in rain rates is consistent with Clausius-Clapeyron theory, some storms exhibit increased future rain rates well above this, likely associated with storm dynamics. Overall, results suggest that U.S. cities might need to prepare for more intense flash flood-producing storms in a future climate. [ABSTRACT FROM AUTHOR]

Meteorological droughts in the continental United States (CONUS) are known to oscillate at the multidecadal time scale in response to the sea surface temperatures (SST) variability over the Pacific Ocean and the North Atlantic Ocean. While previous studies have focused on understanding the influence of SST oscillations on drought frequency over the CONUS, this information has not been integrated with global warming for future drought risk assessment at the decadal scale. In this study, we use the support vector machines (SVMs) to handle correlation between input variables for quantifying the influence of internal variability [Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO)] and global warming on the decadal changes in the severity of seasonal droughts over the CONUS during 1901–2015. The regional drivers of drought severity identified using SVMs are used for the assessment of decadal drought risk in the near future. We find internal variability as the dominant driver of decadal changes in drought severity in the southern and central Great Plains and global warming as the dominant driver for the southeastern and southwestern United States. In the southern Plains, the existing pattern of increasing drought severity is likely to persist in the near future if AMO and PDO remain in their positive and negative phases, respectively, while global warming is likely to contribute to increasing drought severity in the Southeast and Southwest. This study suggests an emerging role of global warming in drought risk over the southern states, where near-term climate change adaptation is necessary. [ABSTRACT FROM AUTHOR]

For 14 alternative climate futures, water yield and snow water equivalent (SWE) throughout the contiguous United States (CONUS) were projected over the twenty-first century using the Variable Infiltration Capacity model (VIC). The futures correspond to climate projections from seven CMIP5 models each forced by two representative concentration pathways for greenhouse gases (RCP4.5 and RCP8.5). With both RCPs, decreases in water yields are projected for roughly two-thirds of the CONUS, and in 60% of that area-mainly at more northern latitudes, where the greatest temperature increases are expected-this occurs despite projected increases in precipitation. The greatest relative decreases in yield are projected for the southern Great Plains and the Southwest, where temperature and precipitation changes combine to decrease yield. Snow accumulation is projected to decrease almost everywhere by the latter half of the century, with the time of peak SWE in some basins projected to occur up to 2 months earlier than it now does. These changes, should they come to pass, will challenge the adaptation capacity of future water management. [ABSTRACT FROM AUTHOR]

Recent analyses of extreme hydrological events across the United States, including those summarized in the recent U.S. Third National Climate Assessment (May 2014), show that extremely large (extreme) precipitation and streamflow events are increasing over much of the country, with particularly steep trends over the northeastern United States. The authors demonstrate that the increase in extreme hydrological events over the northeastern United States is primarily a warm season phenomenon and is caused more by an increase in frequency than magnitude. The frequency of extreme warm season events peaked during the 2000s; a secondary peak occurred during the 1970s; and the calmest decade was the 1960s. Cold season trends during the last 30-50 yr are weaker. Since extreme precipitation events in this region tend to be larger during the warm season than during the cold season, trend analyses based on annual precipitation values are influenced more by warm season than by cold season trends. In contrast, the magnitude of extreme streamflow events at stations used for climatological analyses tends to be larger during the cold season: therefore, extreme event analyses based on annual streamflow values are overwhelmingly influenced by cold season, and therefore weaker, trends. These results help to explain an apparent discrepancy in the literature, whereby increasing trends in extreme precipitation events appear to be significant and ubiquitous across the region, while trends in streamflow appear less dramatic and less spatially coherent. [ABSTRACT FROM AUTHOR]

Water managers across the United States face the need to make informed policy decisions regarding long-term impacts of climate change on water resources. To provide a scientifically informed basis for this, the evolution of important components of the basin-scale water balance through the end of the twenty-first century is estimated. Bias-corrected and spatially downscaled climate projections, from phase 3 of the Coupled Model Intercomparison Project (CMIP3) of the World Climate Research Programme, were used to drive a spatially distributed Variable Infiltration Capacity (VIC) model of hydrologic processes in the Salt-Verde basin in the southwestern United States. From the suite of CMIP3 models, the authors select a five-model subset, including three that best reproduce the historical climatology for the study region, plus two others to represent wetter and drier than model average conditions, so as to represent the range of GCM prediction uncertainty. For each GCM, data for three emission scenarios (A1B, A2, and B1) were used to drive the hydrologic model into the future. The projections of this model ensemble indicate a statistically significant 25% decrease in streamflow by the end of the twenty-first century. The primary cause for this change is due to projected decreases in winter precipitation accompanied by significant (temperature driven) reductions in storage of snow and increased winter evaporation. The results show that water management in central Arizona is highly likely to be impacted by changes in regional climate. [ABSTRACT FROM AUTHOR]