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On seasonal time scales, vapor pressure deficit (VPD) is a known predictor of burned area in the southwestern United States ("the Southwest"). VPD increases with atmospheric warming due to the exponential relationship between temperature and saturation vapor pressure. Another control on VPD is specific humidity, such that increases in specific humidity can counteract temperature-driven increases in VPD. Unexpectedly, despite the increased capacity of a warmer atmosphere to hold water vapor, near-surface specific humidity decreased from 1970 to 2019 in much of the Southwest, particularly in spring, summer, and fall. Here, we identify declining near-surface humidity from 1970 to 2019 in the southwestern United States with both reanalysis and in situ station data. Focusing on the interior Southwest in the months preceding the summer forest fire season, we explain the decline in terms of changes in atmospheric circulation and moisture fluxes between the surface and the atmosphere. We find that an early spring decline in precipitation in the interior region induced a decline in soil moisture and evapotranspiration, drying the lower troposphere in summer. This prior season precipitation decline is in turn related to a trend toward a Northern Hemisphere stationary wave pattern. Finally, using fixed humidity scenarios and the observed exponential relationship between VPD and burned forest area, we estimate that with no increase in temperature at all, the humidity decline alone would still lead to nearly one-quarter of the observed VPD-induced increase in burned area over 1984–2019. Significance Statement: Burned forest area has increased significantly in the southwestern United States in recent decades, driven in part by an increase in atmospheric aridity [vapor pressure deficit (VPD)]. Increases in VPD can be caused by a combination of increasing temperature and decreasing specific humidity. As the atmosphere warms with climate change, its capacity to hold moisture increases. Despite this, there is a decrease in near-surface air humidity in the interior southwestern United States over 1970–2019, which during the summer is likely caused by a decline in early spring precipitation leading to limited soil moisture and evaporation in spring and summer. We estimate that this declining humidity alone, without an increase in temperature, would cause about one-quarter of the VPD-induced increase in burned forest area in this region over 1984–2019. [ABSTRACT FROM AUTHOR]

The serial occurrence of atmospheric rivers (ARs) along the US West Coast can lead to prolonged and exacerbated hydrologic impacts, threatening flood‐control and water‐supply infrastructure due to soil saturation and diminished recovery time between storms. Here a statistical approach for quantifying subseasonal temporal clustering among extreme events is applied to a 41‐year (1979–2019) wintertime AR catalog across the western United States (US). Observed AR occurrence, compared against a randomly distributed AR timeseries with the same average event density, reveals temporal clustering at a greater‐than‐random rate across the western US with a distinct geographical pattern. Compared to the Pacific Northwest, significant AR clusters over the northern Coastal Range of California and Sierra Nevada are more frequent and occur over longer time periods. Clusters along the California Coastal Range typically persist for 2 weeks, are composed of 4–5 ARs per cluster, and account for over 85% of total AR occurrence. Across the northwest Coast‐Cascade Ranges, clusters account for ∼50% of total AR occurrence, typically last 8–10 days, and contain 3–4 individual AR events. Based on precipitation data from a high‐resolution dynamical downscaling of reanalysis, the fractions of total and extreme hourly precipitation attributable to AR clusters are largest along the northern California coast and in the Sierra Nevada. Interannual variability among clusters highlights their importance for determining whether a particular water year is anomalously wet or dry. The mechanisms behind this unusual clustering are unclear and require further research. Plain Language Summary: Atmospheric rivers, or long narrow regions of enhanced water vapor transport, are an important component of the midlatitude water cycle, responsible for producing precipitation and associated extremes. Atmospheric rivers occurring close in time or one after another can lead to exaggerated impacts due to the decreased time between periods of precipitation. Based on the historical record, we identify the timescales at which wintertime atmospheric rivers cluster at a rate different from what would be expected by random chance over the western United States. Compared to the Pacific Northwest, atmospheric river clusters over the mountainous regions of California occur more frequently, over longer periods of time, and account for a larger proportion of total atmospheric river occurrence. Atmospheric rivers in this region are also responsible for a large fraction of total precipitation and are commonly associated with precipitation extremes. The year‐to‐year occurrence of clusters is important for determining wet versus dry years. Future work will identify the atmospheric patterns behind atmospheric river clustering over different geographies. Key Points: Atmospheric rivers (ARs) temporally cluster at a greater‐than‐random rate across the western United States (US) with a distinct geographical patternCompared to the Northwest, Southwest clusters are longer‐lived, consist of more ARs and account for a larger fraction of total AR occurrenceA considerable fraction of western US total and extreme hourly precipitation is attributable to AR clusters [ABSTRACT FROM AUTHOR]

A cooling trend in summer (May-August) daytime temperatures since the mid-twentieth century over the central United States contrasts with strong warming of the western and eastern United States. Prior studies based on data through 1999 suggested that this so-called warming hole arose mainly from internal climate variability and thus would likely disappear. Yet it has prevailed for two more decades, despite accelerating global warming, compelling reexamination of causes that in addition to natural variability could include anthropogenic aerosol-induced cooling, hydrologic cycle intensification by greenhouse gas increases, and land use change impacts. Here we present evidence for the critical importance of hydrologic cycle change resulting from ocean-atmosphere drivers. Observational analysis reveals that the warming hole's persistence is consistent with unusually high summertime rainfall over the region during the first decades of the twenty-first century. Comparative analysis of large ensembles from four different climate models demonstrates that rainfall trends since the mid-twentieth century as large as observed can arise (although with low probability) via internal atmospheric variability alone, which induce warming-hole-like patterns over the central United States. In addition, atmosphereonly model experiments reveal that observed sea surface temperature changes since the mid-twentieth century have also favored central U.S cool/wet conditions during the early twenty-first century. We argue that this latter effect is symptomatic of external radiative forcing influences, which, via constraints on ocean warming patterns, have likewise contributed to persistence of the U.S. warming hole in roughly equal proportion to contributions by internal variability. These results have important ramifications for attribution of extreme events and predicting risks of record-breaking heat waves in the region. [ABSTRACT FROM AUTHOR]

Accurate representation of mesoscale scale convective systems (MCSs) in climate models is of vital importance to understanding global energy, water cycles, and extreme weather. In this study, we evaluate the simulated MCS features over the United States from the newly developed GFDL global high-resolution (∼50 km) AM4 model by comparing them with the observations during spring to early summer (April–June) and late summer (July–August). The results show that the spatial distribution and seasonality of occurrence and genesis frequency of MCSs are reasonably simulated over the central United States in both seasons. The model reliably reproduces the observed features of MCS duration, translation speed, and size over the central United States, as well as the favorable large-scale circulation pattern associated with MCS development over the central United States during spring and early summer. However, the model misrepresents the amplitude and the phase of the diurnal cycle of MCSs during both seasons. In addition, the spatial distribution of occurrence and genesis frequency of MCSs over the eastern United States is substantially overestimated, with larger biases in early spring and summer. Furthermore, while large-scale circulation patterns are reasonably simulated in spring and early summer, they are misrepresented in the model during summer. Finally, we examine MCS-related precipitation, finding that the model overestimates MCS-related precipitation during spring and early summer, but this bias is insufficient to explain the significant dry bias observed in total precipitation over the central United States. Nonetheless, the dry biases in MCS-associated precipitation during late summer likely contribute to the overall precipitation deficit in the model. [ABSTRACT FROM AUTHOR]

The terrestrial water cycle intensity (WCI) is a widely used tool to quantify the impact of climate change on the distribution of global water resources. In this study, a satellite-based WCI was tested by comparing the parameter-elevation regressions on independent slopes model (PRISM) precipitation estimates with those of the Global Precipitation Measurement (GPM) satellite mission across the contiguous United States (CONUS), based on an existing Köppen–Geiger climate classification for the CONUS. Both precipitation products were not statistically different across all climate classes. Consequently, satellite-based WCI changes between two multiannual periods (2001 to 2009 and 2010 to 2019) were calculated at a 0.1-degree spatial resolution using the GPM and a validated global evapotranspiration dataset. This study showed that: (1) The water cycle is speeding up in many parts of the CONUS, particularly the West, driven by recent increases in both precipitation and evapotranspiration through much of the region. (2) The El Niño-Southern Oscillation (ENSO) may be influencing the WCI of the CONUS by driving precipitation in the west, southeast, and parts of the north, and dryness in the northeast regions. The hydrological impacts of these results cannot be generalized. However, flood and drought risks, water availability and quality issues remain key primary concerns. [ABSTRACT FROM AUTHOR]

Despite the emerging influence of anthropogenic climate change on the global water cycle, at regional scales the combination of observational uncertainty, large internal variability, and modeling uncertainty undermine robust statements regarding the human influence on precipitation. Here, we use output from global climate models in a perfect-data sense to develop a framework for conducting regional detection and attribution (D&A) for precipitation, starting with the contiguous United States (CONUS) where observational uncertainty is lower than in other regions. Our unified approach can simultaneously detect systematic trends in mean and extreme precipitation, attribute trends to anthropogenic forcings, compute the effects of forcings as a function of time, and map the effects of individual forcings. Model output is used to conduct a set of tests that yield a parsimonious representation for characterizing seasonal precipitation over the CONUS for the historical record (1900 to present day), which ensures our D&A is insensitive to structural uncertainty. Our framework is developed using synthetic data in a Pearl-causal perspective wherein causality can be identified using intervention-based simulations. While the hypothesis-based framework and accompanying generalized D&A formula we develop should be widely applicable, we include a strong caution that the hypothesis-guided simplification of the formula for the historical climatic record of CONUS as described in this paper will likely fail to hold in other geographic regions and under future warming. [ABSTRACT FROM AUTHOR]

Mississippi River basin floods impart large socioeconomic impacts over the central United States. Improving flood predictability depends on our understanding of the dynamical controls on Mississippi basin hydroclimate. However, short instrumental records make it difficult to constrain the connections between flooding and climate variability. Here, we use the Paleo Hydrodynamics Data Assimilation product, spanning the Last Millennium, to investigate the impacts of tropical Pacific and North Atlantic sea surface temperature (SST) variability on hydrological extremes across the Mississippi River and its major tributaries. Wet extremes are associated with strong El Niño‐like warming over the tropical Pacific, but specific SST patterns matter: dry (wet) conditions occur during Central Pacific (Eastern Pacific) El Niño events. The influence of North Atlantic SSTs is less clear, but cool SSTs contribute to Ohio basin wet extremes. These results are relevant for seasonal‐to‐interannual flood hazard prediction on the fourth largest river basin in the world. Plain Language Summary: Large floods on the Mississippi River during the last century have proven costly, both in economic and social terms. To improve flood hazard prediction, it is critical to understand how patterns in Earth's climate system contribute to Mississippi floods. However, relatively few flooding events occurred during the 20th century, which limits our ability to evaluate the statistics of these events. This work seeks to use records of past climate (from archives such as corals, ice cores, and trees) spanning the last 1,000 years to investigate the drivers of Mississippi flooding. Specifically, we focus on how sea surface temperature (SST) changes over the tropical Pacific and North Atlantic affect the hydrological cycle over the basin. We find that very wet periods are strongly associated with warm SSTs in the eastern tropical Pacific, but central tropical Pacific warming causes dry conditions. The impact of North Atlantic SST variability is much weaker, but, in combination with tropical Pacific warming, cool SSTs over the North Atlantic can amplify wet conditions over the eastern Mississippi River basin's tributaries. Our results harbor implications for seasonal‐to‐interannual flood hazard prediction, and can help stakeholders prepare for and mitigate flooding in the 21st century. Key Points: We investigate the drivers of Mississippi River basin hydroclimate extremes over the last millenniumPaleoclimate data assimilation reveals dry (wet) conditions during central Pacific (eastern Pacific) El Niño eventsSelf‐organizing maps expose a North Atlantic tripole pattern which modulates moisture supply over the Ohio river basin [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) play a key role in regulating variability in the U.S. water and energy cycle. Here a hierarchical dissection of the multiscale forcing of springtime MCSs is carried out through a two-step classification process. Hierarchical clustering is first applied to spatiotemporally evolving upper-tropospheric height fields to reveal large-scale forcing patterns of MCSs. Five distinct forcing patterns (clusters) are identified with three being "remotely forced" and two associated with "local growth." The upper-level troughs associated with these forcing patterns create broad envelopes downstream within which large-scale ascent and MCS genesis tend to occur. Further classification of MCSs based on MCS track locations reveals that local dynamic and thermodynamic forcing determines the precise locations of MCS genesis in the envelope created by large-scale forcing. Specifically, MCSs often occur near surface fronts in warm sectors of surface low pressure systems and are accompanied by low-level kinematic and moisture convergence driven by low-level jets (LLJs). Nearly 50% of spring MCSs are associated with potential instability realized through frontal lifting, and the highest probability of MCS genesis is seen with an environmental CAPE of ∼1400 J kg−1 and CIN of ∼150 J kg−1. The positive trend of the U.S. MCS genesis frequency observed in recent decades is found to be driven by the cluster of MCSs forced at large scale by the Pacific storm track. Regression analysis further suggests that the growing phase of the Pacific decadal oscillation (PDO) modulates the associated MCS large-scale forcing and is ultimately responsible for the positive MCS trend. Significance Statement: The purpose of this study is to provide a systematic classification of multiscale forcing factors triggering mesoscale convective system development over the United States. These storms are very active in spring and often lead to intense rainfall and other weather hazards such as lightning, hail, and tornadoes. They play a key role in the U.S. hydrological cycle and have been occurring more frequently over the past several decades. Our study reveals the detailed characteristics of atmospheric forcing leading to these storms. Such information lays theoretical grounds for designing prediction schemes of warm season severe weather and provides guidance for model development to improve climate models' simulation and long-term projection of these storms. [ABSTRACT FROM AUTHOR]

The Colorado River is a critical water resource in the southwestern United States, supplying drinking water for 40 million people in the region and water for irrigation of 2.2 million hectares of land. Extended drought in the Upper Colorado River Basin (UCOL) and the prospect of a warmer climate in the future pose water availability challenges for those charged with managing the river. Limited water availability in the future also may negatively affect aquatic ecosystems and wildlife that depend upon them. Water availability components of special importance in the UCOL include streamflow, salinity in groundwater and surface water, groundwater levels and storage, and the role of snow in the UCOL water cycle. This manuscript provides a review of current "state of the science" for these UCOL water availability components with a focus on identifying gaps in data, modeling, and trends in the basin. Trends provide context for evaluations of current conditions and motivation for further investigation and modeling, models allow for investigation of processes and projections of future water availability, and data support both efforts. Information summarized in this manuscript will be valuable in planning integrated assessments of water availability in the UCOL. [ABSTRACT FROM AUTHOR]

Since the infamous extreme drought of the 1960s, the climate of the northeastern United States (NEUS) has generally trended toward warmer and wetter conditions. Nonetheless, there is mounting evidence that short-term droughts will continue to pose a significant risk for this region. To better explore the processes governing events such as these, climate models have adopted more complex representations of the fully coupled atmosphere–land–ocean–sea ice system; however, large uncertainties in future projections still persist, with internal variability necessitating large ensembles to understand trends in both rare and high-impact extreme events such as rapidly developing droughts (a term here that includes flash droughts developing on monthly scales). In this study, seven large ensemble (LE) models are employed to answer the outstanding question: How are the frequency and character of drought in the NEUS changing under a warming climate? We find that most LE models indicate the NEUS will experience a long-term wetting trend with more "extremely wet" months, but also more frequent short-term extreme droughts. These changes are associated with increasing precipitation, atmospheric water demand, and climate variability. We also conclude that discrepant trends in precipitation and evapotranspiration variability will lead to increasing anticorrelation of these variables, which is relevant to the intensification of rapidly developing drought, particularly in the spring season. These changes are associated with an increase in evapotranspiration from plants, brought by an earlier emergence of the growing season and denser vegetation. Significance Statement: Droughts are extreme events with the potential to produce considerable social and economic damage. Because droughts emerge slowly and are relatively infrequent, large datasets are needed to study these features. Using multiple climate models, each producing multiple long-duration simulations, along with a novel drought index, we characterize rapidly developing droughts (those flash droughts identifiable from monthly data) and understand their drivers in the northeastern United States. We find that short-term extreme droughts are projected to be more frequent, while rapidly developing droughts will become more intense in the spring season. Intensification of rapidly developing droughts is attributed to differences in patterns of precipitation and evapotranspiration (soil evaporation and plant transpiration), which will be magnified by an extended growing season and an increase in vegetation. [ABSTRACT FROM AUTHOR]

Water stored in mountain snowpacks (i.e., snow water equivalent, SWE) represents an important but poorly characterized component of the terrestrial water cycle. The Western United States snow reanalysis (WUS–SR) dataset is novel in its combination of spatial resolution (~500 m), spatial extent (31°–49° N; 102°–125° W), and temporal continuity (daily over 1985–2021). WUS–SR is generated using a Bayesian framework with model-based snow estimates updated through the assimilation of cloud-free Landsat fractional snow-covered area observations. Over the WUS, the peak SWE verification with independent in situ measurements show correlation coefficient, mean difference (MD), and root mean squared difference (RMSD) of 0.77, −0.15 m, and 0.28 m, respectively. The effects of forest cover and Landsat image availability on peak SWE are assessed. WUS–SR peak SWE is well correlated (ranging from 0.75 to 0.91) against independent lidar-derived SWE taken near April 1st, with MD <0.15 m and RMSD <0.38 m. The dataset is useful for characterizing WUS mountain snow storage, and ultimately for improving snow-derived water resources management. Measurement(s) snow water equivalent, snow depth, fractional snow covered area Technology Type(s) Bayesian snow reanalysis framework with assimilation of fractional snow covered area Sample Characteristic - Location Western United States [ABSTRACT FROM AUTHOR]

The main challenge of evaluating droughts in the context of climate change and linking these droughts to adverse societal outcomes is a lack of a uniform definition that identifies drought conditions at a location and time. The U.S. Drought Monitor (USDM), created in 1999, is a well‐established composite index that combines drought indicators across the hydrological cycle (i.e., meteorological to hydrological) with information from local experts. This makes the USDM one of the most holistic measures for evaluating past drought conditions across the United States. In this study, the USDM was used to define drought events as consecutive periods in time where the USDM status met or exceeded D1 conditions over the past 20 years. This analysis was applied to 5 km grid cells covering the U.S. and Puerto Rico to characterize the frequency, duration, and intensification rates of drought, and the timing of onset, amelioration, and other measures for every drought event on record. Results from this analysis revealed stark contrasts in the evolution of drought across the United States. Over the western United States, droughts evolved much slower, resulting in longer‐lasting but fewer droughts. The eastern United States experienced more frequent, shorter‐duration events. Given the slower evolution from onset to drought peak, flash droughts, which made up 9.8% of all droughts, were less common across the western United States, with a greater frequency over the southern United States. The most severe drought event on record was the 2012 drought, when more than 21% of the United States experienced its largest number of weeks at or above extreme (D3) drought conditions. The availability of historical drought events would support future societal impacts studies relating drought to adverse outcomes and aid in the evaluation of mitigation strategies by providing a dataset to local decision makers to compare and evaluate past droughts. [ABSTRACT FROM AUTHOR]

Unlike streamflow, which can be sampled in aggregate at the catchment outlet, evapotranspiration (ET) is spatially dispersed, challenging large‐scale age estimation. Here, we introduce an approach for constraining the age of ET via mass balance and present the minimum flux‐weighted age of ET across the continental United States using distributed, publicly available water flux data sets. The lower‐bound constraint on ET age can be calculated by assuming that ET is preferentially sourced from the most recent precipitation through a last‐in, first‐out algorithm. From 2012 to 2017, ET was at least several months old across large areas of the western continental United States, including in Mediterranean and (semi‐)arid climate zones and shrub and evergreen needleleaf plant communities. The primary limitation of this approach is that it provides only a minimum flux‐weighted average age to satisfy the mass balance of outgoing fluxes; true ET fluxes are composed of distributions of ages and may be composed of much older water. The primary advantage of the approach is that flux time series of precipitation and ET are sufficient to constrain ET age, and model parameterization is unnecessary. ET ages can be used to validate tracer‐aided and modeling approaches and inform studies of biogeochemistry, water‐rock interactions, and plant water sourcing under drought. Plain Language Summary: What is the age of water returned to the atmosphere from the terrestrial land surface? Here, we explore the results of a simple mass‐balance approach that yields the minimum age of evapotranspired water by assuming that evapotranspiration (ET) sources water from the most recently arrived precipitation: arriving precipitation is added to an age ranked storage reservoir, and the youngest water in the storage reservoir is withdrawn for ET. We demonstrate that this last‐in, first‐out selection of water from storage for ET results in a lower bound of the true average age over a time period of record, even without knowledge of other outgoing fluxes like stream discharge. Cloud computation enables the creation of a minimum flux‐weighted ET age map across the continental United States from distributed, publicly available precipitation and ET data sets. The results of this study constrain an otherwise challenging property of the hydrologic cycle to monitor, as the lack of tracer data (e.g., water isotope concentrations) in ET at the continental scale makes quantifying age with traditional transit time approaches infeasible without significant model parameter assumptions. Key Points: The minimum flux‐weighted age of evapotranspiration (ET) can be calculated from a last‐in, first‐out (LIFO) selection of stored waterA LIFO‐based continental‐scale ET minimum age map was created with distributed water flux time seriesThe minimum flux‐weighted ET age is greatest in the Western United States in seasonally dry and (semi‐)arid biomes [ABSTRACT FROM AUTHOR]

We evaluate the simulated teleconnection of El Niño–Southern Oscillation (ENSO) to winter season precipitation extremes over the United States in a long (98 years) 1950 control high-resolution version (HR; 25-km nominal atmosphere model horizontal resolution) of the U.S. Department of Energy's (DOE) Energy Exascale Earth System Model version 1 (E3SMv1). The model bias and spatial pattern of ENSO teleconnections to mean and extreme precipitation in HR overall are similar to the low-resolution model's (LR; 110 km) historical simulation (four-member ensemble, 1925–59). However, over the southeastern United States (SE-U.S.), HR produces stronger El Niño–associated extremes, reducing LR's model bias. Both LR and HR produce weaker than observed increase in storm track activity during El Niño events there, but HR improves the ENSO-associated variability of moisture transport over SE-U.S. During El Niño, stronger vertical velocities in HR produce stronger large-scale precipitation, causing larger latent heating of the troposphere that pulls in more moisture from the Gulf of Mexico into the SE-U.S. This positive feedback also contributes to the stronger mean and extreme precipitation response in HR. Over the Pacific Northwest, LR's bias of stronger than observed La Niña associated extremes is amplified in HR. Both models simulate stronger than observed moisture transport from the Pacific Ocean into the region during La Niña years. The amplified HR bias there is due to stronger orographically driven vertical updrafts that create stronger large-scale precipitation, despite weaker La Niña–induced storm track activity. Significance Statement: New high-resolution Earth system models (ESMs) solve mathematical equations of fluid flow at much smaller spatial scales than prevalent ESMs, and thus are prohibitively expensive to compute. However, they can be useful for simulating accurate details of regional climate extremes that are driven by naturally occurring climate oscillations like El Niño–Southern Oscillation (ENSO). Here, we evaluate the simulation of ENSO-driven precipitation extremes over the United States in the high-resolution version of the U.S. Department of Energy's new Energy Exascale Earth System Model version 1. We find that the high-resolution model improves upon its low-resolution counterpart over the southeastern United States by producing a better transport of moisture into the region from the Gulf of Mexico during El Niño. Over the U.S. Pacific Northwest, the high-resolution model simulates the atmospheric flow in more detail over the complex mountainous terrain. However, it also brings in more moisture from the Pacific Ocean just like the low-resolution model. This causes it to produce precipitation extremes during La Niña years there that are stronger than that observed in the real world. [ABSTRACT FROM AUTHOR]

Diagnosis of rapidly developing springtime droughts in the central United States has mostly been made via numerous individual case studies rather than in an aggregate sense. This study investigates common aspects of subseasonal "meteorological drought" evolution, here defined as persistent precipitation minus evapotranspiration (P − ET) deficits, revealed in early (1 April–15 May) and late (16 May–30 June) spring composites of 5-day running mean JRA-55 reanalysis data for three different central U.S. regions during 1958–2018. On average, these droughts are initiated by a quasi-stationary Rossby wave packet (RWP), propagating from the western North Pacific, which arises about a week prior to drought onset. The RWP is related to a persistent ridge west of the incipient drought region and strong subsidence over it. This subsidence is associated with low-level divergent flow that dries the atmosphere and suppresses precipitation for roughly 1–2 weeks, and generally has a greater impact on the local moisture budget than does reduced poleward moisture transport. The resulting "dynamically driven" evaporative demand corresponds to a rapid drying of the root-zone soil moisture, which decreases around 40 percentiles within about 10 days. Anomalous near-surface warmth develops only after the P − ET deficit onset, as does anomalously low soil moisture that then lingers a month or more, especially in late spring. The horizontal scale of the RWPs, and of the related drought anomalies, decreases from early to late spring, consistent with the climatological change in the Pacific Rossby waveguide. Finally, while this composite analysis is based upon strong, persistent P − ET deficits, it still appears to capture much of the springtime development of "flash droughts" as well. [ABSTRACT FROM AUTHOR]

Flood hazard across the western United States (US) has generally shown decreasing trends in recent decades. This region's extreme streamflow is highly influenced by natural variability, which could either mask or amplify anthropogenic streamflow trends. In this study, we utilize a technique known as dynamical adjustment to assess historical (1970–2020) annual maximum 1‐day streamflow (Qx1d) from unregulated basins across the western US with and without the impact of natural variability. After removing natural variability, the fraction of basins with a positive (>5%) trend in Qx1d shifts from 25% to 53%. Basins with increasing (decreasing) Qx1d trends after dynamical adjustment exhibit weak (strong) drying, and furthermore are associated with intensifying precipitation extremes and/or large decreases in snowpack. Increasing flood hazard will likely emerge for such basins as the current phase of natural decadal variability shifts, and anthropogenic signals continue to intensify. Plain Language Summary: Historical observations of streamflow provide important insight into how the water cycle is responding to a changing climate. In particular, changes to extreme streamflow values, associated with highly impactful flooding events, are of great scientific interest. However, these events are largely controlled by inherently noisy processes like precipitation and temperature, which has limited the ability to isolate the influence of global warming on flooding trends to date. Here, we apply a method to determine how much each year's most extreme flood event has been influenced by natural variability in the climate system. In doing so, we can evaluate an "adjusted" timeseries of maximum annual floods from 1970 to 2020, which represents changes in flooding due to rising greenhouse gases. We find that increases in flood hazard are likely to occur, as the current phase of natural variability shifts, for basins with lower decreases in their historical annual water availability. These changes will be primarily due to warming‐driven snowpack loss and enhanced heavy rainfall. Lastly, basins with strong drying trends in their annual water availability will likely maintain their historically observed decreasing trends in flood hazard. Key Points: Internal atmospheric‐circulation variability can profoundly influence extreme streamflow trends across the western United StatesAnthropogenic climate change is driving decreasing trends in flood hazard across basins with strong drying trends in annual streamflowAnthropogenic flood hazard trend is positive in basins with weak drying, intensifying precipitation extremes and/or decreases in snowpack [ABSTRACT FROM AUTHOR]

• Rainfall leads to increased humidity and a subsequent end to the heatwave. • Post- heatwave periods witness a notable decrease in water storage. • Heatwave conclusions correspond with heightened rainfall and increased runoff. • Rainfall is more probable post- heatwave than in non– heatwave intervals. Extreme heat and drought conditions are affecting water availability in many regions worldwide, leading to negative impacts on human societies, agriculture, and ecosystems. However, current research lacks comprehensive spatiotemporal analysis examining the interplay between multiple hydrological factors and heatwave events, especially in the context of climate change. This research broadly pertains to understanding the dynamics of hydrological factors and their potential responses to heatwave during warm seasons across the contiguous United States for the period from 2003 to 2022. Utilizing data from the Global Land Data Assimilation System (GLDAS), we analyzed surface runoff, evapotranspiration (ET), precipitation, Groundwater Storage (GWS), Root Zone Soil Moisture (RZSM), and Total Water Storage (TWS) to discern annual patterns and the impacts of heatwave. The spatial patterns of heatwave highlighted a higher occurrence in the western, central, and northeastern U.S., with longer average durations in the western and south-central regions. These events are predominantly dry, characterized by low Relative Humidity (RH), except in the southeastern U.S., where heatwave coincide with high RH levels. Post-heatwave analysis indicated a reduction in GWS, TWS, RZSM, and ET, alongside an increase in surface runoff, RH, and precipitation. An in-depth examination of rainfall and temperature dynamics during heatwave revealed weak correlations between rainfall and temperature, as well as between rainfall and heatwave duration, highlighting the complex nature of these interactions. The study also found an enhanced probability of rainfall following heatwave, particularly in the eastern regions, drawing attention to the potential for increased flood risks post-heatwave. Our findings contribute to the growing body of knowledge on the impacts of heatwave on hydrological factors, providing valuable insights for climate change adaptation and water resource management strategies. [ABSTRACT FROM AUTHOR]

Water availability in the dry western United States (US) under climate change and increasing water use demand has become a serious concern. Previous studies have projected future runoff changes across the western US but ignored the impacts of ecosystem response to elevated CO2 concentration. Here, we aim to understand the impacts of elevated CO2 on future runoff changes through ecosystem responses to both rising CO2 and associated warming using the Noah‐MP model with representations of vegetation dynamics and plant hydraulics. We first validated Noah‐MP against observed runoff, leaf area index (LAI), and terrestrial water storage anomaly from 1980 to 2015. We then projected future runoff with Noah‐MP under downscaled climates from three climate models under Representative Concentration Pathway 8.5. The projected runoff declines variably from the Pacific Northwest by −11% to the Lower Colorado River basin by −92% from 2016 to 2099. To discern the exact causes, we conducted an attribution analysis of the modeled evapotranspiration from two additional sensitivity experiments: one with constant CO2 and another one with static monthly LAI climatology. Results show that surface "greening" (due to the CO2 fertilization effect) and the stomatal closure effect are the second largest contributors to future runoff change, following the warming effect. These two counteracting CO2 effects are roughly compensatory, leaving the warming effect to remain the dominant contributor to the projected runoff declines at large river basin scales. This study suggests that both surface "greening" and stomatal closure effects are important factors and should be considered together in water resource projections. Plain Language Summary: Water shortage in the western United States (US) is becoming increasingly serious due to increasing socioeconomic demands and climate change. Although previous studies have projected various degrees of runoff changes, they neglect the impact of rising CO2 on runoff projections. To explore the possible role that CO2 may play in the hydrologic cycle, we conducted three experiments with the newly improved Noah‐MP land model including vegetation dynamics and plant hydraulics. Consistent with previous studies, the western US tends to be drier toward the end of the 21st Century. CO2‐induced leaf area index increases (surface "greening") contribute considerably to the projected widespread transpiration increases and runoff reductions; however, these changes are nearly compensated by the stomatal closure effect of CO2 on transpiration, leaving the warming effect to remain the major cause to these transpiration and runoff changes. Therefore, the dual roles of CO2 in the hydrologic cycle through interactions with vegetation processes need to be considered in water resource projections. Key Points: Annual runoff of the major western US rivers is projected to decline variably from −11% to −92% by 2099 under Representative Concentration Pathway 8.5The counteracting CO2 fertilization and stomatal closure effects on runoff are roughly compensatoryDue to the two offsetting CO2 effects, warming remains the dominant driver for the projected runoff decline at river basin scales [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) account for more than 50% of summertime precipitation over the central United States and have a significant impact on local weather and hydrologic cycle. It is hypothesized that the inadequate treatment of MCSs is responsible for the long-standing warm and dry bias over the central United States in coarse-resolution general circulation model (GCM) simulations. In particular, a better understanding of MCS initiation is still lacking. Here a single-column Lagrangian parcel model is first developed to simulate the basic features of a rising parcel. This simple model demonstrates the collective effects of boundary layer moistening and dynamical lifting in triggering convective initiation and reproduces successfully its early afternoon peak with surface equivalent potential temperature as a controlling factor. It also predicts that convection is harder to trigger in the future climate under global warming, consistent with the results from convection-permitting regional climate simulations. Then, a multicolumn model that includes an array of single-column models aligned in the east–west direction and incorporates idealized cold pool interaction mechanisms is developed. The multicolumn model captures readily the cold pool–induced upscale growth feature in MCS genesis from initially scattered convection that is organized into a mesoscale cluster in a few hours. It also highlights the crucial role of lifting effects due to cold pool collision and spreading, subsidence effect, and gust front propagation speed in controlling the final size of mesoscale clusters and cold pool regions. This simple model should be useful for understanding fundamental mechanisms of MCS initiation and providing guidance for improving MCS simulations in GCMs. [ABSTRACT FROM AUTHOR]

As more global satellite-derived precipitation products become available, it is imperative to evaluate them more carefully for providing guidance as to how well precipitation space–time features are captured for use in hydrologic modeling, climate studies, and other applications. Here we propose a space–time Fourier spectral analysis and define a suite of metrics that evaluate the spatial organization of storm systems, the propagation speed and direction of precipitation features, and the space–time scales at which a satellite product reproduces the variability of a reference "ground-truth" product ("effective resolution"). We demonstrate how the methodology relates to our physical intuition using the case study of a storm system with rich space–time structure. We then evaluate five high-resolution multisatellite products (CMORPH, GSMaP, IMERG-Early, IMERG-Final, and PERSIANN-CCS) over a period of 2 years over the southeastern United States. All five satellite products show generally consistent space–time power spectral density when compared to a reference ground gauge–radar dataset (GV-MRMS), revealing agreement in terms of average morphology and dynamics of precipitation systems. However, a deficit of spectral power at wavelengths shorter than 200 km and periods shorter than 4 h reveals that all satellite products are excessively "smooth." The products also show low levels of spectral coherence with the gauge–radar reference at these fine scales, revealing discrepancies in capturing the location and timing of precipitation features. From the space–time spectral coherence, the IMERG-Final product shows superior ability in resolving the space–time dynamics of precipitation down to 200-km and 4-h scales compared to the other products. Significance Statement: Precipitation estimation products are essential for understanding water cycle dynamics and climate change, and for decision support in regions lacking ground observations. Several global products exist from multiple satellites orbiting Earth, but the challenge remains that of evaluating these products for accuracy and for improving the retrieval algorithms. Here we posit that the classical "pixel-to-pixel" comparison is not adequate and propose an approach that focuses on comparing space–time dynamics through a Fourier spectral analysis, which provides information about the size, shape, and orientation of precipitation systems, as well as their motion speed and direction. We evaluate five state-of-the-art multisatellite products and identify shortcomings, in particular in their ability to capture the submesoscale variability of precipitation. [ABSTRACT FROM AUTHOR]

Integrated, distributed hydrologic models leverage advances in computational power and data accessibility to improve predictive understanding of the water cycle. While impressive advances in this area of environmental modeling have been accomplished, such models are still rarely used, partially because of difficulty integrating model and data. This research describes the release of Watershed Workflow version 1.2, a new library aiming to automate and enable complex workflows defining inputs to high resolution, integrated, distributed hydrologic models. Watershed Workflow provides tools enabling the discovery, acquisition, mapping, and coordination of watershed geometry, land cover, soil properties, and meteorological data. It enables the construction of unstructured meshes that incorporate this data, and provides tools for automating a "first" simulation on any watershed in the United States. We present the design of the workflow tool, and describe best practices for its usage, culminating in a final example from watershed specification to simulation at the Coweeta Hydrologic Laboratory. [Display omitted] • An open-source workflow tool automates the setup of watershed hydrologic models anywhere in the US. • Workflow output integrates land cover type, subsurface structure, and meteorological forcing. • The workflow uses Jupyter notebooks to ensure automation, reproducibility, and extensibility. [ABSTRACT FROM AUTHOR]

[Display omitted] • Reservoir sedimentation is unsustainably diminishing storage capacity and benefits. • Sedimentation leads to costly dam decommissioning and intergenerational inequity. • A new sustainable management paradigm is needed for all reservoirs. • Monitoring is needed to measure the extent and rate of sedimentation. • Sustainable management strategies are sediment yield reduction, bypass, or removal. Although the hydrologic cycle is a continuously renewable resource, the natural rate of water delivery is highly variable. Water is made available to our society on a consistent and reliable basis largely due to flow regulation by storage reservoirs. However, under current management, the reservoir storage capacity needed for flow regulation is a non-renewable resource because this capacity is steadily being lost to sedimentation. Today's reservoirs occupy unique sites and may be considered largely irreplaceable, making the nation dependent on a non-sustainable resource. Sedimentation is steadily depleting storage capacity and progressively degrading the ability of reservoirs to fulfill their designated purposes. Sedimentation is also causing environmental impacts upstream and downstream of reservoirs. In the United States, the combined impacts of sedimentation and population growth have resulted in an estimated 35% decline in storage capacity per capita since this value peaked around 1970. In absolute terms, the estimated total reservoir storage capacity in the U.S. has dropped from a peak of 850 Gm3 in the late 1980s to 810 Gm3 today. Yet, sustaining the nation's long-term reservoir storage capacity has not been a priority for many public or private dam owners, especially when they lack a reservoir sedimentation monitoring policy. In many regions, future reservoir storage will have to serve an important role in the mitigation of climate change to help ensure water, food, and energy, and the reduction of flood risk. There is an imperative need to preserve existing reservoir storage capacity due to rising demands associated with population growth, and increasing hydrologic variability associated with climate change, and the challenges and costs associated with either expanding existing capacity or decommissioning and developing new storage capacity. The trapping of sediment behind dams has also contributed to the decline of freshwater and coastal environments downstream of dams. Reversing these dangerous trends in storage capacity and environmental integrity will require increased monitoring of reservoirs, application of both established and emerging sediment management technologies, and a new paradigm for sustainable reservoir design and management. It requires moving from the traditional design life (reservoir life expectancy) approach to the adoption of sustainable use as the appropriate criteria for reservoir design and operation, achieving a sediment balance across reservoirs to permit the indefinite operation of this critical infrastructure. [ABSTRACT FROM AUTHOR]