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In the two decades, since the advent of the term "flash drought," considerable research has been directed toward the topic. Within the scientific community, we have actively forged a new paradigm that has avoided a chaotic evolution of conventional drought but instead recognizes that flash droughts have distinct dynamics and, particularly, impacts. We have moved beyond the initial debate over the definition of flash drought to a centralized focus on the triad of rapid onset, drought development, and associated impacts. The refinement toward this general set of principles has led to significant progress in determining key variables for monitoring flash drought development, identifying notable case studies, and compiling fundamental physical characteristics of flash drought. However, critical focus areas still remain, including advancing our knowledge on the atmospheric and oceanic drivers of flash drought; developing flash drought‐specific detection indices and monitoring systems tailored to practitioners; improving subseasonal‐to‐seasonal prediction of these events; constraining uncertainty in flash drought and impact projections; and using social science to further our understanding of impacts, particularly with regard to sectors that lie outside of our traditional hydroclimatological focus, such as wildfire management and food‐security monitoring. Researchers and stakeholders working together on these critical topics will assure society is resilient to flash drought in a changing climate. This article is categorized under:Science of Water > Water Extremes [ABSTRACT FROM AUTHOR]

In recent years, extreme droughts in the United States have increased in frequency and severity, underlining a need to improve our understanding of vegetation resilience and adaptation. Flash droughts are extreme events marked by the rapid dry down of soils due to lack of precipitation, high temperatures, and dry air. These events are also associated with reduced preparation, response, and management time windows before and during drought, exacerbating their detrimental impacts on people and food systems. Improvements in actionable information for flash drought management are informed by atmospheric and land surface processes, including responses and feedbacks from vegetation. Phenologic state, or growth stage, is an important metric for modeling how vegetation modulates land–atmosphere interactions. Reduced stomatal conductance during drought leads to cascading effects on carbon and water fluxes. We investigate how uncertainty in vegetation phenology and stomatal regulation propagates through vegetation responses during drought and non-drought periods by coupling a land surface hydrology model to a predictive phenology model. We assess the role of vegetation in the partitioning of carbon, water, and energy fluxes during flash drought and carry out a comparison against drought and non-drought periods. We selected study sites in Kansas, USA, that were impacted by the flash drought of 2012 and that have AmeriFlux eddy covariance towers which provide ground observations to compare against model estimates. Results show that the compounding effects of reduced precipitation and high vapor pressure deficit (VPD) on vegetation distinguish flash drought from other drought and non-drought periods. High VPD during flash drought shuts down modeled stomatal conductance, resulting in rates of evapotranspiration (ET), gross primary productivity (GPP), and water use efficiency (WUE) that fall below those of average drought conditions. Model estimates of GPP and ET during flash drought decrease to rates similar to what is observed during the winter, indicating that plant function during drought periods is similar to that of dormant months. These results have implications for improving predictions of drought impacts on vegetation. [ABSTRACT FROM AUTHOR]

Increased flash drought awareness in recent years has motivated the development of numerous indicators for monitoring, early warning, and assessment. The flash drought indicators can act as a complementary set of tools by which to inform flash drought response and management. However, the limitations of each indicator much be measured and communicated between research and practitioners to ensure effectiveness. The limitations of any flash drought indicator are better understood and overcome through assessment of indicator sensitivity and consistency; however, such assessment cannot assume any single indicator properly represents the flash drought "truth." To better understand the current state of flash drought monitoring, this study presents an intercomparison of nine, widely used flash drought indicators. The indicators represent perspectives and processes that are known to drive flash drought, including evapotranspiration and evaporative demand, precipitation, and soil moisture. We find no single flash drought indicator consistently outperforms all others across the contiguous United States. We do find the evaporative demand- and evapotranspiration-driven indicators tend to lead precipitation- and soil moisture-based indicators in flash drought onset, but also tend to produce more flash drought events collectively. Overall, the regional and definition-specific variability in results supports the argument for a multi-indicator approach for flash drought monitoring, as advocated by recent studies. Furthermore, flash drought research-especially evaluation of historical and potential future changes in flash drought characteristics-should test multiple indicators, datasets, and methods for representing flash drought, and ideally employ a multi-indicator analysis framework over use of a single indicator from which to infer all flash drought information. SIGNIFICANCE STATEMENT: Rapid onset or "flash" drought has been an increasing concern globally, with quickly intensifying impacts to agriculture, ecosystems, and water resources. Many tools and indicators have been developed to monitor and provide early warning for flash drought, ideally resulting in more time for effective mitigation and reduced impacts. However, there remains no widely accepted single method for defining, monitoring, and measuring flash drought, which means most indicators that are developed are compared with other individual indicators or conditions and impacts in one or two flash drought events. In this study, we measure the state of flash drought monitoring through an intercomparison of nine, widely used flash drought indicators that represent different aspects of flash drought. We find that no single flash drought indicator outperformed all others and suggest that a comprehensive flash drought monitor should leverage multiple, complementary indicators, datasets, and methods. Furthermore, we suggest flash drought research-especially that which reflects on historical or projected changes in flash drought characteristics-should seek multiple indicators, datasets, and methods for analyses, thereby reducing the potentially confounding effects of sensitivity to a single indicator. [ABSTRACT FROM AUTHOR]

Recent studies suggest springtime wet extremes and summertime dry extremes will occur more frequently in the U.S. Midwest, potentially leading to devastating agricultural consequences. To understand the role of circulation patterns in the projected changes in seasonal precipitation extremes, the k-means clustering approach is applied to the large-ensemble experiments of Community Earth System Model, version 2 (CESM2-LE), and ensemble projections of CMIP6. We identify two key atmospheric circulation patterns that are associated with the extremely wet spring and extremely dry summer in the U.S. Midwest. The springtime wet extremes are typically linked to baroclinic waves with a northward shift of the North American westerly jet and positive anomalies in sea level pressure over the western Atlantic, which favor the development of the Great Plains low-level jet. The summertime dry extremes are associated with the development of an anomalous ridge with suppressed storm tracks over the central United States. The projected increase in springtime wet extremes and summertime dry extremes can be attributed to significantly more frequent occurrences of the associated atmospheric regimes. Particularly, the intensity of wet extremes is expected to increase mainly due to the enhanced moisture flux from the Gulf of Mexico. The moisture budget analysis suggests that the precipitation extremes are mainly associated with the dynamic component of atmospheric circulation. CESM2-LE and CMIP6 exhibit good agreement in the projected changes in circulation patterns and precipitation extremes. Our results explain the mechanism of the projected changes in the Midwest seasonal precipitation and highlight the contribution of circulation patterns to hydroclimatic extremes. [ABSTRACT FROM AUTHOR]

Precipitation extremes present significant risks to Midwest agriculture, water resources, and natural ecosystems. Recently, there is growing attention to the transitions of precipitation extremes, or shifts between heavy precipitation and drought, due to their profound environmental and socio‐economic impacts. Changes in Midwest precipitation extremes and transitions between extremes over the past few decades have been documented; however, their future changes are still unknown. In this study, we estimate the projected changes in transitions of precipitation extremes in the Midwest based on 17 CMIP6 models. Two Standardized Precipitation Index (SPI) based metrics, intra‐annual variability and transitions, are used to quantify the magnitude, duration, and frequency of variability and transitions between wet and dry extremes. Compared with the observation‐based precipitation datasets, the multimodel ensemble median of CMIP6 can reasonably represent the spatial patterns of SPI extremes and transitions. Climate projections show significantly intensified wet extremes across the Midwest by the end of the century, with a greater increase over the northern Midwest and the Great Lakes region. The short‐term SPI also shows intensified dry extremes over the western half of the Midwest. Consequently, there is a significant increase in the magnitude of intra‐annual variability in most areas. Projections also suggest more frequent and rapid transitions between the wet and dry extremes, especially over the Great Lakes region and northern Midwest. Seasonally, more frequent transitions from a wet spring to a dry summer (or from a dry fall to a wet winter/spring) are projected to occur; and generally, the wet and dry conditions between the transitions are projected to be more intense compared to the historical period. Furthermore, the intensified precipitation extremes and accelerated transitions are greatly alleviated under a lower emission scenario, implying that future changes in hydroclimate extremes, and impacts thereof, in the Midwest are sensitive to climate change mitigation. [ABSTRACT FROM AUTHOR]

Severe winter weather is a staple of Midwest United States (U.S.) climate and is an important natural hazard that has significant economic and environmental impacts. Winter season severity varies both spatially and temporally in the Midwest, and past studies have documented significant changes in Midwest winter characteristics, including increases in temperature and decreases in snow depth. In this study, we use the Accumulated Winter Season Severity Index (AWSSI) to characterize winter severity across the Midwest and assess its variability and change on various spatial and temporal scales during the 1951–2020 period. AWSSI is derived from daily records of snowfall (SF), snow depth (SD), maximum surface air temperature (TMAX), and minimum surface air temperature (TMIN) during the winter season. The daily total AWSSI index value reflects the sum of points accumulated from daily values of each of these four variables surpassing pre-determined thresholds, and the total season sum reflects the overall winter season severity. We find AWSSI provides a unique perspective by which to describe climatological differences in winter season character in the Midwest. Namely, over three quarters of winter season days accumulate points in the northern Midwest, compared to just over half in the southern Midwest. Meanwhile, the relative contribution of extreme winter days to total winter severity is much larger in the southern Midwest than farther north. In addition, we find overall winter season severity has significantly decreased at only a quarter of stations and the frequency of extreme winter days has significantly decreased at only a fifth of stations, despite widespread increases in winter daily maximum and minimum temperature. The results suggest Midwest U.S. winter season severity as described by the AWSSI has not significantly changed over the past 70 years. [ABSTRACT FROM AUTHOR]

The Accumulated Winter Season Severity Index (AWSSI) describes the “harshness” of the cold season. This work utilizes AWSSI to explore the interannual teleconnective influences that shaped winter severity between 1951 and 2020 across the Midwest U.S. Annual AWSSI total variability clusters into four distinct geographic areas, each shaped by different teleconnective influences. The regions are closely delineated by the main river basins and include the Ohio (Region 1), upper Mississippi and Missouri (Region 2), central Mississippi and southern Missouri (Region 3), and the Great Lakes (Region 4). Of outmost influence in shaping severe winters across the Midwest have been synoptic flow modifications associated with significant meandering and southern displacement of the Polar jet over the conterminous United States and/or the Midwest that depress near-surface air temperatures and increase the likelihood of snow fall and/or snow depth. These flows are most closely related to the combined influence of the negative (positive) phases of the NAO (PNA and PDO) in Region 1, PNA− in Region 2, NAO− in Region 3, and the negative (positive) phase of the PNA (TNH) across Region 4. Mild winters have been shaped by more zonal flows with the Polar jet positioned north of the Midwest and bringing milder temperatures, less snowfall, and reduced winter severity to the impacted areas. Such modifications have been related to TNH−, PNA+, and NAO+ across Regions 1, 2, and 3, respectively. Mild winters have been shaped by TNH− and to a limited extent NAO+, across Region 4. [ABSTRACT FROM AUTHOR]

Soil moisture can be obtained from in-situ measurements, satellite observations, and model simulations. This study evaluates different methods of combining model, satellite, and in-situ soil moisture data to provide an accurate and spatially-continuous soil moisture product. Three independent soil moisture datasets are used, including an in situ-based product that uses regression kriging (RK) with precipitation, SMAP L4 soil moisture, and model-simulated soil moisture from the Noah model as part of the North American Land Data Assimilation System. Triple collocation (TC), relative error variance (REV), and RK were used to estimate the error variance of each parent dataset, based on which the least squares weighting (LSW) was applied to blend the parent datasets. These results were also compared with that using simple average (AVE). The results indicated no significant differences between blended soil moisture datasets using errors estimated from TC, REV or RK. Moreover, the LSW did not outperform AVE. The SMAP L4 data have a significant negative bias (-18 %) comparing with in-situ measurements, and in-situ measurements are valuable for improving the accuracy of hybrid results. In addition, datasets using anomalies and percentiles have smaller errors than using volumetric water content, mainly due to the reduced bias. Finally, the in situ-based soil moisture and the simple-averaged product from in situ-based and Noah soil moisture are the two optimal datasets for soil moisture mapping. The in situ-based product performs better when the sample density is high, while the simple-averaged product performs better when the station density is low, or measurement sites are less representative. [ABSTRACT FROM AUTHOR]