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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]

Soil moisture feedbacks that initiate, enhance, or suppress convection initiation and precipitation are important components of regional hydroclimatology. However, soil moisture feedbacks and the processes through which they operate are notoriously challenging to observe and study outside of model environments. In this study, we combine a climatological assessment of event frequency‐based measurements of soil moisture‐precipitation coupling in the central United States with a process‐based analysis of the mechanisms by which wet‐ and dry‐soil feedbacks may operate in the region. We use the Thunderstorm Observation by Radar algorithm to identify the location of convection initiation, circumventing the issue of using precipitation accumulation as a proxy for convection initiation. Results show substantial spatial variability in the climatological sign and strength of soil moisture‐precipitation coupling in the central United States, including regions that exhibit signs of both wet‐ and dry‐soil feedbacks. Within the regions with the strongest feedback signals, we find consistently strong coupling between soil moisture and the partitioning of surface heat flux, and strong coupling between surface heat flux—particularly sensible heat flux—and diurnal change in planetary boundary layer height. In all three regions assessed, the process‐based metrics confirmed the potential of wet‐ and/or dry‐soil feedbacks leading to convection initiation. Plain Language Summary: Soil moisture can affect the occurrence, location, and intensity of precipitation in many global regions. Observations of the drivers of so‐called soil moisture feedbacks are important for constraining models; however, feedbacks are challenging to observe and study outside of model environments. We use a data set of thousands of thunderstorm initiation locations with model‐based soil moisture to measure the sign, strength, and variability in soil moisture feedback to precipitation in the central United States. We denote three regions with strong evidence of both wet‐soil and dry‐soil feedbacks to precipitation. Key Points: The sign and strength of soil moisture‐precipitation coupling was assessed using thousands of convection events points in the central USMultiple regions show signs of both wet and dry soil feedbacks, with strong coupling between soil moisture and surface heat fluxClimatological assessment and process‐based metrics confirmed wet‐ and/or dry‐soil feedbacks leading to convection in the central US [ABSTRACT FROM AUTHOR]

Skillful subseasonal prediction of extreme heat and precipitation greatly benefits multiple sectors, including water management, public health, and agriculture, in mitigating the impact of extreme events. A statistical model is developed to predict the weekly frequency of extreme warm days and 14-day standardized precipitation index (SPI) during boreal summer in the United States. We use a leading principal component of U.S. soil moisture and an index based on the North Pacific sea surface temperature (SST) as predictors. The model outperforms the NCEP Climate Forecast System, version 2 (CFSv2), at weeks 3–4 in the eastern United States. It is found that the North Pacific SST anomalies persist for several weeks and are associated with a persistent wave train pattern, which leads to increased occurrences of blocking and extreme temperature over the eastern United States. Extreme dry soil moisture conditions persist into week 4 and are associated with an increase in sensible heat flux and a decrease in latent heat flux, which may help to maintain the overlying anticyclone. The clear-sky conditions associated with blocking anticyclones further decrease soil moisture and increase the frequency of extreme warm days. This skillful statistical model has the potential to aid in irrigation scheduling, crop planning, and reservoir operation and to provide mitigation of impacts from extreme heat events. [ABSTRACT FROM AUTHOR]

Flash droughts are noted by their unusually rapid rate of onset or intensification, which makes it difficult to anticipate and prepare for them, thus resulting in severe impacts. Although the development of flash drought can be associated with certain atmospheric conditions, vegetation also plays a role in propagating flash drought. This study examines the climatology of warm season (March–September) flash drought occurrence in the United States between 1979 and 2014, and quantifies the possible impacts of vegetation on flash drought based on a set of sensitivity experiments using the Community Earth System Model, version 2 (CESM2). With atmospheric nudging, CESM2 well captures historical flash drought. Compared with NASA's Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and National Climate Assessment–Land Data Assimilation System (NCA-LDAS), CESM2 shows agreement on the high flash drought frequency in the Great Plains and southeastern United States, but overestimates flash drought occurrence in the Midwest. The vegetation sensitivity experiments suggest that vegetation greening can significantly increase the flash drought frequency in the Great Plains and the western United States during the warm seasons through enhanced evapotranspiration. However, flash drought occurrence is not significantly affected by vegetation phenology in the eastern United States and Midwest due to weak land–atmosphere coupling. In response to vegetation greening, the extent of flash drought also increases, but the duration of flash drought is not sensitive to greening. This study highlights the importance of vegetation in flash drought development, and provides insights for improving flash drought monitoring and early warning. [ABSTRACT FROM AUTHOR]

Soil moisture is an important variable for numerous scientific disciplines, and therefore provision of accurate and timely soil moisture information is critical. Recent initiatives, such as the National Soil Moisture Network effort, have increased the spatial coverage and quality of soil moisture monitoring infrastructure across the contiguous United States. As a result, the foundation has been laid for a high-resolution, real-time gridded soil moisture product that leverages data from in situ networks, satellite platforms, and land surface models. An important precursor to this development is a comprehensive, national-scale assessment of in situ soil moisture data fidelity. Additionally, evaluation of the United States's current in situ soil moisture monitoring infrastructure can provide a means toward more informed satellite and model calibration and validation. This study employs a triple collocation approach to evaluate the fidelity of in situ soil moisture observations from over 1200 stations across the contiguous United States. The primary goal of the study is to determine the monitoring stations that are best suited for 1) inclusion in national-scale soil moisture datasets, 2) deriving in situ-informed gridded soil moisture products, and 3) validating and benchmarking satellite and model soil moisture data. We find that 90% of the 1233 stations evaluated exhibit high spatial consistency with satellite remote sensing and land surface model soil moisture datasets. In situ error did not significantly vary by climate, soil type, or sensor technology, but instead was a function of station-specific properties such as land cover and station siting. [ABSTRACT FROM AUTHOR]

Soil moisture can affect precipitation, however there is significant debate about the sign and strength of land–atmosphere coupling. This may be due to the differences regarding the selection of data sources, the presence of atmospheric persistence, and the spatial and temporal scales of the analysis. This study is a sensitivity analysis that quantifies how each of these factors influences land–atmosphere coupling in the central United States from 2005 to 2007. Four different sources of soil moisture are used to represent soil moisture: in situ measurements and three satellite products. The Thunderstorm Observation by Radar (ThOR) algorithm is used to identify convective events. The results show that warm-season afternoon convection initiates preferentially over dry soil, if in situ measurements are used. However, when satellite data are used the sign and strength of the soil moisture-precipitation coupling varies depending on which satellite dataset is used. This demonstrates that evaluations of land–atmosphere coupling strength are sensitive to the source of soil moisture. Our results also show that accounting for atmospheric persistence tends to weaken apparent land–atmosphere coupling. Changing the spatial scale of the analysis can also influence the sign and coupling strength. Analyses that are performed at a coarser spatial resolution tend to indicate a wet preference because they do not capture the local negative feedbacks. This study demonstrates that contradictions in the literature regarding the sign and strength of soil moisture-precipitation feedbacks can be partly attributed to differences in datasets, methods and scale of the analysis. [ABSTRACT FROM AUTHOR]

Rapid onset droughts, termed “flash droughts”, present a series of unique challenges for drought monitoring, forecasting, and mitigation. Due to the rapid onset and lack of early warning systems, stakeholders can be caught off-guard by flash droughts and suffer disproportionate impacts. Despite these impacts, little is known about the physical drivers of flash droughts. The purpose of this study is to determine antecedent meteorological conditions prior to the onset of flash drought in the Eastern United States. Emphasizing the agricultural impacts, flash droughts were defined as periods when the pentad-average 0–40 cm volumetric water content declines from at least the 40th percentile to below the 20th percentile in 4 pentads or less. Meteorological variables from 125 stations in the Eastern U.S. from March − October 1979 − 2010 were analyzed for their relationships with flash drought onset. Consistent with previous findings, flash drought was associated with decreased precipitation and humidity, increased solar radiation, and elevated temperatures. However logistic regression results suggest variables that accounted for surface moisture balance and/or atmospheric evaporative demand were more closely linked with the likelihood of flash drought than temperature and/or precipitation. Associated surface conditions are likely driven by ridging in the mid to upper level troposphere, which is shown to be more persistent leading up the flash droughts in the northern half of the study region. Our results elucidate the meteorological conditions immediately prior to the onset of one type or “flavor” of flash drought, defined by characteristic rapid intensification. Arguably, one could define flash drought with soil moisture thresholds varying from those used in this study and/or different time scales of soil moisture depletion. Therefore, we additionally argue that absences of both a standard flash drought definition and consistent precedent for identifying flash drought complicates monitoring and predicting these events. [ABSTRACT FROM AUTHOR]

ABSTRACT Regions of strong land-atmosphere coupling are often depicted as static in time. However, the mechanisms through which the land surface impacts atmospheric conditions vary on sub-daily to multi-decadal timescales. Therefore, characterizing the long-term variability of land-atmosphere interactions may provide a means of predicting when surface-induced extreme temperature events will be more or less likely to occur. We evaluate the coupling strength between soil moisture, as represented by in situ observations and 1-month Standardized Precipitation Index ( SPI), and subsequent monthly maximum temperature ( TMAX) over the contiguous United States. We find that the utility of SPI as a proxy for soil moisture anomalies is limited to the summer, as the correlations between SPI and TMAX are not significantly related in the other seasons. We examine the variability in summer SPI-TMAX coupling in four regions of the United States. In general, we find the strongest relationships between SPI and TMAX in the Southern Great Plains. However, our results demonstrate that the coupling strength varies considerably over time in most regions of the United States. The long-term variability in SPI-TMAX coupling strength is strongly related to the Pacific Decadal Oscillation in the northwest and midwest United States, and the Atlantic Multidecadal Oscillation in the southeast United States The results of this study suggest that land-atmosphere coupling in the contiguous United States is modulated by multi-decadal oscillations in Pacific and Atlantic sea surface temperatures. [ABSTRACT FROM AUTHOR]

Flash droughts are characterized by a period of rapid intensification over sub-seasonal time scales that culminates in the rapid emergence of new or worsening drought impacts. This study presents a new flash drought intensity index (FDII) that accounts for both the unusually rapid rate of drought intensification and its resultant severity. The FDII framework advances our ability to characterize flash drought because it provides a more complete measure of flash drought intensity than existing classification methods that only consider the rate of intensification. The FDII is computed using two terms measuring the maximum rate of intensification (FD_INT) and average drought severity (DRO_SEV). A climatological analysis using soil moisture data from the Noah land surface model from 1979–2017 revealed large regional and interannual variability in the spatial extent and intensity of soil moisture flash drought across the US. Overall, DRO_SEV is slightly larger over the western and central US where droughts tend to last longer and FD_INT is ~75% larger across the eastern US where soil moisture variability is greater. Comparison of the FD_INT and DRO_SEV terms showed that they are strongly correlated (r = 0.82 to 0.90) at regional scales, which indicates that the subsequent drought severity is closely related to the magnitude of the rapid intensification preceding it. Analysis of the 2012 US flash drought showed that the FDII depiction of severe drought conditions aligned more closely with regions containing poor crop conditions and large yield losses than that captured by the intensification rate component (FD_INT) alone. [ABSTRACT FROM AUTHOR]