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1. Decomposing the Critical Components of Flash Drought Using the Standardized Evaporative Stress Ratio

   https://doi.org/10.2139/ssrn.4136023  

   Edris, Stuart G.; Basara, Jeffrey B.; Christian, Jordan I.; Hunt, Eric D.; Otkin, Jason A.; Salesky, Scott T.; Illston, Bradley G. (June 2022, SSRN Electronic Journal)

   Flash droughts develop rapidly (∼1 month timescale) and produce significant ecological, agricultural, and socioeconomical impacts. Recent advances in our understanding of flash droughts have resulted in methods to identify and quantify flash drought events. However, few studies have been done to isolate the individual rapid intensification and drought components of flash drought, which could further determine their causes, evolution, and predictability. This study utilized the standardized evaporative stress ratio (SESR) to quantify individual components of flash drought from 1979 – 2019, using evapotranspiration (ET) and potential evapotranspiration (PET) data from the North American Regional Reanalysis (NARR) dataset. The temporal change in SESR was utilized to quantify the rapid intensification component of flash drought. The drought component was also determined using SESR and compared to the United States Drought Monitor. The results showed that SESR was able to represent the spatial coverage of drought well for regions east of the Rocky Mountains. Furthermore, the rapid intensification component agreed well with previous flash drought studies, with the overall climatology of rapid intensification events showing similar hotspots to the flash drought climatology east of the Rocky Mountains. The rapid intensification climatology suggested areas west of the Rocky Mountains experience rapid drying more often than east of the Rocky Mountains. 

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2. Trends, Variability, and Drivers of Flash Droughts in the Contiguous United States

   https://doi.org/10.1029/2022WR032186  

   Lesinger, Kyle; Tian, Di (September 2022, Water Resources Research)

   Abstract Flash droughts are recently recognized subseasonal extreme climate phenomena, which develop with rapid onset and intensification and have significant socio‐environmental impacts. However, their historical trends and variability remain unclear largely due to the uncertainty associated with existing approaches. Here we comprehensively assessed trends, spatiotemporal variability, and drivers of soil moisture (SM) and evaporative demand (ED) flash droughts over the contiguous United States (CONUS) during 1981–2018 using hierarchical clustering, wavelet analysis, and bootstrapping conditional probability approaches. Results show that flash droughts occur in all regions in CONUS with Central and portions of the Eastern US showing the highest percentage of weeks in flash drought. ED flash drought trends are significantly increasing in all regions, while SM flash drought trends were relatively weaker across CONUS, with small significant increasing trends in the South and West regions and a decreasing trend in the Northeast. Rising ED flash drought trends are related to increasing temperature trends, while SM flash drought trends are strongly related to trends in weekly precipitation intensity besides weekly average precipitation and evapotranspiration. In terms of temporal variability, high severity flash droughts occurred every 2–7 years, corresponding with ENSO periods. For most CONUS regions, severe flash droughts occurred most often during La Niña and when the American Multidecadal Oscillation was in a positive phase. Pacific Decadal Oscillation negative phases and Artic Oscillation positive phases were also associated with increased flash drought occurrences in several regions. These findings may have implications for informing long‐term flash drought predictions and adaptations. 

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3. How Land Surface Characteristics Influence the Development of Flash Drought through the Drivers of Soil Moisture and Vapor Pressure Deficit

   https://doi.org/10.1175/JHM-D-22-0158.1  

   Lowman, Lauren E. L.; Christian, Jordan I.; Hunt, Eric D. (September 2023, Journal of Hydrometeorology)

   Abstract As global mean temperature rises, extreme drought events are expected to increasingly affect regions of the United States that are crucial for agriculture, forestry, and natural ecology. A pressing need is to understand and anticipate the conditions under which extreme drought causes catastrophic failure to vegetation in these areas. To better predict drought impacts on ecosystems, we first must understand how specific drivers, namely, atmospheric aridity and soil water stress, affect land surface processes during the evolution of flash drought events. In this study, we evaluated when vapor pressure deficit (VPD) and soil moisture thresholds corresponding to photosynthetic shutdown were crossed during flash drought events across different climate zones and land surface characteristics in the United States. First, the Dynamic Canopy Biophysical Properties (DCBP) model was used to estimate the thresholds that define reduced photosynthesis by assimilating vegetation phenology data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to a predictive phenology model. Next, we characterized and quantified flash drought onset, intensity, and duration using the standardized evaporative stress ratio (SESR) and NLDAS-2 reanalysis. Once periods of flash drought were identified, we investigated how VPD and soil moisture coevolved across regions and plant functional types. Results demonstrate that croplands and grasslands tend to be more sensitive to soil water limitations than trees across different regions of the United States. We found that whether VPD or soil moisture was the primary driver of plant water stress during drought was largely region specific. The results of this work will help to inform land managers of early warning signals relevant for specific ecosystems under threat of flash drought events. 

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4. Diagnostic Classification of Flash Drought Events Reveals Distinct Classes of Forcings and Impacts

   https://doi.org/10.1175/JHM-D-21-0134.1  

   Osman, Mahmoud; Zaitchik, Benjamin F.; Badr, Hamada S.; Otkin, Jason; Zhong, Yafang; Lorenz, David; Anderson, Martha; Keenan, Trevor F.; Miller, David L.; Hain, Christopher; et al (February 2022, Journal of Hydrometeorology)

   Abstract Recent years have seen growing appreciation that rapidly intensifying flash droughts are significant climate hazards with major economic and ecological impacts. This has motivated efforts to inventory, monitor, and forecast flash drought events. Here we consider the question of whether the term “flash drought” comprises multiple distinct classes of event, which would imply that understanding and forecasting flash droughts might require more than one framework. To do this, we first extend and evaluate a soil moisture volatility–based flash drought definition that we introduced in previous work and use it to inventory the onset dates and severity of flash droughts across the contiguous United States (CONUS) for the period 1979–2018. Using this inventory, we examine meteorological and land surface conditions associated with flash drought onset and recovery. These same meteorological and land surface conditions are then used to classify the flash droughts based on precursor conditions that may represent predictable drivers of the event. We find that distinct classes of flash drought can be diagnosed in the event inventory. Specifically, we describe three classes of flash drought: “dry and demanding” events for which antecedent evaporative demand is high and soil moisture is low, “evaporative” events with more modest antecedent evaporative demand and soil moisture anomalies, but positive antecedent evaporative anomalies, and “stealth” flash droughts, which are different from the other two classes in that precursor meteorological anomalies are modest relative to the other classes. The three classes exhibit somewhat different geographic and seasonal distributions. We conclude that soil moisture flash droughts are indeed a composite of distinct types of rapidly intensifying droughts, and that flash drought analyses and forecasts would benefit from approaches that recognize the existence of multiple phenomenological pathways. 

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5. Generative Adversarial Network for Real‐Time Flash Drought Monitoring: A Deep Learning Study

   https://doi.org/10.1029/2023WR035600  

   Foroumandi, Ehsan; Gavahi, Keyhan; Moradkhani, Hamid (May 2024, Water Resources Research)

   Abstract Droughts are among the most devastating natural hazards, occurring in all regions with different climate conditions. The impacts of droughts result in significant damages annually around the world. While drought is generally described as a slow‐developing hazardous event, a rapidly developing type of drought, the so‐called flash drought has been revealed by recent studies. The rapid onset and strong intensity of flash droughts require accurate real‐time monitoring. Addressing this issue, a Generative Adversarial Network (GAN) is developed in this study to monitor flash droughts over the Contiguous United States (CONUS). GAN contains two models: (a) discriminator and (b) generator. The developed architecture in this study employs a Markovian discriminator, which emphasizes the spatial dependencies, with a modified U‐Net generator, tuned for optimal performance. To determine the best loss function for the generator, four different networks are developed with different loss functions, including Mean Absolute Error (MAE), adversarial loss, a combination of adversarial loss with Mean Square Error (MSE), and a combination of adversarial loss with MAE. Utilizing daily datasets collected from NLDAS‐2 and Standardized Soil Moisture Index (SSI) maps, the network is trained for real‐time daily SSI monitoring. Comparative assessments reveal the proposed GAN's superior ability to replicate SSI values over U‐Net and Naïve models. Evaluation metrics further underscore that the developed GAN successfully identifies both fine‐ and coarse‐scale spatial drought patterns and abrupt changes in the SSI temporal patterns that is important for flash drought identification. 

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