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Caily Schwartz
,
Tonya Haigh
,
Mark Svoboda
, and
Madeline Goebel

Abstract

Because flash drought is a relatively new phenomenon in drought research, defining the concept is critical for scientists and decision-makers. Having detrimental impacts on many sectors, it is important to have a consistent definition and understanding of flash drought, between experts and stakeholders, to provide early warning to the community. This study focuses on onset and progression of conditions and demonstrates the difference in flash drought identification for 15 events across six quantitative definitions of flash drought that use the U.S. Drought Monitor (USDM). Five flash drought events have been studied in the literature while 10 additional events have been perceived as flash drought by stakeholders. The results show that two of six definitions consistently capture the earliest onset of flash drought and include a large percent area in the identification. A qualitative analysis of management challenges and needs determined by stakeholders was completed using survey data. The results found that managing impacts and better communication and education were the top challenges and more data and enhanced and efficient communication as the top needs to better monitor, manage, and respond to flash droughts. The results demonstrate the need for assessing the characteristics of the definitions to enhance communication and monitoring strategies for large and small-scale flash droughts.

Significance Statement

The purpose of this study is to better understand how different numerical flash drought definitions characterize multiple flash drought events and how these definitions are useful in addressing the needs and challenges of stakeholders. This is important because definitions may capture different areas in flash droughts, which can impact how end users identify a flash drought. Further, this study uses events identified by the literature and by people familiar with drought monitoring. From these findings, definitions that capture flash drought earliest would help address the challenge of rapid onset and the need of quicker data. Further, definitions by sector would be beneficial to address the scale of impacts. This study identifies the importance of definitions for early warning systems.

Open access
Zachary T. Leasor
,
Steven M. Quiring
, and
Mark D. Svoboda

Abstract

Drought is a prominent climatic hazard in the south-central United States. Drought severity is frequently classified using the categories established by the U.S. Drought Monitor (USDM). This study evaluates whether the thresholds for the standardized precipitation index (SPI) used by the USDM accurately classify drought severity. This study uses the SPI based on PRISM precipitation data from 1900 to 2015 to evaluate drought severity in Texas, Oklahoma, and Kansas. The results show that the fixed SPI thresholds for the USDM drought categories may lead to a systematic underestimation of drought severity in arid regions. To address this issue, objective drought thresholds were developed at each location by fitting a cumulative distribution function at each location to ensure that the observed frequency of drought in each severity category (D0–D4) matched the theoretical expectations of the USDM. This approach reduces the systematic biases in drought severity across the western portion of the study region. Therefore, we recommend developing objective drought thresholds for each location and SPI time scale (e.g., 1, 3, and 6 months). This method can be used to develop objective drought thresholds for any drought index and climate region of interest.

Free access
Jason A. Otkin
,
Martha C. Anderson
,
Christopher Hain
, and
Mark Svoboda

Abstract

In this study, the ability of a new drought metric based on thermal infrared remote sensing imagery to provide early warning of an elevated risk for drought intensification is assessed. This new metric, called the rapid change index (RCI), is designed to highlight areas undergoing rapid changes in moisture stress as inferred from weekly changes in the evaporative stress index (ESI) generated using the Atmosphere–Land Exchange Inverse (ALEXI) surface energy balance model. Two case study analyses across the central United States revealed that the initial appearance of negative RCI values indicative of rapid increases in moisture stress preceded the introduction of severe-to-exceptional drought in the U.S. Drought Monitor (USDM) by more than 4 weeks. Using data from 2000 to 2012, the probability of USDM intensification of at least one, two, or three categories over different time periods was computed as a function of the RCI magnitude. Compared to baseline probabilities, the RCI-derived probabilities often indicate a much higher risk for drought development that increases greatly as the RCI becomes more negative. When the RCI is strongly negative, many areas are characterized by intensification probabilities that are several times higher than the baseline climatology. The highest probabilities encompass much of the central and eastern United States, with the greatest increase over climatology within regions most susceptible to rapid drought development. These results show that the RCI provides useful drought early warning capabilities that could be used to alert stakeholders of an increased risk for drought development over subseasonal time scales.

Full access
Jason A. Otkin
,
Martha C. Anderson
,
Christopher Hain
, and
Mark Svoboda

Abstract

In this study, the potential utility of using rapid temporal changes in drought indices to provide early warning of an elevated risk for drought development over subseasonal time scales is assessed. Standardized change anomalies were computed each week during the 2000–13 growing seasons for drought indices depicting anomalies in evapotranspiration, precipitation, and soil moisture. A rapid change index (RCI) that encapsulates the accumulated magnitude of rapid changes in the weekly anomalies was computed each week for each drought index, and then a simple statistical method was used to convert the RCI values into drought intensification probabilities depicting the likelihood that drought severity as analyzed by the U.S. Drought Monitor (USDM) would worsen in subsequent weeks. Local and regional case study analyses revealed that elevated drought intensification probabilities often occur several weeks prior to changes in the USDM and in topsoil moisture and crop condition datasets compiled by the National Agricultural Statistics Service. Statistical analyses showed that the RCI-derived probabilities are most reliable and skillful over the central and eastern United States in regions most susceptible to rapid drought development. Taken together, these results suggest that tools used to identify areas experiencing rapid changes in drought indices may be useful components of future drought early warning systems.

Full access
Paul Xavier Flanagan
,
Rezaul Mahmood
,
Terry Sohl
,
Mark Svoboda
,
Brian Wardlow
,
Michael Hayes
, and
Eric Rappin

Abstract

Land-use land-cover change (LULCC) has become an important topic of research for the central United States because of the extensive conversion of the natural prairie into agricultural land, especially in the northern Great Plains. As a result, shifts in the natural climate (minimum/maximum temperature, precipitation, etc.) across the north-central United States have been observed, as noted within the Fourth National Climate Assessment (NCA4) report. Thus, it is necessary to understand how further LULCC will affect the near-surface atmosphere, the lower troposphere, and the planetary boundary layer (PBL) atmosphere over this region. The goal of this work was to investigate the utility of a new future land-use land-cover (LULC) dataset within the Weather Research and Forecasting (WRF) modeling system. The present study utilizes a modeled future land-use dataset developed by the Forecasting Scenarios of Land-Use Change (FORE-SCE) model to investigate the influence of future (2050) land use on a simulated PBL development within the WRF Model. Three primary areas of LULCC were identified within the FORE-SCE future LULC dataset across Nebraska and South Dakota. Variations in LULC between the 2005 LULC control simulation and four FORE-SCE simulations affected near-surface temperature (0.5°–1°C) and specific humidity (0.3–0.5 g kg−1). The differences noted in the temperature and moisture fields affected the development of the simulated PBL, leading to variations in PBL height and convective available potential energy. Overall, utilizing the FORE-SCE dataset within WRF produced notable differences relative to the control simulation over areas of LULCC represented in the FORE-SCE dataset.

Full access
Michael J. Hayes
,
Mark. D. Svoboda
,
Donald A. Wiihite
, and
Olga V. Vanyarkho

Droughts are difficult to detect and monitor. Drought indices, most commonly the Palmer Drought Severity Index (PDSI), have been used with limited success as operational drought monitoring tools and triggers for policy responses. Recently, a new index, the Standardized Precipitation Index (SPI), was developed to improve drought detection and monitoring capabilities. The SPI has several characteristics that are an improvement over previous indices, including its simplicity and temporal flexibility, that allow its application for water resources on all timescales. In this article, the 1996 drought in the southern plains and southwestern United States is examined using the SPI. A series of maps are used to illustrate how the SPI would have assisted in being able to detect the onset of the drought and monitor its progression. A case study investigating the drought in greater detail for Texas is also given. The SPI demonstrated that it is a tool that should be used operationally as part of a state, regional, or national drought watch system in the United States. During the 1996 drought, the SPI detected the onset of the drought at least 1 month in advance of the PDSI. This timeliness will be invaluable for improving mitigation and response actions of state and federal government to drought-affected regions in the future.

Full access
Jay Lawrimore
,
Richard R. Heim Jr.
,
Mark Svoboda
,
Val Swail
, and
Phil J. Englehart
Full access
Kelly Helm Smith
,
Mark E. Burbach
,
Michael J. Hayes
,
Patrick E. Guinan
,
Andrew J. Tyre
,
Brian Fuchs
,
Tonya Haigh
, and
Mark D. Svoboda

Abstract

Drought-related decision-making and policy should go beyond numeric hydrometeorological data to incorporate information on how drought affects people, livelihoods, and ecosystems. The effects of drought are nested within environmental and human systems, and relevant data may not exist in readily accessible form. For example, drought may reduce forage growth, compounded by both late-season freezes and management decisions. An effort to gather crowdsourced drought observations in Missouri in 2018 yielded a much higher number of observations than did previous related efforts. Here we examine 1) the interests, circumstances, history, and recruitment messaging that coincided to produce a high number of reports in a short time; 2) whether and how information from volunteer observers was useful to state decision-makers and to U.S. Drought Monitor (USDM) authors; and 3) potential for complementary use of stakeholder and citizen science reports in assessing trustworthiness of volunteer-provided information. State officials and the Cattlemen’s Association made requests for reports, clearly linked to improving the accuracy of the USDM and the related financial benefit. Well-timed requests provided a focus for people’s energy and a reason to invest their time. State officials made use of the dense spatial coverage that observers provided. USDM authors were very cautious about a surge of reports coinciding closely with financial incentives linked to the Livestock Forage Disaster program. An after-the-fact comparison between stakeholder reports and parallel citizen science reports suggests that the two could be complementary, with potential for developing protocols to facilitate real-time use.

Open access
Jason A. Otkin
,
Yafang Zhong
,
Eric D. Hunt
,
Jeff Basara
,
Mark Svoboda
,
Martha C. Anderson
, and
Christopher Hain

Abstract

This study examines the evolution of soil moisture, evapotranspiration, vegetation, and atmospheric conditions during an unusual flash drought–flash recovery sequence that occurred across the south-central United States during 2015. This event was characterized by a period of rapid drought intensification (flash drought) during late summer that was terminated by heavy rainfall at the end of October that eliminated the extreme drought conditions over a 2-week period (flash recovery). A detailed analysis was performed using time series of environmental variables derived from meteorological, remote sensing, and land surface modeling datasets. Though the analysis revealed a similar progression of cascading effects in each region, characteristics of the flash drought such as its onset time, rate of intensification, and vegetation impacts differed between regions due to variations in the antecedent conditions and the atmospheric anomalies during its growth. Overall, flash drought signals initially appeared in the near-surface soil moisture, followed closely by reductions in evapotranspiration. Total column soil moisture deficits took longer to develop, especially in the western part of the region where heavy rainfall during the spring and early summer led to large moisture surpluses. Large differences were noted in how land surface models in the North American Land Data Assimilation System depicted soil moisture evolution during the flash drought; however, the models were more similar in their assessment of conditions during the flash recovery period. This study illustrates the need to use multiple datasets to track the evolution and impacts of rapidly evolving flash drought and flash recovery events.

Full access
David J. Lorenz
,
Jason A. Otkin
,
Mark Svoboda
,
Christopher R. Hain
,
Martha C. Anderson
, and
Yafang Zhong

Abstract

The U.S. Drought Monitor (USDM) classifies drought into five discrete dryness/drought categories based on expert synthesis of numerous data sources. In this study, an empirical methodology is presented for creating a nondiscrete USDM index that simultaneously 1) represents the dryness/wetness value on a continuum and 2) is most consistent with the time scales and processes of the actual USDM. A continuous USDM representation will facilitate USDM forecasting methods, which will benefit from knowledge of where, within a discrete drought class, the current drought state most probably lies. The continuous USDM is developed such that the actual discrete USDM can be reconstructed by discretizing the continuous USDM based on the 30th, 20th, 10th, 5th, and 2nd percentiles—corresponding with USDM definitions for the D4–D0 drought classes. Anomalies in precipitation, soil moisture, and evapotranspiration over a range of different time scales are used as predictors to estimate the continuous USDM. The methodology is fundamentally probabilistic, meaning that the probability density function (PDF) of the continuous USDM is estimated and therefore the degree of uncertainty in the fit is properly characterized. Goodness-of-fit metrics and direct comparisons between the actual and predicted USDM analyses during different seasons and years indicate that this objective drought classification method is well correlated with the current USDM analyses. In Part II, this continuous USDM index will be used to improve intraseasonal USDM intensification forecasts because it is capable of distinguishing between USDM states that are either far from or near to the next-higher drought category.

Full access