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Flash Drought in CMIP5 Models

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  • 1 a Monash University, Melbourne, Victoria, Australia
  • | 2 b Australian Research Council Centre of Excellence for Climate Extremes, Melbourne, Victoria, Australia
  • | 3 c Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado
  • | 4 d National Oceanic and Atmospheric Administration/Physical Sciences Laboratory, Boulder, Colorado
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Abstract

“Flash drought” (FD) describes the rapid onset of drought on subseasonal times scales. It is of particular interest for agriculture because it can deplete soil moisture for crop growth in just a few weeks. To better understand the processes causing FD, we evaluate the importance of evaporative demand and precipitation by comparing three different drought indices that estimate this hazard using meteorological and hydrological parameters from the CMIP5 suite of models. We apply the standardized precipitation index (SPI); the evaporative demand drought index (EDDI), derived from evaporative demand E0; and the evaporative stress index (ESI), which connects atmospheric and soil moisture conditions by measuring the ratio of actual and potential evaporation. The results show moderate-to-strong relationships (r2 > 0.5) between drought indices and upper-level soil moisture on daily time scales, especially in drought-prone regions. We find that all indices are able to identify FD in the top 10-cm layer of soil moisture in a similar proportion to that in the models’ climatologies. However, there is significant intermodel spread in the characteristics of the FDs identified. This spread is mainly caused by an overestimation of E0, indicating stark differences in the land surface models and coupling in individual CMIP5 models. Of all indices, the SPI provides the highest skill in predicting FD prior to or at the time of onset in soil moisture, while both EDDI and ESI show significantly lower skill. The results highlight that the lack of precipitation is the main contributor to FDs in climate models, with E0 playing a secondary role.

Significance Statement

This study is the first to assess the representation of rapidly developing drought, commonly referred to as flash drought, in global coupled climate models. This study elucidates how these models simulate flash drought and how they represent flash drought processes to allow for assessment in a changing climate. The work is also the first to compare the skill of drought indices based on precipitation and evaporative demand E0 for flash drought early detection on a global scale. We show that precipitation deficits are the main contributor to flash drought in climate models, with E0 playing a secondary role. However, an overestimation of E0 in some models causes significant intermodel disagreement, reflecting differences in the representation of land–atmosphere interactions.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JHM-D-20-0262.s1.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Publisher’s Note: This article was revised on 25 May 2021 to correct a mistake in the affiliations of the first two authors.

Corresponding author: David Hoffmann, david.hoffmann@monash.edu

Abstract

“Flash drought” (FD) describes the rapid onset of drought on subseasonal times scales. It is of particular interest for agriculture because it can deplete soil moisture for crop growth in just a few weeks. To better understand the processes causing FD, we evaluate the importance of evaporative demand and precipitation by comparing three different drought indices that estimate this hazard using meteorological and hydrological parameters from the CMIP5 suite of models. We apply the standardized precipitation index (SPI); the evaporative demand drought index (EDDI), derived from evaporative demand E0; and the evaporative stress index (ESI), which connects atmospheric and soil moisture conditions by measuring the ratio of actual and potential evaporation. The results show moderate-to-strong relationships (r2 > 0.5) between drought indices and upper-level soil moisture on daily time scales, especially in drought-prone regions. We find that all indices are able to identify FD in the top 10-cm layer of soil moisture in a similar proportion to that in the models’ climatologies. However, there is significant intermodel spread in the characteristics of the FDs identified. This spread is mainly caused by an overestimation of E0, indicating stark differences in the land surface models and coupling in individual CMIP5 models. Of all indices, the SPI provides the highest skill in predicting FD prior to or at the time of onset in soil moisture, while both EDDI and ESI show significantly lower skill. The results highlight that the lack of precipitation is the main contributor to FDs in climate models, with E0 playing a secondary role.

Significance Statement

This study is the first to assess the representation of rapidly developing drought, commonly referred to as flash drought, in global coupled climate models. This study elucidates how these models simulate flash drought and how they represent flash drought processes to allow for assessment in a changing climate. The work is also the first to compare the skill of drought indices based on precipitation and evaporative demand E0 for flash drought early detection on a global scale. We show that precipitation deficits are the main contributor to flash drought in climate models, with E0 playing a secondary role. However, an overestimation of E0 in some models causes significant intermodel disagreement, reflecting differences in the representation of land–atmosphere interactions.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JHM-D-20-0262.s1.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Publisher’s Note: This article was revised on 25 May 2021 to correct a mistake in the affiliations of the first two authors.

Corresponding author: David Hoffmann, david.hoffmann@monash.edu

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