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The Evaporative Demand Drought Index. Part I: Linking Drought Evolution to Variations in Evaporative Demand

Michael T. Hobbins, Andrew Wood , Daniel J. McEvoy, Justin L. Huntington, Charles Morton, Martha Anderson, Christopher Hain, | March 1, 2016
Summary

Many operational drought indices focus primarily on precipitation and temperature when depicting hydroclimatic anomalies, and this perspective can be augmented by analyses and products that reflect the evaporative dynamics of drought. The linkage between atmospheric evaporative demand E0 and actual evapotranspiration (ET) is leveraged in a new drought index based solely on E0—the Evaporative Demand Drought Index (EDDI). EDDI measures the signal of drought through the response of E0 to surface drying anomalies that result from two distinct land surface–atmosphere interactions: 1) a complementary relationship between E0 and ET that develops under moisture limitations at the land surface, leading to ET declining and increasing E0, as in sustained droughts, and 2) parallel ET and E0 increases arising from increased energy availability that lead to surface moisture limitations, as in flash droughts. To calculate EDDI from E0, a longterm, daily reanalysis of reference ET estimated from the American Society of Civil Engineers (ASCE) standardized reference ET equation using radiation and meteorological variables from the North American Land Data Assimilation System phase 2 (NLDAS-2) is used. EDDI is obtained by deriving empirical probabilities of aggregated E0 depths relative to their climatologic means across a user-specific time period and normalizing these probabilities. Positive EDDI values then indicate drier-than-normal conditions and the potential for drought. EDDI is a physically based, multiscalar drought index that that can serve as an indicator of both flash and sustained droughts, in some hydroclimates offering early warning relative to current operational drought indices. The performance of EDDI is assessed against other commonly used drought metrics across CONUS in Part II.

Product Description

Many operational drought indices focus primarily on precipitation and temperature when depicting hydroclimatic anomalies, and this perspective can be augmented by analyses and products that reflect the evaporative dynamics of drought. The linkage between atmospheric evaporative demand E0 and actual evapotranspiration (ET) is leveraged in a new drought index based solely on E0—the Evaporative Demand Drought Index (EDDI). EDDI measures the signal of drought through the response of E0 to surface drying anomalies that result from two distinct land surface–atmosphere interactions: 1) a complementary relationship between E0 and ET that develops under moisture limitations at the land surface, leading to ET declining and increasing E0, as in sustained droughts, and 2) parallel ET and E0 increases arising from increased energy availability that lead to surface moisture limitations, as in flash droughts. To calculate EDDI from E0, a longterm, daily reanalysis of reference ET estimated from the American Society of Civil Engineers (ASCE) standardized reference ET equation using radiation and meteorological variables from the North American Land Data Assimilation System phase 2 (NLDAS-2) is used. EDDI is obtained by deriving empirical probabilities of aggregated E0 depths relative to their climatologic means across a user-specific time period and normalizing these probabilities. Positive EDDI values then indicate drier-than-normal conditions and the potential for drought. EDDI is a physically based, multiscalar drought index that that can serve as an indicator of both flash and sustained droughts, in some hydroclimates offering early warning relative to current operational drought indices. The performance of EDDI is assessed against other commonly used drought metrics across CONUS in Part II.

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Keywords:

atmospheric evaporative demand (Eo), Desert Research Institute (DRI), drought, evaporative transpiration (ET), National Oceanic and Atmospheric Administration (NOAA), U.S. Department of Agriculture (USDA), University of Maryland, water supply forecasting