Drought in Africa: Understanding and Exploiting the Demand Perspective Using a New Evaporative Demand Reanalysis
Journal Article
Overview
abstract
In operational analyses of the surface moisture imbalance that defines; drought, the supply aspect has generally been well characterized by; precipitation; however, the same count be said of the demand side—a; function of evaporative demand (E0) and surface moisture availability.; In drought monitoring, E0 is often poorly parameterized by a; climatological mean, by non-physically based estimates, or is neglected; entirely. One problem has been a paucity of driver data—on; temperature, humidity, solar radiation, and wind speed—required to; fully characterize E0. This deficient E0 modeling is particularly; troublesome over data-sparse regions that are also home to; drought-vulnerable populations, such as across much of Africa. There is; thus urgent need for global E0 estimates for physically accurate drought; analyses and food security assessments; further we need an improved; understanding of how E0 and drought interact and to exploit these; interactions in drought monitoring. In this presentation we explore ways; to meet these needs. From MERRA-2—an accurate, fine-resolution; land-surface/atmosphere reanalysis—we have developed a; >38-year, daily, global Penman-Monteith reference ET; dataset as a fully physical metric of E0. This dataset is valuable for; examining hydroclimatic changes and extremes. A novel drought index; based on this dataset—the Evaporative Demand Drought Index; (EDDI)—represents drought’s demand perspective, and permits early; warning and ongoing monitoring of agricultural flash drought and; hydrologic drought. We highlight the findings of our examination of; E0-drought interactions and using EDDI in Africa. Using reference ET as; an E0 metric has permitted explicit attribution of the variability of E0; across Africa, and of E0 anomalies associated with canonical droughts in; the Sahel region. This analysis determines where, when, and to what; relative degree each of the individual drivers of E0 affects the demand; side of drought. Using independent estimates of drought across space and; time—CHIRPS precipitation and the Normalized Difference Vegetation; Index for 1982-2015—we examine the differences between drought and; non-drought periods, and between precipitation-forced droughts and; droughts forced by a combination of precipitation and E0.
