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.