A new global reference evapotranspiration reanalysis: global opportunities in operational drought monitoring and famine early warning
Journal Article
Overview
abstract
Data-sparse hydroclimates across the globe are often the most vulnerable to climate shocks and their populations to food insecurity. Drought monitoring and famine early warning in these regions have for too long relied on poor parameterizations of atmospheric evaporative demand (E0)—no less than the demand side of drought and of consumptive use by agriculture—either relying on physically poor process representations of E0 or on climatological mean estimates. However, by exploiting the advent of long-term, spatially distributed, and accurate reanalyses of the land-atmosphere system and its drivers we can put new data to use to save livelihoods and lives by improving drought monitoring, famine early warning, and multi-scale agricultural risk assessment.Here we describe one such effort—to create a daily, long-term, accurate, global operational dataset of E0. Funded by the Famine Early Warning Systems Network (FEWS NET) and its partners, we have developed a nearly 42-year long, daily, 0.125-degree, global dataset of Penman-Monteith reference evapotranspiration as a fully physical metric of E0. This new E0 dataset is driven by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2)—an accurate, fine-resolution land-surface/atmosphere reanalysis. We verified the accuracy of the dataset against (i) point-estimates of E0 derived by Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) initiative in Southern Africa, a region with sparse ground-truth data and significant humanitarian need, and (ii) on a spatially distributed basis against E0 derived from other reanalyses (Global Data Assimilation System and Princeton Global Forcing) that, although global, are otherwise unsuitable for operational food-security decision-making.We summarize the various uses to which the new E0 dataset is already being put in support of food-security monitoring and decision-making in food-insecure countries within the FEWS NET framework: to provide input data for a global implementation of the Evaporative Demand Drought Index (EDDI), which examines anomalies in E0 to permit early warning and ongoing monitoring of agricultural flash drought and hydrologic drought, both crucial drivers of food insecurity; and to diagnose the anomalies in E0 that lead to or signal drought into the relative contributions from its drivers, examining canonical droughts across Africa (e.g., the 2015 drought in Malawi, and the 2016 Horn of Africa drought, and the current multi-year East African drought). We also present use-cases that verify the operational applicability of the new E0 dataset in long-established drought, famine, crop- and pastoral-stress metrics, and in predictability assessments of drought forecasts. Driven by this new dataset, these analyses should significantly contribute to a more holistic understanding of drought and food-security across the African continent and the rest of the world.
