Impact-based drought forecasting for agro-pastoralists in the Horn of Africa drylands

Vollständiger Abstract

Worum geht es in dieser Arbeit?

<p>Drought currently threatens the food security of 26 million people in the Horn of Africa, and without urgent action this could have a devastating impact during the first half of 2022. Local agro-pastoralists living in the Horn of Africa drylands are among the most vulnerable people to these droughts. Drought forecasts are crucial for them to prepare, as these allow for life-saving forecast-based actions. However, there is a mismatch between forecasts and the impacts felt on the ground leading to local agro-pastoralists not using these forecasts.<br><br>Therefore, we will develop and evaluate impact-based forecasting techniques for agro-pastoralists in the Horn of Africa using the TAMSAT-ALERT early-warning system. Over Kenya, these ensemble forecasts indicate a good relationship to pasture availability (NDVI/VCI) and maize yield, and can reliably anticipate drought conditions (<20^th percentile soil moisture) up to 2 months before the end of the season. We build further on these results by testing its capabilities to forecast more specific drought variables relevant for agro-pastoralists. This includes a transition to drought (i.e. the drought onset), drought duration, the occurrence of dry spells in the rainy season, and possibly wet periods during the dry season. Moreover, we will assess how these variables relate to drought impacts, using impact data on livestock losses and IPC Acute Food Insecurity Classifications from FEWS-NET. This will pave the way for an estimation of the capabilities of TAMSAT-ALERT to serve as an impact-based forecasting system in African drylands.<br><br>Furthermore, we will improve the model by integrating ensemble sub-seasonal European Centre for Medium-Range Weather Forecasts (ECMWF) precipitation forecasts, and will evaluate how much these forecasts increase the forecast accuracy of TAMSAT-ALERT. Using the potential economic value theory to trigger anticipatory action, we will reveal on when effective anticipatory actions can best be triggered, such as distribution of emergency fodder or migration of pastoralists. These research steps will provide decision-makers with tailored drought forecasts and decision-support, which will be crucial to increase drought resilience in African drylands.<img src="data:image/png;base64, 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