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Developing seasonal rainfall scenarios for food security early warning |
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| Authors: | Gregory J Husak Christopher C Funk Joel Michaelsen Tamuka Magadzire Kirk P Goldsberry |
| Institution: | 1. Department of Geography, University of California, Santa Barbara, CA, 93106-4060, USA 2. Earth Resources and Observation Science Center, U.S. Geological Survey, 47914 252nd Street, Sioux Falls, SD, 57198-0001, USA 3. Southern African Development Community, Famine Early Warning Systems Network, Plot No. 54385, Central Business District, Private Bag 0095, Gaborone, Botswana 4. Department of Geography, Michigan State University, 673 Auditorium Road, Room 116, East Lansing, MI, 48824, USA |
| Abstract: | Rainfed agriculture in Sub-Saharan Africa accounts for 95 % of the local cereal production, impacting hundreds of millions of people. Early identification of poor rainfall conditions is a critical indicator of food security. As such, monitoring accumulated seasonal rainfall gives an important mid-season estimate of final accumulated totals. However, characterizing the remaining uncertainty in a season has largely been ignored by the food security community. This paper presents a new technique describing rainfall conditions over the duration of a crop-growing cycle by combining estimated rainfall-to-date with potential scenarios for the remaining season based on available satellite rainfall estimates, the common tool for rainfall analysis in Africa. The limited historical record provided by satellite rainfall estimates using previous seasons provides only a coarse view of likely seasonal totals. To combat this, scenarios developed by bootstrapping dekadal data to create synthetic seasons allow for a finer understanding of potential seasonal accumulations. Updating this throughout the season shows a narrowing envelope of seasonal totals, converging on the final seasonal result. The resulting scenarios inform the expectations for the final seasonal rainfall accumulation, allowing analysts to quantify and visualize the uncertainty in seasonal totals. Giving decision makers a tool for understanding the likelihood of specific rainfall amounts provides additional time to enact and mobilize efforts to reduce the impact of agricultural drought. |
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