Original Paper

Theoretical and Applied Climatology

, Volume 114, Issue 1, pp 291-302

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Developing seasonal rainfall scenarios for food security early warning

  • Gregory J. HusakAffiliated withDepartment of Geography, University of California Email author 
  • , Christopher C. FunkAffiliated withDepartment of Geography, University of CaliforniaEarth Resources and Observation Science Center, U.S. Geological Survey
  • , Joel MichaelsenAffiliated withDepartment of Geography, University of California
  • , Tamuka MagadzireAffiliated withSouthern African Development Community, Famine Early Warning Systems Network
  • , Kirk P. GoldsberryAffiliated withDepartment of Geography, Michigan State University


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.