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The onset and cessation of seasonal rainfall over Africa

2016/09/17 by C. Dunning, Emily Black, Richard P. Allan · 4 citations
Earth and Planetary Sciences · Environmental Science · Mathematics · #Agriculture #Cartography #Climate change #Climate variability and models #Climatology #Environmental science #Geography #Geology #Interim #Mathematics #Meteorological Phenomena and Simulations #Observational study #Oceanography #Precipitation Measurement and Analysis #Seasonality #Statistics #Wet season

paper · pdf · doi:10.1002/2016jd025428

openalex publication_date 2016/09/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31

Abstract

Abstract Variation in the seasonal cycle of African rainfall is of key importance for agriculture. Here an objective method of determining the timing of onset and cessation is, for the first time, extended to the whole of Africa. The method is applied to five observational data sets and the ERA‐Interim reanalysis. Compatibility with known physical drivers of African rainfall, consistency with indigenous methods, and generally strong agreement between satellite‐based rainfall data sets confirm that the method is capturing the correct seasonal progression of African rainfall. The biannual rainfall regime is correctly identified over the coastal region of Ghana and the Ivory Coast. However, the ERA‐Interim reanalysis exhibits timing biases over areas with two rainy seasons, and both ERA‐Interim and the ARCv2 observational data set exhibit some inconsistent deviations over West Africa. The method can be used to analyze both seasonal‐interannual variability and long‐term change. Over East Africa, we find that failure of the rains and subsequent humanitarian disaster is associated with shorter as well as weaker rainy seasons, e.g., on average the long rains were 11 days shorter in 2011. Cessation of the short rains over this region is 7 days later in El Niño and 5 days earlier in La Niña years with only a small change in onset date. The methodology described in this paper is applicable to multiple data sets and to large regions, including those that experience multiple rainy seasons. As such, it provides a means for investigating variability and change in the seasonal cycle over the whole of Africa.

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