Abstract
This study investigates the spatial-temporal trends and variability of rainfall within East and South Africa (ESA) region. The newly available Climate Hazards group Infrared Precipitation with Stations (CHIRPS-v2) gridded data spanning 37 years (1981 to 2017) was validated against gauge observations (N = 4243) and utilised to map zones experiencing significant monotonic rainfall trends. Standardised annual rainfall anomalies revealed the spatial-temporal distribution of below and above normal rains that are associated with droughts and floods respectively. Results showed that CHIRPS-v2 data had a satisfactory skill to estimate monthly rainfall with Kling-Gupta efficiency (KGE = 0.68 and a high temporal agreement (r = 0.73) while also preserving total amount (β = 0.99) and variability (γ = 0.8). Two contiguous zones with significant increase in annual rainfall (3–15 mm year−1) occurred in Southwest Zambia and in Northern Lake Victoria Basin between Kenya and Uganda. The most significant decrease in annual rainfall (− 20 mm year−1) was recorded at Mount Kilimanjaro in Tanzania. Other significant decreases in annual rainfall ranging between − 4 and − 10 mm year−1 were observed in Southwest Tanzania, Central-South Kenya, Central Uganda and Western Rwanda. CHIRPS-v2 rainfall product provides reliable high spatial resolution information on amount of rainfall that can complement sparse rain gauge network in rain-fed agricultural systems in ESA region. The observed spatial-temporal trends and variability in rainfall are important basis for guiding targeting of appropriate adaptive measures across multiple sectors.
Highlights
There is an increasing body of evidence supporting that climate change and variability have significant impact on ecosystem health (Bartzke et al 2018) and agricultural production (Craparo et al 2015; Niles et al 2015; Lobell et al 2011)
Over 70% of livelihoods in East and Southern Africa (ESA) region depends on rain-fed agriculture, highly vulnerable to climate change and variability (Ochieng et al 2017)
We posit that Climate Hazards group Infrared Precipitation with Stations (CHIRPS)-v2 rainfall estimates offer a reliable dataset for monitoring spatial-temporal trends and variability of rainfall over regions with low density of ground observation stations in Africa
Summary
There is an increasing body of evidence supporting that climate change and variability have significant impact on ecosystem health (Bartzke et al 2018) and agricultural production (Craparo et al 2015; Niles et al 2015; Lobell et al 2011). Understanding the spatial and temporal patterns of climate change and variability is a key step towards designing and targeting appropriate adaptation strategies. The repetitive and near global coverage of remote sensing platform compliments the gauge data by providing more intuitive spatial-temporal patterns of rainfall to improve decision support applications such as drought monitoring and early warning systems (Funk et al 2015; Toté et al 2015). The trend analyses identify zones experiencing significant increasing or decreasing rainfall trends This information is helpful in quantifying the magnitude of risks posed by climate change and variability to guide prioritisation of scarce resources by directing appropriate measures to most vulnerable zones. We posit that CHIRPS-v2 rainfall estimates offer a reliable dataset for monitoring spatial-temporal trends and variability of rainfall over regions with low density of ground observation stations in Africa
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