Long-term spatial-temporal trends and variability of rainfall over Eastern and Southern Africa.
- Resource Type
- Article
- Authors
- Muthoni, Francis Kamau; Odongo, Vincent Omondi; Ochieng, Justus; Mugalavai, Edward M.; Mourice, Sixbert Kajumula; Hoesche-Zeledon, Irmgard; Mwila, Mulundu; Bekunda, Mateete
- Source
- Theoretical & Applied Climatology. Aug2019, Vol. 137 Issue 3/4, p1869-1882. 14p. 7 Diagrams, 1 Chart, 1 Graph, 2 Maps.
- Subject
- *RAINFALL
*RAINFALL anomalies
*RAIN gauges
*WATERSHEDS
*DROUGHTS
- Language
- ISSN
- 0177-798X
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. [ABSTRACT FROM AUTHOR]