Abstract
This study aimed at establishing and quantifying the evolution and socio-economic impacts of extreme rainfall events in October 2019. The study also focused on ascertaining the extent to which the Indian Ocean Dipole (IOD) and the El Ni?o Southern Oscillation (ENSO) influenced anomalous rainfall over East Africa (EA) in October 2019. It employed Singular Value Decomposition (SVD) methods to analyze inter-annual variability of EA rainfall and the Sea Surface Temperature Anomalies (SSTA) over the Indian and Pacific Ocean with a focus on October to December 2019 rainfall season. The SVD analysis enabled the exploration of the leading modes from the mean monthly rainfall and SSTs leading to the determination of the likely influence of the IOD and ENSO respectively. The first SVD coupled modes, which dominate the co-variability between the October rainfall over the EA domain, and SSTA over the Indian and Pacific Oceans based on 1981 to 2010 climatology indicate the monopole positive co-variability with rainfall over the entire EA domain. The corresponding spatial pattern for the SSTA over the Indian Ocean (IO) recaptures the positive IOD event while the central equatorial Pacific Ocean (i.e., over Ni?o 3.4 region) reveals a monopole positive loading, a typical signal for the warm phase of ENSO. The positive rainfall anomaly over the EA during October is found to be associated with either the IOD event or ENSO condition events independently or in phase. However, the inter-annual variability between October rainfall over EA and ENSO reveals a moderate relationship (r = 0.4212) while a robust association (r = 0.7084) is revealed with IOD. Comparatively, the October 2019 rainfall anomaly peaks the highest in history over the EA and was found to be coupled with highest positive IOD event in record. Unlikely, the 1997 October rainfall (which peaked the second in history), was associated with the co-occurrence of the positive phase of ENSO and IOD events. The findings of this study suggest that the positive IOD coupled mode had large impact on the distribution and variability of the October 2019 rainfall over the EA region.
Highlights
The livelihood and socio-economic development of majority of the people in East African countries including Tanzania, Kenya, Uganda, Burundi and Rwanda largely depend on rain-fed agricultural activities
The Singular Value Decomposition (SVD) analysis in this study explored the leading climatic modes from the mean monthly rainfall over East Africa (EA) and Sea Surface Temperature (SST) over the Indian and Pacific Oceans and their associated principal components (PCs), which further ascertained the likely influence of the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO) modulation towards enhancing extreme rainfall during October, 2019
This was achieved by comparing the global precipitation climatology center (GPCC) and CHIRPS data and observed station data over Tanzania
Summary
The livelihood and socio-economic development of majority of the people in East African countries including Tanzania, Kenya, Uganda, Burundi and Rwanda largely depend on rain-fed agricultural activities. The production and productivity in agricultural and other socio-economic activities are largely influenced by the distribution of rainfall and associated variability [1]. There are multiple factors responsible for modulating rainfall distribution in the region; these include the Inter-Tropical Convergence Zone (ITCZ), the Sea Surface Temperature (SST) over the global Oceans (i.e., the El Niño southern oscillation, ENSO and the Indian Ocean Dipole, IOD mode), and Tropical cyclones among others These large-scale drivers for the inter-annual East African rainfall variability are well described by a number of researchers [9] [13] [14] [15] [16]
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