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<p>The long rains in East Africa are vital for agriculture, water resources, and socio-economic stability, sustaining millions of livelihoods. However, their pronounced interannual variability exacerbates food insecurity, emphasizing the need to understand the region’s rainfall drivers. This study analyzed rainfall variability using Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) data (1981–2023). Empirical Orthogonal Function (EOF) analysis identified a dominant north–south spatial dipole pattern, explaining 27.6% of the variance. Singular Value Decomposition (SVD) highlighted the 600-hPa level as critical for rainfall co-variability with atmospheric variables, guiding composite analyses. Composite analysis of seven dry and eight wet neutral-phase periods revealed that negative sea surface temperature (SST) anomalies over the Indo-Atlantic basin associated with dry periods, while positive anomalies correspond to wet periods. Dry conditions are linked to a strengthened Azores High and weakened Mascarene Highs, whereas wet conditions show the opposite. The Azores High negatively correlates with rainfall, while the Mascarene High shows a positive correlation. Moist air masses from the equatorial Atlantic and Congo basin dominate during wet periods, while weakened dry periods. Negative outgoing longwave radiation (OLR) anomalies enhance wet conditions, while positive anomalies denote dry periods. Warmer temperatures align with wet periods and cooler temperatures with dry periods. In conclusion, the zonal wind at 600-hPa, OLR, and the sea level pressure difference between the Azores and Mascarene Highs were identified as the main contributors to precipitation variability and should be incorporated into modelling efforts. These findings provide crucial insights for improving precipitation modelling and developing robust climate resilience strategies in East Africa. Future research should explore the influence of teleconnection climate modes, such as the Quasi-Biennial Oscillation (QBO), and the mechanisms of the El Niño-Southern Oscillation (ENSO), and assess the impacts of land-use changes on rainfall variability.</p>

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Unravelling atmospheric factors associated with long rain precipitation variability in East Africa

  • 期刊论文

  • 发表日期：

    2025年2月3日

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  • Tewelde Berihu,
  • Wen Chen,
  • Lin Wang

摘要

The long rains in East Africa are vital for agriculture, water resources, and socio-economic stability, sustaining millions of livelihoods. However, their pronounced interannual variability exacerbates food insecurity, emphasizing the need to understand the region’s rainfall drivers. This study analyzed rainfall variability using Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) data (1981–2023). Empirical Orthogonal Function (EOF) analysis identified a dominant north–south spatial dipole pattern, explaining 27.6% of the variance. Singular Value Decomposition (SVD) highlighted the 600-hPa level as critical for rainfall co-variability with atmospheric variables, guiding composite analyses. Composite analysis of seven dry and eight wet neutral-phase periods revealed that negative sea surface temperature (SST) anomalies over the Indo-Atlantic basin associated with dry periods, while positive anomalies correspond to wet periods. Dry conditions are linked to a strengthened Azores High and weakened Mascarene Highs, whereas wet conditions show the opposite. The Azores High negatively correlates with rainfall, while the Mascarene High shows a positive correlation. Moist air masses from the equatorial Atlantic and Congo basin dominate during wet periods, while weakened dry periods. Negative outgoing longwave radiation (OLR) anomalies enhance wet conditions, while positive anomalies denote dry periods. Warmer temperatures align with wet periods and cooler temperatures with dry periods. In conclusion, the zonal wind at 600-hPa, OLR, and the sea level pressure difference between the Azores and Mascarene Highs were identified as the main contributors to precipitation variability and should be incorporated into modelling efforts. These findings provide crucial insights for improving precipitation modelling and developing robust climate resilience strategies in East Africa. Future research should explore the influence of teleconnection climate modes, such as the Quasi-Biennial Oscillation (QBO), and the mechanisms of the El Niño-Southern Oscillation (ENSO), and assess the impacts of land-use changes on rainfall variability.