Seasonal forecasting of East African short rains
Abstract The variability of East African short rains (October–December) has profound socioeconomic and environmental impacts on the region, making accurate seasonal rainfall predictions essential. We evaluated the predictability of East African short rains using model ensembles from the multi-system...
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Nature Portfolio
2025-01-01
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| author | Agumase Kindie Tefera Giovanni Liguori William Cabos Antonio Navarra |
| author_facet | Agumase Kindie Tefera Giovanni Liguori William Cabos Antonio Navarra |
| author_sort | Agumase Kindie Tefera |
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| description | Abstract The variability of East African short rains (October–December) has profound socioeconomic and environmental impacts on the region, making accurate seasonal rainfall predictions essential. We evaluated the predictability of East African short rains using model ensembles from the multi-system seasonal retrospective forecasts from the Copernicus Climate Change Service (C3S). We assess the prediction skill for 1- to 5-month lead times using forecasts initialized in September for each year from 1993 to 2016. Although most models exhibit significant mean rainfall biases, they generally show skill in predicting OND (October–December) precipitation anomalies across much of East Africa. However, skill is low or absent in some northern and western parts of the focus area. Along the East African coasts near Somalia and over parts of the western Indian Ocean, models demonstrate skill throughout the late winter (up to December–February), likely due to the persistence of sea surface temperature anomalies in the western Indian Ocean. Years when models consistently outperform persistence forecasts typically align with the mature phases of El Niño Southern Oscillation (ENSO) and/or Indian Ocean Dipole (IOD). This latter mode, when tracked using the Dipole Mode Index, is generally able to predict the sign of the rainfall anomaly in all models. Despite East Africa’s proximity to the west pole of the IOD, the correlation between short rains and IOD maximizes when both east and west are considered. This finding confirms previous studies based on observational datasets, which indicate that broader-scale IOD variability associated with changes in the Walker Circulation, rather than local SST fluctuations, is the primary driver behind East African rainfall. |
| format | Article |
| id | doaj-art-05a34b43e64d4da8ad51113a7671926b |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-05a34b43e64d4da8ad51113a7671926b2025-01-26T12:28:37ZengNature PortfolioScientific Reports2045-23222025-01-0115111010.1038/s41598-025-86564-0Seasonal forecasting of East African short rainsAgumase Kindie Tefera0Giovanni Liguori1William Cabos2Antonio Navarra3Department of Biological, Geological, and Environmental Sciences, University of BolognaDepartment of Biological, Geological, and Environmental Sciences, University of BolognaDepartment of Physics and Mathematics, University of AlcaláDepartment of Biological, Geological, and Environmental Sciences, University of BolognaAbstract The variability of East African short rains (October–December) has profound socioeconomic and environmental impacts on the region, making accurate seasonal rainfall predictions essential. We evaluated the predictability of East African short rains using model ensembles from the multi-system seasonal retrospective forecasts from the Copernicus Climate Change Service (C3S). We assess the prediction skill for 1- to 5-month lead times using forecasts initialized in September for each year from 1993 to 2016. Although most models exhibit significant mean rainfall biases, they generally show skill in predicting OND (October–December) precipitation anomalies across much of East Africa. However, skill is low or absent in some northern and western parts of the focus area. Along the East African coasts near Somalia and over parts of the western Indian Ocean, models demonstrate skill throughout the late winter (up to December–February), likely due to the persistence of sea surface temperature anomalies in the western Indian Ocean. Years when models consistently outperform persistence forecasts typically align with the mature phases of El Niño Southern Oscillation (ENSO) and/or Indian Ocean Dipole (IOD). This latter mode, when tracked using the Dipole Mode Index, is generally able to predict the sign of the rainfall anomaly in all models. Despite East Africa’s proximity to the west pole of the IOD, the correlation between short rains and IOD maximizes when both east and west are considered. This finding confirms previous studies based on observational datasets, which indicate that broader-scale IOD variability associated with changes in the Walker Circulation, rather than local SST fluctuations, is the primary driver behind East African rainfall.https://doi.org/10.1038/s41598-025-86564-0East Africa rainfallPredictability of short rainsSeasonal forecastingENSOIOD |
| spellingShingle | Agumase Kindie Tefera Giovanni Liguori William Cabos Antonio Navarra Seasonal forecasting of East African short rains Scientific Reports East Africa rainfall Predictability of short rains Seasonal forecasting ENSO IOD |
| title | Seasonal forecasting of East African short rains |
| title_full | Seasonal forecasting of East African short rains |
| title_fullStr | Seasonal forecasting of East African short rains |
| title_full_unstemmed | Seasonal forecasting of East African short rains |
| title_short | Seasonal forecasting of East African short rains |
| title_sort | seasonal forecasting of east african short rains |
| topic | East Africa rainfall Predictability of short rains Seasonal forecasting ENSO IOD |
| url | https://doi.org/10.1038/s41598-025-86564-0 |
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