Publication: Predictability of intra-seasonal descriptors of rainy season over Senegal using global SST patterns
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2022
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Abstract
Seasonal forecasting of the rainfall characteristics in Sahel is of crucial interest in determining crop variability in these countries. This study aims to provide further characterization of nine rainfall metrics over Senegal (Onset, cessation, LRS, CDD, CDD7, CDD15, NR90p, NR95p, NR99p)and their response to global SST patterns from 1981 to 2018. The Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) dataset and the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) were used. The results showed strong spatio-temporal variability with a pronounced south–north gradient for all metrics. The earliest onset was observed in the south of the country from 4 July and the latest onset in the north from 9 August. Since 2012, a new regime is observed with an increase in both long dry spells and extreme wet events. Furthermore, SST forcing has shown that the North tropical Atlantic and the East Equatorial Pacific are better able to explain the interannual variability of the intraseasonal descriptors. However, the prediction of metrics is earlier for the most remote basin (Pacific) compared to the most local basin (Atlantic). These results have implications for the seasonal forecasting of Sahel’s intraseasonal variability based on SST predictors, as significant predictability is found far from the beginning of the season.
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© 2022 by the authors.
We thank the PNA-FEM project for funding the research that led to this paper. The LMI ECLAIRS 2 contributed significantly to this work. To this end, we thank this program, whose contribution was attributed to the author Touré, for helping with the realization of this study. We also thank the Department of Meteorology, Faculty of Physics, of the Universidad Complutense de Madrid (UCM).