Abstract
In this paper, the sea surface temperature (SST) based statistical seasonal forecast model (S4CAST) is utilized to examine the spatial and temporal prediction skill of Sahel heavy and extreme daily precipitation events. As in previous studies, S4CAST points out the Mediterranean Sea and El Niño Southern Oscillation (ENSO) as the main drivers of Sahel heavy/extreme daily rainfall variability at interannual timescales (period 1982–2015). Overall, the Mediterranean Sea emerges as a seasonal short-term predictor of heavy daily rainfall (1 month in advance), while ENSO returns a longer forecast window (up to 3 months in advance). Regarding the spatial skill, the response of heavy daily rainfall to the Mediterranean SST forcing is significant over a widespread area of the Sahel. Contrastingly, with the ENSO forcing, the response is only significant over the southernmost Sahel area. These differences can be attributed to the distinct physical mechanisms mediating the analyzed SST-rainfall teleconnections. This paper provides fundamental elements to develop an operational statistical-seasonal forecasting system of Sahel heavy and extreme daily precipitation events.
Highlights
The Sahel region is one of the most important observed climate change hotspots [1].Increasingly unpredictable weather patterns associated with extreme rainfall events contribute to threatening the livelihoods of the Sahelian population [2,3], whose subsistence is highly dependent on rainfed agriculture [4,5].Oceanic forcing is the dominant driver of the West African Monsoon (WAM) variability (e.g., [6,7]), while land-surface processes have an amplifying effect [8,9,10]
This is consistent with Suárez-Moreno [26] and D19, as these sea surface temperature (SST) variability patterns are identified at interannual timescales, and they appear highlighted for all rainfall indices (Figure 1a,c,e)
The present paper primarily focuses on heavy and extreme daily rainfall events
Summary
The Sahel region is one of the most important observed climate change hotspots [1]. Increasingly unpredictable weather patterns associated with extreme rainfall events contribute to threatening the livelihoods of the Sahelian population [2,3], whose subsistence is highly dependent on rainfed agriculture [4,5]. Energy is stored in the global oceans, to be subsequently released into the atmosphere via turbulent and radiative energy exchange at the sea surface This process takes place at much longer timescales (seasonal to multi-decadal) than those typically associated with short-term weather prediction (1–10 days). In this context, several studies have shown the influence of sea surface temperatures (SSTs) on the WAM interannual. Diakhaté [37] (hereafter D19), addressed this question for the first time They showed that Sahel heavy and extreme daily precipitation variability was mainly linked to ENSO and Mediterranean SST anomalies.
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