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Open AccessArticle

Seasonal Forecasting of the Onset of the Rainy Season in West Africa

1
Institute of Geography, University of Augsburg, 86159 Augsburg, Germany
2
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Campus Alpin, 82467 Garmisch-Partenkirchen, Germany
3
Competence Center, West African Science Service Centre on Climate Change and Adapted Land Use, Ouagadougou 9507, Burkina Faso
4
Training and Research Department, AGRHYMET Regional Centre, Niamey PB 11011, Niger
*
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(9), 528; https://doi.org/10.3390/atmos10090528
Received: 31 July 2019 / Revised: 27 August 2019 / Accepted: 2 September 2019 / Published: 8 September 2019
(This article belongs to the Special Issue Improved (Sub)Seasonal Climate Forecast for Impact Modelling)
Seasonal forecasts for monsoonal rainfall characteristics like the onset of the rainy seasons (ORS) are crucial for national weather services in semi-arid regions to better support decision-making in rain-fed agriculture. In this study an approach for seasonal forecasting of the ORS is proposed using precipitation information from a global seasonal ensemble prediction system. It consists of a quantile–quantile-transformation for eliminating systematic differences between ensemble forecasts and observations, a fuzzy-rule based method for estimating the ORS date and graphical methods for an improved visualization of probabilistic ORS forecasts. The performance of the approach is tested for several climate zones (the Sahel, Sudan and Guinean zone) in West Africa for a period of eleven years (2000 to 2010), using hindcasts from the Seasonal Forecasting System 4 of ECMWF. We indicated that seasonal ORS forecasts can be skillful for individual years and specific regions (e.g., the Guinean coasts), but also associated with large uncertainties. A spatial verification of the ORS fields emphasizes the importance of selecting appropriate performance measures (e.g., the anomaly correlation coefficient) to avoid an overestimation of the forecast skill. The graphical methods consist of several common formats used in seasonal forecasting and a new index-based method for a quicker interpretation of probabilistic ORS forecast. The new index can also be applied to other seasonal forecast variables, providing an important alternative to the common forecast formats used in seasonal forecasting. Moreover, the forecasting approach proposed in this study is not computationally intensive and is therefore operational applicable for forecasting centers in tropical and subtropical regions where computing power and bandwidth are often limited. View Full-Text
Keywords: seasonal forecasts; onset of the rainy season; bias correction; spatial verification; fuzzy logic; West Africa seasonal forecasts; onset of the rainy season; bias correction; spatial verification; fuzzy logic; West Africa
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Rauch, M.; Bliefernicht, J.; Laux, P.; Salack, S.; Waongo, M.; Kunstmann, H. Seasonal Forecasting of the Onset of the Rainy Season in West Africa. Atmosphere 2019, 10, 528.

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