A Modeling Strategy for Early Warning d on Off-Season Rains:Case Study Application on the January 2002 Extreme Case over Senegal and Mauritania

Extreme events represent a threat to vulnerable communities in West Africa. Strategic plans for early warning systems (EWS), at various time scales, are the responsibility of National Meteorological Services. In this region, ore attention is given to major weather and climate events occurring during the monsoon season. Western Sahel, mainly Senegal and Mauritania, is affected during the dry season by the so called off-season rains, which are for the most significant ones, long lasting light rains which cause damages from October to March, a window during which crops are still outside. It's a typical example of interaction between temperate and tropical region through interplay between different time and space scales atmospheric circulations. They are locally named “Heug” or “Mango rains” in local languages in Senegal. The case investigated in this study is one of the most severe and caused tremendous damages on crops and almost led to the loss of the livestock in both northern parts of Senegal and southern Mauritania. Because of the cold wave associated with the event and the intensity and amount of rainfall, 8 people were reported dead. In this study we highlight a modeling strategy in support to an early warning system which could mitigate the effect this system had. The Weather Research and Forecast model (WRF ARW v3.2) is used to simulate the event days ahead using a nesting technique to end up with high resolution (9 km) in the target area. The performance of the model in simulating the event is shown and used to further understand key dynamic and thermodynamic processes of the system. . The model was successfully able to simulate both timing and intensity of the event between 48 to 50 hours ahead. This falls in the short term forecast category and an appropriate coupling warning system base on global-mesoscale models can designed for these kinds of events between 8 to 10 days ahead.