Model studies have shown that soil moisture anomaly has a significant impact on precipitation variability in model prediction. However, obtaining a full understanding of the impact of soil moisture on model prediction requires better understanding of the physics involved in surface-atmosphere interactions. This problem is compounded by the lack of soil moisture observations, particularly on a global scale. Efforts have recently begun that will provide soil moisture analysis data (e.g., GLDAS) which will aid this effort.

The objective of this study is to assess the impact of soil moisture initialization on model forecasts of seasonal precipitation in the West African Sahel. A key reason for studying this region is that studies have shown that soil moisture impact may be most significant in transition zones such as the Sahel. The results presented here will be from a preliminary analysis where the CVS version of the NCEP Regional Spectral Model is initialized with soil moisture from multiple sources including data assimilation (GLDAS) and AFWA Agricultural Meteorology Modeling System (AGRMET). The model precipitation will be compared to observed precipitation (gauge and satellite derived) as part of the assessment of the model’s sensitivity to soil moisture in this region.