Abstract

Seasonal climate forecasts are crucial inputs for effective planning of adaptation to climate variability in the climate-sensitive development sectors. In West Africa, recommendations associated with seasonal forecasts are often based on expert judgment and assessment of the forecasts. This approach can be subjective and misleading, thus limiting the effectiveness of adaptation planning decision. This Info Note proposes a novel approach for translating seasonal forecasts into actionable sector-specific information. The approach proposed to use seasonal forecasts as inputs to sectorial biophysical and process-based models to generate actionable recommendations that are less sensitive to expert interpretation biases. Preliminary results of a case study application in Niger are presented to illustrate the approach. Application of the approach to the case of Niger has generated forecasts of sowing dates and yields of Millet and Sorghum, satisfaction index for water requirements at different developmental stages, and runoff forecasts for the season 2022-2023. Key findings illustrate the potential of using biophysical models to improve seasonal forecast information in the agricultural and water resource sectors. Further investigations and capacity building are required to refine approaches and facilitate the appropriation of lessons learned by NMHSs in view of a future adoption during West African Regional Climate Outlook Forum (RCOF).