Sahelian West Africa is a region of high year-to-year climate variability that can significantly impact on communities and livelihoods. Adaptive social protection (ASP) is being introduced in the region to support vulnerable people through enabling more effective responses to climate shocks, bridging social protection with disaster risk reduction and climate change adaptation. The ASPIRE (Adaptive Social Protection: Information for enhanced REsilience) project aimed to provide technical support to the World Bank's Sahel Adaptive Social Protection Programme through demonstrating the use of climate forecasts in ASP and promoting dialogue between climate and social protection stakeholders.Here we discuss lessons learned in the project, highlighting challenges and opportunities for including climate forecasts in early warning systems to inform ASP. We provide recommendations to help achieve ASP systems designed to use climate forecasts, arguing that tailored seasonal forecast products have potential in some countries to improve the lead time of interventions to address climate-induced disasters. Critical to this is continued investment in underpinning science and capacity building of climate and social protection stakeholders, as well as strengthened dialogue between actors to co-develop climate forecasts that provide actionable information.

The South Asia Seasonal Climate Outlook Forum (SASCOF) issues seasonal tercile precipitation forecasts to provide advance warning of anomalously dry or wet monsoon seasons in South Asia. To increase objectivity of the SASCOF seasonal outlook, the World Meteorological Organisation recommends using a multi-model ensemble combining the most skilful dynamical seasonal models for the region. We assess the skill of 12 dynamical models at forecasting seasonal precipitation totals for 1993–2016 for the southwest (July-September) and northeast (October-December) monsoon seasons at both regional and national levels for Afghanistan, Bangladesh, Nepal, and Pakistan, using identical forecast periods, hindcast initialisation months and domain used at the SASCOF. All models demonstrate positive skill when regionally averaged, especially for the southwest monsoon season, noting considerable spatial differences. Models demonstrate highest skill in areas with strong ENSO teleconnections in the observations, e.g., central/north India and Nepal during the southwest monsoon, and Afghanistan and north Pakistan during the northeast monsoon. Models with higher skill typically simulate an exaggerated ENSO teleconnection. Model skill is especially low in northwest India and northeast of the region during the southwest monsoon, e.g., Bangladesh (despite high precipitation totals) coinciding with a weak ENSO teleconnection. The IOD teleconnection is less pronounced in the SW monsoon season, whereas the spatial pattern for the NE monsoon season closely resembles that of ENSO. Due to the high variability in model skill, we recommend including all models in the multi-model ensemble for the basis of the SASCOF forecast but discounting poorly performing models at the national level.

The South Asia Seasonal Climate Outlook Forum (SASCOF) issues seasonal tercile precipitation forecasts to provide advance warning of anomalously dry or wet monsoon seasons in South Asia. To increase objectivity of the SASCOF seasonal outlook, the World Meteorological Organisation recommends using a multi-model ensemble combining the most skilful dynamical seasonal models for the region. We assess the skill of 12 dynamical models at forecasting seasonal precipitation totals for 1993–2016 for the southwest (June–July–August–September) and northeast (October–November–December) monsoon seasons at regional and national levels for Afghanistan, Bangladesh, Nepal, and Pakistan, using identical forecast periods, hindcast initialisation months and domain used at the SASCOF. All models demonstrate positive skill when regionally-averaged, especially for the southwest monsoon season, noting considerable spatial differences. Models exhibit highest skill where correlation between observed precipitation and El Niño Southern Oscillation (ENSO) is highest, e.g., central/north India and Nepal during the southwest monsoon, and Afghanistan and north Pakistan during the northeast monsoon. Model skill is especially low in northwest India and northeast of South Asia during the southwest monsoon, e.g., Bangladesh (despite high precipitation totals) coinciding with a weak ENSO teleconnection. The Indian Ocean Dipole teleconnection is less pronounced in the southwest monsoon season, whereas the spatial pattern for the northeast monsoon closely resembles that of ENSO. Due to high variability in model skill, we recommend basing the SASCOF forecast on a multi-model ensemble of all models but discounting poorly performing models at the national level.