Climate variability and change have been identified as major threats to important sectors that drive economic growth and sustainable development in Africa. The provision of tailor-made climate information services is increasingly gaining importance as a vital adaptation and mitigation strategy against the adverse effects of climate change and variability. While various co-design and co-production models have been used to tailor climate information services (CIS) in different parts of the world, there is hardly any rigorous evidence assessing their effectiveness in meeting users’ needs.

The main objective of this study is to assess the effectiveness of the Multidisciplinary Working Group (MWG) — a participatory model that fosters interactions among different actors who produce, translate, transfer, and use CIS, to ensure that climate information is appropriately tailored to meet the needs of end-users. More specifically, we analyze the effectiveness of the MWG in improving farmers’ awareness, access, and uptake of CIS, as well as how this information is used to inform decision-making by users.

Based on the findings of this case study, we highlight two broad lessons. First, there is a positive association between the existence of the MWG model and farmers’ awareness, access, and use of CIS, as well as in influencing farm management decisions. This is encouraging and suggests that participatory approaches in the provision of tailored climate information and advisory services can lead to higher uptake and use among end-users. Second, these results demonstrate that the MWG model may well be instrumental in increased uptake of CIS in the Kaffrine region, which could offer lessons in the design, implementation, monitoring and evaluation, and scaling of similar initiatives to the rest of Senegal and other countries in Africa and beyond. It is important to highlight that this study does not analyze the impact of CIS use on higher-order welfare outcomes such as household food security, income, or poverty, which requires long-term seasonal data collected from the same farms.