Paper short abstract:

This paper explores methods of co-production of knowledge between forecast users, social scientists, meteorologists and local forecasters focusing on equally valuing different sources of knowledge to enable a greater uptake of Met Office generated climate information by farmers in Burkina Faso.

Paper long abstract:

Climate change is having significant impact on climate extremes in West Africa. Moreover, it is affecting the indigenous indicators that farmers in these regions have used to predict the weather and seasonal climate. Conversely, scientific data, generated by Meteorological Offices worldwide, is becoming increasingly able to forecast weather and climate which could increase people's resilience to climate shocks. However, many barriers exist in making this information accessible, relevant and useable for people at risk including illiteracy and lack of access to radio or smartphones. Access to information also differs across socio-economic and gender delineations. In addition, there often exists a lack of trust in scientific data and a preference for long-held indigenous knowledge and techniques for forecasting.

This research, funded by NERC Innovation Placement scheme, focuses on identifying conditions necessary for co-producing consensus forecasts which focus on equally valuing different sources of knowledge, such as local indicators as well as scientific knowledge. What spaces and processes could enable farming households in Burkina Faso, traditional forecasters and Meteorological Office scientists to change the way they perceive and value each other's knowledge concerning seasonal weather forecasts? The paper explores how participatory techniques can be used to create disruption in the current way stakeholders acknowledge and analyse forecasts in order to allow for a co-production process to happen. Co-produced consensus forecasts, equally valuing all sources of knowledge, would lead to greater uptake of scientific climate information which, in turn, would improve people's resilience to climate extremes.