Agriculture is the backbone of many economies and provides livelihood to a significant proportion of the population in Africa. However, the sector is largely rainfed and faces considerable challenges due to the impacts of climate variability and change, resulting in increasing rainfall unpredictability. Despite recent advances in generating climate information services, many farmers do not have limited access to reliable climate information to make adaptive farm-level decisions. Studies have shown that even farmers with limited access still doubt the efficacy of the information and reject it or employ it as an alternative to their indigenous knowledge. Using the Pra River basin as a case, this study assessed how climate information influences farmers’ farm-level decisions by interviewing 382 farmers and evaluated the performance of seasonal forecasts from the European Centre for Medium-Range Weather Forecast (ECMWF) in meeting farmer’s needs. Rainfall onset, amount and cessation were the three most prioritised needs ranked in descending order. Most farmers preferred to receive climate information at a 2-month lead time. However, ECMWF-S5 only provided the second-ranked need (rainfall amount) at a 1-month lead time with the highest skill in forecasting rainfall in the study area at correlation coefficient, RMSE, and KGE within the ranges of 0.7–0.9, 40-53, and 0.6-0.8, respectively. The skill of ECMWF-S5 decreases with increasing lead times. ECMWF-S5 rainfall forecast information at a 1-month lead time is advisable and likely to positively impact the decision-making process for farming in the Pra River Basin. It is recommended that other forecast models, including Indigenous techniques, should be combined to improve the lead time of forecast and also to determine the onset and cessation of adaptive farming
Keywords: Climate Change, Climate information services, hydroclimatic needs, lead time, rainfall forecast, ECMWF-S5 model, forecast accuracy
Article submitted to Discovery Sustainability | This research was extracted from an MPhil thesis submitted to Kwame Nkrumah University of Science and Technology, Ghana. The study was funded by Carnegie Corporation, New York of the Future Africa Research Leadership Fellowship at the University of Pretoria and the International Foundation for Science, Stockholm, Sweden, through a grant [W_6201-2] to Enoch Bessah. We acknowledge the farmers, Directors of the Department of Agriculture and Extension Officers from the participating districts involved in this study. Moreover, we thank the Ghana Meteorological Agency for participation and appreciate ECMWF-S5 and GPCC data providers for making it accessible online.
