Abstract
Improved weather and climate forecast information services are important to sustain small-scale crop production in many developing countries. Previous studies recognized the value of integrating local forecasting knowledge (LFK) with scientific forecasting knowledge (SFK) to support farmers’ decision-making. Yet, little work has focused on proper documentation, quality verification, and integration techniques. The skills of local and scientific forecasts were compared, and new integration approaches were derived over the coastal zone of Ghana. LFK indicators were documented, and farmers were trained to collect indicators’ observations and record rainfall in real time using digital tools and rain gauges, respectively, in 2019. Dichotomous forecasts verification metrics were then used to verify the skills of both local and scientific forecasts against rainfall records. Farmers use a diverse set of LKF indicators for both weather and seasonal climate time-scale predictions. LFK indicators are mainly used to predict rainfall occurrence, amount of seasonal rainfall, dry spell occurrence, and onset and cessation of the rainy season. The average skill of a set of LFK indicators in predicting one-day rainfall is higher than individual LFK indicators. Also, the skills of a set of LFK indicators can potentially be higher than the forecasts given by the Ghana Meteorological Agency for the Ada District. The results of the documentation and skills indicate that approaches and methods developed for integrating LFK and SFK can contribute to increasing forecast resolution and skills and reducing recurring tensions between the two knowledge systems. Future research and application of these methods can help improve weather and climate information services in Ghana.
Significance Statement
Most African farmers still rely on local or traditional knowledge on weather and climate forecasts to manage climate variability and change, although there is much effort to reach farmers with the increasing availability of scientific forecasts and data. Exploring the potential of local forecasts and the possible integration with modern forecasts has been suggested as a path to reach out to farmers with more accessible and credible climate information services (CIS). We aimed to understand the contribution of this local knowledge by documenting and investigating its quality. We found that local forecast indicators used by farmers are diverse, and their level of quality can potentially improve the development of CIS, especially when they are combined or integrated with scientific forecasts.
ORCID: 0000-0002-8929-7108.
Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/WCAS-D-20-0012.s1.
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