Harnessing local forecasting knowledge on weather and climate in Ghana : Documentation, skills, and integration with scientific forecasting knowledge
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.
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| Format: | Article/Letter to editor biblioteca |
| Language: | English |
| Subjects: | Africa, Agriculture, Climate prediction, Climate services, Decision support, Forecast verification/skill, |
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dig-wur-nl-wurpubs-5782372024-12-04 Gbangou, Talardia van Slobbe, Erik Ludwig, Fulco Kranjac-Berisavljevic, Gordana Paparrizos, Spyridon Article/Letter to editor Weather, Climate, and Society 13 (2021) 1 ISSN: 1948-8327 Harnessing local forecasting knowledge on weather and climate in Ghana : Documentation, skills, and integration with scientific forecasting knowledge 2021 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. en application/pdf https://research.wur.nl/en/publications/harnessing-local-forecasting-knowledge-on-weather-and-climate-in- 10.1175/WCAS-D-20-0012.1 https://edepot.wur.nl/540525 Africa Agriculture Climate prediction Climate services Decision support Forecast verification/skill Wageningen University & Research |
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Africa Agriculture Climate prediction Climate services Decision support Forecast verification/skill Africa Agriculture Climate prediction Climate services Decision support Forecast verification/skill Gbangou, Talardia van Slobbe, Erik Ludwig, Fulco Kranjac-Berisavljevic, Gordana Paparrizos, Spyridon Harnessing local forecasting knowledge on weather and climate in Ghana : Documentation, skills, and integration with scientific forecasting knowledge |
| description |
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. |
| format |
Article/Letter to editor |
| topic_facet |
Africa Agriculture Climate prediction Climate services Decision support Forecast verification/skill |
| author |
Gbangou, Talardia van Slobbe, Erik Ludwig, Fulco Kranjac-Berisavljevic, Gordana Paparrizos, Spyridon |
| author_facet |
Gbangou, Talardia van Slobbe, Erik Ludwig, Fulco Kranjac-Berisavljevic, Gordana Paparrizos, Spyridon |
| author_sort |
Gbangou, Talardia |
| title |
Harnessing local forecasting knowledge on weather and climate in Ghana : Documentation, skills, and integration with scientific forecasting knowledge |
| title_short |
Harnessing local forecasting knowledge on weather and climate in Ghana : Documentation, skills, and integration with scientific forecasting knowledge |
| title_full |
Harnessing local forecasting knowledge on weather and climate in Ghana : Documentation, skills, and integration with scientific forecasting knowledge |
| title_fullStr |
Harnessing local forecasting knowledge on weather and climate in Ghana : Documentation, skills, and integration with scientific forecasting knowledge |
| title_full_unstemmed |
Harnessing local forecasting knowledge on weather and climate in Ghana : Documentation, skills, and integration with scientific forecasting knowledge |
| title_sort |
harnessing local forecasting knowledge on weather and climate in ghana : documentation, skills, and integration with scientific forecasting knowledge |
| url |
https://research.wur.nl/en/publications/harnessing-local-forecasting-knowledge-on-weather-and-climate-in- |
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