Using co-production to improve the appropriate use of sub-seasonal forecasts in Africa
| Autor: | Emmah Mwangi, Eniola Olaniyan, Pascal Moudi Igri, Richard Nzekwu, Patricia Nying'uro, Emma Visman, Oumar Konte, Kamoru A. Lawal, Victor S. Indasi, Elisabeth Thompson, Felipe M. de Andrade, Willis Ochieng, Elijah A. Adefisan, Cheikh Dione, Elias Nkiaka, Jesse Ashong, Chris Kiptum, Joshua Talib, Mary Kilavi, Richmond Konadu Amoah, Zewdu T. Segele, Linda Hirons, Steve Woolnough, Nana Kofi Opoku, Richard Muita, Jasper Batureine Mwesigwa, Masilin Gudoshava, Hussen Seid Endris, Victoria L. Boult, Benjamin Lamptey, Tidiane Diedhiou |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
H1-99
Atmospheric Science Global and Planetary Change Process management Disaster risk reduction Computer science Process (engineering) User-driven forecasting for Africa Testbed Context (language use) Actionbased forecasting Social sciences (General) Co-production Resource (project management) Operational forecasting testbed Meteorology and Climatology Preparedness Meteorology. Climatology Sustainability Sub-seasonal forecasting QC851-999 Bespoke |
| Zdroj: | Climate Services, Vol 23, Iss, Pp 100246-(2021) |
| ISSN: | 2405-8807 |
| Popis: | Forecasts on sub-seasonal to seasonal (S2S) timescales have huge potential to aid preparedness and disaster risk reduction planning decisions in a variety of sectors. However, realising this potential depends on the provision of reliable information that can be appropriately applied in the decision-making context of users. This study describes the African SWIFT (Science for Weather Information and Forecasting Techniques) forecasting testbed which brings together researchers, forecast producers and users from a range of African and UK institutions. The forecasting testbed is piloting the provision of real-time, bespoke S2S forecast products to decision-makers in Africa. Drawing on data from the kick-off workshop and initial case study examples, this study critically reflects on the co-production process. Specifically, having direct access to real-time data has allowed user-guided iterations to the spatial scale, timing, visualisation and communication of forecast products to make them more actionable for users. Some key lessons for effective co-production are emerging. First, it is critical to ensure there is sufficient resource to support co-production, especially in the early co-exploration of needs. Second, all the groups in the co-production process require capacity building to effectively work in new knowledge systems. Third, evaluation should be ongoing and combine meteorological verification with decision-makers feedback. Ensuring the sustainability of project-initiated services within the testbed hinges on integrating the knowledge-exchanges between individuals in the co-production process into shaping sustainable pathways for improved operational S2S forecasting within African institutions. |
| Databáze: | OpenAIRE |
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