TY - JOUR
T1 - Using co-production to improve the appropriate use of sub-seasonal forecasts in Africa
AU - Hirons, Linda
AU - Thompson, Elisabeth
AU - Dione, Cheikh
AU - Indasi, Victor S.
AU - Kilavi, Mary
AU - Nkiaka, Elias
AU - Talib, Joshua
AU - Visman, Emma
AU - Adefisan, Elijah A.
AU - de Andrade, Felipe
AU - Ashong, Jesse
AU - Mwesigwa, Jasper Batureine
AU - Boult, Victoria L.
AU - Diédhiou, Tidiane
AU - Konte, Oumar
AU - Gudoshava, Masilin
AU - Kiptum, Chris
AU - Amoah, Richmond Konadu
AU - Lamptey, Benjamin
AU - Lawal, Kamoru Abiodun
AU - Muita, Richard
AU - Nzekwu, Richard
AU - Nying'uro, Patricia
AU - Ochieng, Willis
AU - Olaniyan, Eniola
AU - Opoku, Nana Kofi
AU - Endris, Hussen Seid
AU - Segele, Zewdu
AU - Igri, Pascal Moudi
AU - Mwangi, Emmah
AU - Woolnough, Steve
N1 - Publisher Copyright:
© 2021 The Author(s)
PY - 2021/8
Y1 - 2021/8
N2 - 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.
AB - 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.
KW - Actionbased forecasting
KW - Co-production
KW - Operational forecasting testbed
KW - Sub-seasonal forecasting
KW - User-driven forecasting for Africa
UR - https://www.scopus.com/pages/publications/85112515478
U2 - 10.1016/j.cliser.2021.100246
DO - 10.1016/j.cliser.2021.100246
M3 - Article
AN - SCOPUS:85112515478
SN - 2405-8807
VL - 23
JO - Climate Services
JF - Climate Services
M1 - 100246
ER -