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Application of real time S2S forecasts over Eastern Africa in the co-production of climate services

Gudoshava, M., Wanzala, M., Thompson, E., Mwesigwa, J., Endris, H. S., Segele, Z., Hirons, L. ORCID:, Kipkogei, O., Mumbua, C., Njoka, W., Baraibar, M., de Andrade, F., Woolnough, S. ORCID:, Atheru, Z. and Artan, G. (2022) Application of real time S2S forecasts over Eastern Africa in the co-production of climate services. Climate Services, 27. 100319. ISSN 2405-8807

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To link to this item DOI: 10.1016/j.cliser.2022.100319


A significant proportion of the population in Sub-Saharan Africa are vulnerable to extreme climatic conditions, hence there is a high demand for climate information. In response to this need, the Global Challenges Research Fund African Science for Weather Information and Forecasting Techniques has been undertaking a two-year testbed to co-produce tailored forecasts for different sectors using the sub-seasonal to seasonal forecast data- sets from the sub-seasonal to seasonal Real Time Pilot Initiative project. Sub-seasonal forecasts are essential for early warning and informed decision-making in the agriculture and food security sector. This study summarises the co-production process of climate services between the Intergovernmental Authority on Development (IGAD) Climate Prediction and Applications Centre and the Food Security and Nutrition Working Group for Eastern and Central Africa, highlighting the importance of efficient communication as well as the lessons learnt and chal- lenges faced in the co-production process. A case study approach is utilised to evaluate the model performance. Two contrasting case studies, one for an extreme rainfall event in week three in April and another for the evolution of tropical cyclone Gati were conducted for the year 2020. Skillful and timely climate information and services co-produced has the potential to increase the uptake, ownership, and appropriate use of sub-seasonal forecasts for resilience building in Eastern Africa.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:106313


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