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Building climate resilience: lessons of early warning in Africa

Boyd, E. and Cornforth, R. J. (2013) Building climate resilience: lessons of early warning in Africa. In: Moser, S. C. and Boykoff, M. T. (eds.) Successful Adaptation to Climate Change: Linking Science and Policy in a Rapidly Changing World. Routledge, pp. 201-219. ISBN 9780415524995

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Given the high levels of uncertainty and substantial variability in local weather and climate, what constitutes successful adaptation for the 800 million food-insecure people in Africa? In this context there is a need for building climate resilience through effective early warning systems, bringing real-time monitoring and decision-making together with stakeholders. The chapter presents two effective operational early warning systems in Africa: The Radio and Internet (RANET) network and the Rainwatch project. These examples were developed in partnership with local climate scientists and tailored to local development needs, enabled and encouraged with only modest international support. They deliver important lessons about how to prepare for crises using simple real-time monitoring. They also help us identify characteristics of managing for resilience in practice. The chapter concludes that successful adaptation requires adaptive, flexible, linked institutions, together with ground-based collaboration and practical tools. In the context of early warning three features stand out that make these systems successful: effective communication of current weather and climate information, a key individual within a bridging organization with the ability to navigate the governance systems, and sufficient time for innovation development.

Item Type:Book or Report Section
Divisions:Faculty of Science > School of Archaeology, Geography and Environmental Science > Human Environments
Faculty of Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
Faculty of Science > School of Mathematical, Physical and Computational Sciences > NCAS
ID Code:33786

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