Future changes and uncertainty in decision-relevant measures of East African climate

F. Jorge Bornemann, David P. Rowell (), Barbara Evans, Dan J. Lapworth, Kamazima Lwiza, David M.J. Macdonald, John H. Marsham, Kindie Tesfaye, Matthew J. Ascott and Celia Way
Additional contact information
F. Jorge Bornemann: Met Office Hadley Centre
David P. Rowell: Met Office Hadley Centre
Barbara Evans: University of Leeds
Dan J. Lapworth: British Geological Survey
Kamazima Lwiza: Stony Brook University
David M.J. Macdonald: British Geological Survey
John H. Marsham: University of Leeds
Kindie Tesfaye: International Maize and Wheat Improvement Center (CIMMYT)
Matthew J. Ascott: British Geological Survey
Celia Way: University of Leeds

Climatic Change, 2019, vol. 156, issue 3, No 6, 365-384

Abstract: Abstract The need for the development of adaptation strategies for climate change in Africa is becoming critical. For example, infrastructure with a long lifespan now needs to be designed or adapted to account for a future climate that will be different from the past or present. There is a growing necessity for the climate information used in decision making to change from traditional science-driven metrics to decision-driven metrics. This is particularly relevant in East Africa, where limited adaptation and socio-economic capacity make this region acutely vulnerable to climate change. Here, we employ an interdisciplinary consultation process to define and analyse a number of such decision-oriented metrics. These metrics take a holistic approach, addressing the key East African sectors of agriculture, water supply, fisheries, flood management, urban infrastructure and urban health. A multifaceted analysis of multimodel climate projections then provides a repository of user-focused information on climate change and its uncertainties, for all metrics and seasons and two future time horizons. The spatial character and large intermodel uncertainty of changes in temperature and rainfall metrics are described, as well as those of other relevant metrics such as evaporation and solar radiation. Intermodel relationships amongst metrics are also explored, with two clear clusters forming around rainfall and temperature metrics. This latter analysis determines the extent to which model weights could, or could not, be applied across multiple climate metrics. Further work must now focus on maximising the utility of model projections, and developing tailored risk-based communication strategies.

Date: 2019
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DOI: 10.1007/s10584-019-02499-2

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