Using global climate model simulations for outlooks on how climate change affects future diarrhoea risks

Climate models are not designed to provide detailed information on local rainfall that may trigger an outbreak of diarrhoea, but are nevertheless able to reproduce large-scale climatic conditions, processes, and phenomena. Hence, they have a minimum skillful scale, and downscaling makes use of skilfully simulated large-scale aspects in addition to information about how local rainfall depends on those larger scale conditions. The SPRINGS project studies the link between climate change and diarrhoea outbreak through a chain of models, where one stage provides input to the next. It’s important to design such model chains so that they provide a flow of salient and relevant information. This framework also needs to ensure robust results, as different global climate model simulations may give a different regional outlooks. It also needs to involve proper evaluation, and it's important that it is designed for both how the end-results are being used in decision-making, and that the end-results are correctly interpreted in terms of what they really represent. Here, such a framework used in SPRINGS is presented.