Using global and regional crop models to inform adaptation

Lead Research Organisation: University of Leeds
Department Name: School of Earth and Environment

Abstract

The global imperative is to enable adaptation to changes in the world's climates if we are to succeed in delivering global food security. One of the challenges of adaptation is being able to know in advance and with some degree of certainty what the effects of climate change will be on our ability to grow crops. Crop modelling is an established scientific method for predicting the impacts of climate on food production. Predictions are made for general or specific contexts on either global or regional scales. The uncertainty inherent in the information produced by predictive models is a contributing barrier to the use of this information in adaptation planning. This CASE studentship will explore this problem by looking at how scaling in impact modelling affects the meaningful use of impact assessments for adaption planning.Existing stakeholder networks will be used to ensure that the regional-scale assessments are useful. The project will also reduce the uncertainty in global scale assessments of crop yield, thus providing more robust evidence for policy makers.
Crop models will be used to make directly-comparable assessments of impacts at both regional and global scales. This studentship will explore how regional and global studies might be used synergistically to develop regional adaptation options and deliver global-scale assessment of impacts and adaptation. The underlying research questions for this aim are:
1. What is the value of the greater detail used in regional impacts studies for the skill of a given impacts model?
2. What are the potential synergies between global and regional-scale impacts models? The student will determine, for example, whether the value of regional models is primarily through model calibration techniques or improved data quality.

Publications

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