Development of methods for the probabilistic assessment of climate change impacts on crop production

Reimund P. Rötter, Mikhael A. Semenov

Abstract


Various attempts have been made to determine the relative importance of uncertainties in climate change impact assessments stemming from climate projections and crop models, respectively, and to analyse yield outputs probabilistically. For example, in the ENSEMBLES project, probabilistic climate projections (Harris et al. 2010) have been applied in conjunction with impact response surfaces (IRS), constructed by using impact models, to estimate the future likelihood (risk) of exceeding critical thresholds of crop yield impact (see, Fronzek et al., 2011, for an explanation of the method). In this task, we aimed to further develop and operationalize these methods and testing them in different case study regions in Europe. The method combines results of a sensitivity analysis of (one or more) impact model(s) with probabilistic projections of future temperature and precipitation (Fronzek et al., 2011). Such an overlay is one way of portraying probabilistic estimates of future impacts. By further accounting for the uncertainties in crop and biophysical parameters (using perturbed parameter approaches), the outcome represents an ensemble of impact risk estimates, encapsulating both climate and crop model uncertainties.


Keywords


impact response surface, models, sensitivity, ensembles

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References


Børgesen CD, Olesen JE (2011) A probabilistic assessment of climate change impacts on yield and nitrogen leaching from winter wheat in Denmark. Natural Hazards and Earth System Science 11:2541–2553

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Fronzek S, Carter TR, Räisänen J, Ruokolainen L, Luoto M (2010) Applying probabilistic projections of climate change with impact models: a case study for sub-arctic palsa mires in Fennoscandia. Climatic Change 99:515–534

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Rötter RP, Höhn J, Fronzek S (2012). Projections of climate change impacts on crop production – a global and a Nordic perspective. Acta Agriculturae Scandinavica, Section A (Special Issue), 62(4), p. 166-180, doi:10.1080/09064702.2013.793735.





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