Generating downscaled weather data from a suite of climate models for agricultural modelling applications

Jones, P.G. and Thornton, P.K. (2013) Generating downscaled weather data from a suite of climate models for agricultural modelling applications. Agricultural Systems, 114. pp. 1-5.

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We describe a generalised downscaling and data generation method that takes the outputs of a General Circulation Model and allows the stochastic generation of daily weather data that are to some extent characteristic of future climatologies. Such data can then be used to drive any agricultural model that requires daily (or otherwise aggregated) weather data. The method uses an amalgamation of unintelligent empirical downscaling, climate typing and weather generation. We outline a web-based software tool ( to do this for a subset of the climate models and scenario runs carried out for the 2007 Fourth Assessment Report of the Intergovernmental Panel on Climate Change. We briefly assess the tool and comment on its use and limitations.

Item Type: Article
Additional Information: Support for this work was provided by the numerous donors contributing to the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and by the Federal Ministry for Economic Cooperation and Development (BMZ), Germany. We gratefully acknowledge the provision of data from the archives of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP CMIP3 multi-model dataset, which is supported by the Office of Science, US Department of Energy; and from the CERA scenario database at the DKRZ, http://cera-www.dkrz. de/.
Uncontrolled Keywords: Markov models, Climate change, Stochastic generation, Downscaling DSSAT
Author Affiliation: Waen Associates, Y Waen, Islawrdref, Dolgellau, Gwynedd LL40 1TS, United Kingdom
Subjects: Atmosperic Science
Divisions: General
Depositing User: Mr Siva Shankar
Date Deposited: 18 Dec 2012 06:03
Last Modified: 18 Dec 2012 06:03
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