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

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  • Jones, Peter G.
  • Thornton, Philip K.

Abstract

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 (http://gismap.ciat.cgiar.org/MarkSimGCM) 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.

Suggested Citation

  • Jones, Peter G. & Thornton, Philip K., 2013. "Generating downscaled weather data from a suite of climate models for agricultural modelling applications," Agricultural Systems, Elsevier, vol. 114(C), pages 1-5.
  • Handle: RePEc:eee:agisys:v:114:y:2013:i:c:p:1-5
    DOI: 10.1016/j.agsy.2012.08.002
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    Citations

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    Cited by:

    1. Euler, Michael & Hoffmann, Munir P. & Fathoni, Zakky & Schwarze, Stefan, 2016. "Exploring yield gaps in smallholder oil palm production systems in eastern Sumatra, Indonesia," Agricultural Systems, Elsevier, vol. 146(C), pages 111-119.
    2. Nouri, Milad & Homaee, Mehdi & Bannayan, Mohammad & Hoogenboom, Gerrit, 2016. "Towards modeling soil texture-specific sensitivity of wheat yield and water balance to climatic changes," Agricultural Water Management, Elsevier, vol. 177(C), pages 248-263.
    3. repec:spr:waterr:v:31:y:2017:i:11:d:10.1007_s11269-017-1691-9 is not listed on IDEAS
    4. Shirsath, Paresh B. & Aggarwal, P.K. & Thornton, P.K. & Dunnett, A., 2017. "Prioritizing climate-smart agricultural land use options at a regional scale," Agricultural Systems, Elsevier, vol. 151(C), pages 174-183.
    5. Habtemariam, Lemlem Teklegiorgis & Abate Kassa, Getachew & Gandorfer, Markus, 2017. "Impact of climate change on farms in smallholder farming systems: Yield impacts, economic implications and distributional effects," Agricultural Systems, Elsevier, vol. 152(C), pages 58-66.
    6. Welikhe, Pauline & Essamuah-Quansah, Joseph & Boote, Kenneth & Asseng, Senthold & El Afandi, Gamal, 2016. "Impact of Climate Change on Corn Yields in Alabama," Professional Agricultural Workers Journal (PAWJ), Professional Agricultural Workers Conference, vol. 4(1).
    7. repec:spr:climat:v:147:y:2018:i:3:d:10.1007_s10584-018-2151-0 is not listed on IDEAS
    8. Wallace, Carlington W. & Flanagan, Dennis C. & Engel, Bernard A., 2017. "Quantifying the effects of conservation practice implementation on predicted runoff and chemical losses under climate change," Agricultural Water Management, Elsevier, vol. 186(C), pages 51-65.
    9. Kima, Aimé Sévérin & Traore, Seydou & Wang, Yu-Min & Chung, Wen-Guey, 2014. "Multi-genes programing and local scale regression for analyzing rice yield response to climate factors using observed and downscaled data in Sahel," Agricultural Water Management, Elsevier, vol. 146(C), pages 149-162.
    10. Nouri, Milad & Homaee, Mehdi & Bannayan, Mohammad & Hoogenboom, Gerrit, 2017. "Towards shifting planting date as an adaptation practice for rainfed wheat response to climate change," Agricultural Water Management, Elsevier, vol. 186(C), pages 108-119.
    11. Jones, Peter G. & Thornton, Philip K., 2015. "Representative soil profiles for the Harmonized World Soil Database at different spatial resolutions for agricultural modelling applications," Agricultural Systems, Elsevier, vol. 139(C), pages 93-99.

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