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Effects of different climate downscaling methods on the assessment of climate change impacts on wheat cropping systems

Author

Listed:
  • De Li Liu

    (Wagga Wagga Agricultural Institute)

  • Garry J. O’Leary

    (Agriculture Victoria Research, Department of Economic Development, Jobs, Transport and Resources)

  • Brendan Christy

    (Agriculture Victoria Research, Department of Economic Development, Jobs, Transport and Resources)

  • Ian Macadam

    (University of New South Wales
    Now at Met Office)

  • Bin Wang

    (Wagga Wagga Agricultural Institute)

  • Muhuddin R. Anwar

    (Wagga Wagga Agricultural Institute)

  • Anna Weeks

    (Agriculture Victoria Research, Department of Economic Development, Jobs, Transport and Resources)

Abstract

The use of different downscaling methods (DSMs) to generate downscaled daily climate (DDC) data for assessing climate change impacts on wheat cropping systems was investigated. DDC data were generated from SRES A2 emission scenario simulations of seven global climate models (GCMs) using two different change factor methods, denoted as DTS and RSC, and two weather generator methods, LARS-WG (LWG) and NWAI-WG (NWG). The DDC data were used to drive the Agricultural Production Systems sIMulator (APSIM) wheat model. Significant differences in future changes in simulated crop growth and soil water balance were found between the four DSMs. For raw GCM output, multi-GCM mean changes by the mid-twenty-first century in annual mean temperature (AMT) ranged from +1.2 to +2.0 °C and in annual rainfall (AR) ranged from −11 to −5% across the 6 study sites. The DTS, LWG and NWG SDMs modified the raw GCM changes in both AMT and AR. As a result, climate change impacts on crop growth and soil water balance are not well correlated between DSMs. Since different DSMs give different impact results, we conclude that in addition to using multiple GCMs, selecting appropriate DSMs can be an important consideration in climate change impact assessments.

Suggested Citation

  • De Li Liu & Garry J. O’Leary & Brendan Christy & Ian Macadam & Bin Wang & Muhuddin R. Anwar & Anna Weeks, 2017. "Effects of different climate downscaling methods on the assessment of climate change impacts on wheat cropping systems," Climatic Change, Springer, vol. 144(4), pages 687-701, October.
    • Handle: RePEc:spr:climat:v:144:y:2017:i:4:d:10.1007_s10584-017-2054-5
    DOI: 10.1007/s10584-017-2054-5
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    References listed on IDEAS

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    1. A. Potgieter & H. Meinke & A. Doherty & V. Sadras & G. Hammer & S. Crimp & D. Rodriguez, 2013. "Spatial impact of projected changes in rainfall and temperature on wheat yields in Australia," Climatic Change, Springer, vol. 117(1), pages 163-179, March.
    2. Ludwig, Fulco & Asseng, Senthold, 2010. "Potential benefits of early vigor and changes in phenology in wheat to adapt to warmer and drier climates," Agricultural Systems, Elsevier, vol. 103(3), pages 127-136, March.
    3. De Liu & Heping Zuo, 2012. "Statistical downscaling of daily climate variables for climate change impact assessment over New South Wales, Australia," Climatic Change, Springer, vol. 115(3), pages 629-666, December.
    4. A. J. Challinor & J. Watson & D. B. Lobell & S. M. Howden & D. R. Smith & N. Chhetri, 2014. "A meta-analysis of crop yield under climate change and adaptation," Nature Climate Change, Nature, vol. 4(4), pages 287-291, April.
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