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

Liu De Li (), Garry J. O’Leary, Brendan Christy, Ian Macadam, Bin Wang, Muhuddin R. Anwar and Anna Weeks
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Liu De Li: 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
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

Climatic Change, 2017, vol. 144, issue 4, No 12, 687-701

Abstract: 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.

Date: 2017
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DOI: 10.1007/s10584-017-2054-5

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