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ARS Home » Midwest Area » Ames, Iowa » National Laboratory for Agriculture and The Environment » Soil, Water & Air Resources Research » Research » Publications at this Location » Publication #287037

Title: Uncertainty in simulating wheat yields under climate change

Author
item ASSENG, SENTHOLD - University Of Florida
item EWERT, FRANK - Institute For Agriculture & Crop Science - Germany
item ROSENZWEIG, CYNTHIA - National Aeronautics And Space Administration (NASA)
item JONES, JAMES - University Of Florida
item Hatfield, Jerry
item RUANE, ALEX - National Aeronautics And Space Administration (NASA)
item BOOTE, KENNETH - University Of Florida
item THORBURN, PETER - Commonwealth Scientific And Industrial Research Organisation (CSIRO)
item ROTTER, ROBERT - Mtt Agrifood Research Finland
item CAMMARANO, DOMINIC - University Of Florida
item BRISSON, NADINE - Inland Northwest Research Alliance, Inra
item BASSO, BRUNO - Michigan State University
item MARTRE, P - Inland Northwest Research Alliance, Inra
item RIPOCHE, D - Inland Northwest Research Alliance, Inra
item BERTUZZI, P - Inland Northwest Research Alliance, Inra
item STEDUTO, P - Food & Agriculture Organization (FAO)
item HENG, L - International Atomic Energy Agency (IAEA)
item SEMENOV, M - Rothamsted Research
item STRATONOVITCH, P - Rothamsted Research
item STOCKLE, C - Washington State University
item O'LEARY, G - Nsw Department Of Primary Industries
item AGGARWAL, PARMOD - International Water Management Institute
item KUMAR, S - Indian Agricultural Research Institute
item IZAURRALDE, R - Global Change Research Institute
item White, Jeffrey
item HUNT, L - University Of Guelph
item GRANT, R - University Of Alberta
item KERSEBAUM, K - Leibniz Institute
item PALOSUO, T - Mtt Agrifood Research Finland
item HOOKER, J - University Of Reading
item OSBORNE, T - University Of Reading
item WOLF, J - Wageningen University
item SUPIT, I - Wageningen University
item OLESEN, J - Aarhus University
item DOLTRA, J - Cantabria University
item NENDEL, C - Leibniz Institute
item GAYLER, S - University Of Tubingen
item INGWERSEN, J - University Of Hohenheim
item PRIESACK, E - German Research Center For Environmental Health
item STRECK, T - Hohenheim University
item TAO, F - Chinese Academy Of Sciences
item MULLER, C - Potsdam Institute
item WAHA, K - Potsdam Institute
item GOLDBERG, R - National Aeronautics And Space Administration (NASA)
item ANGULO, C
item SHCHERBAK, I - Michigan State University
item BIERNATH, C - Helmholtz Centre
item WALLACH, D - Inland Northwest Research Alliance, Inra
item TRAVASSO, M - Inland Northwest Research Alliance, Inra
item WILLIAMS, J - Texas A&M University
item CHALLINOR, A - University Of Leeds

Submitted to: Nature Climate Change
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/22/2013
Publication Date: 9/1/2013
Citation: Asseng, S., Ewert, F., Rosenzweig, C., Jones, J., Hatfield, J.L., Ruane, A., Boote, K., Thorburn, P., Rotter, R., Cammarano, D., Brisson, N., Basso, B., Martre, P., Ripoche, D., Bertuzzi, P., Steduto, P., Heng, L., Semenov, M.A., Stratonovitch, P., Stockle, C., O'Leary, G., Aggarwal, P.K., Kumar, S.N., Izaurralde, R.C., White, J.W., Hunt, L.A., Grant, R., Kersebaum, K.C., Palosuo, T., Hooker, J., Osborne, T., Wolf, J., Supit, I., Olesen, J.E., Doltra, J., Nendel, C., Gayler, S., Ingwersen, J., Priesack, E., Streck, T., Tao, F., Muller, C., Waha, K., Goldberg, R., Angulo, C., Shcherbak, I., Biernath, C., Wallach, D., Travasso, M., Williams, J.R., Challinor, A.J. 2013. Uncertainty in simulating wheat yields under climate change. Nature Climate Change. 3:827-832. DOI: 10.1038/NCLIMATE1916.

Interpretive Summary: Ensuring a stable food supply into the future with the uncertainty of climate change and the increasing population requires the development of tools to be able to assess the impact of changes on grain production. As part of an international effort to intercompare and improve crop models a comparison was made among 27 different wheat yield simulation models using four sites around the world as test cases. This type of effort had not been conducted before to this extent and is being used to identify where model improvements can be made and how reliable combination of models are in estimating the impacts of changes in climate. This evaluation revealed that there is a wide range in the estimates provided by the models and the sensitivity to different climate factors. The best estimate for future changes can be achieved through the use of five to six different crop models to create an ensemble of grain yields under future climates. These data would be of value to scientists and policymakers to evaluate how crop models could be more effectively used to estimate future grain supplies with increased reliability and confidence in the projections.

Technical Abstract: Anticipating the impacts of climate change on crop yields is critical for assessing future food security. Process-based crop simulation models are the most commonly used tools in such assessments. Analysis of uncertainties in future greenhouse gas emissions and their impacts on future climate change has been increasingly described in the literature while assessments of the uncertainty in crop responses to climate change are very rare. Systematic and objective comparisons across impact studies is difficult, and thus has not been fully realized. Here we present the largest coordinated and standardized crop model intercomparison for climate change impacts on wheat production to date. We found that several individual crop models are able to reproduce measured grain yields under current diverse environments, particularly if sufficient details are provided to execute them. However, simulated climate change impacts can vary across models due to differences in model structures and algorithms. The crop-model component of uncertainty in climate change impact assessments was considerably larger than the climate-model component from Global Climate Models (GCMs). Model responses to high temperatures and temperature-by-CO2 interactions are identified as major sources of simulated impact uncertainties. Significant reductions in impact uncertainties through model improvements in these areas and improved quantification of uncertainty through multi-model ensembles are urgently needed for a more reliable translation of climate change scenarios into agricultural impacts in order to develop adaptation strategies and aid policymaking.