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United States Department of Agriculture

Agricultural Research Service

Research Project: MANAGEMENT OF AGRICULTURAL AND NATURAL RESOURCE SYSTEMS TO REDUCE ATMOSPHERIC EMISSIONS AND INCREASE RESILIENCE TO CLIMATE CHANGE

Location: Soil, Water & Air Resources Research

Title: Uncertainty in simulating wheat yields under climate change)

Author
item Asseng, Senthold
item Ewert, Frank
item Rosenzweig, Cynthia
item Jones, James
item Hatfield, Jerry
item Ruane, Alex
item Boote, Kenneth
item Thorburn, Peter
item Rotter, Robert
item Cammarano, Dominic
item Brisson, Nadine
item Basso, Bruno
item Martre, P
item Ripoche, D
item Bertuzzi, P
item Steduto, P
item Heng, L
item Semenov, M
item Stratonovitch, P
item Stockle, C
item O'leary, G
item Aggarwal, Parmod
item Kumar, S
item Izaurralde, R
item White, Jeffrey
item Hunt, L
item Grant, R
item Kersebaum, K
item Palosuo, T
item Hooker, J
item Osborne, T
item Wolf, J
item Supit, I
item Olesen, J
item Doltra, J
item Nendel, C
item Gayler, S
item Ingwersen, J
item Priesack, E
item Streck, T
item Tao, F
item Muller, C
item Waha, K
item Goldberg, R
item Angulo, C
item Shcherbak, I
item Biernath, C
item Wallach, D
item Travasso, M
item Williams, J
item Challinor, A

Submitted to: Nature Climate Change
Publication Type: Peer reviewed journal
Publication Acceptance Date: 4/22/2013
Publication Date: 9/1/2013
Publication URL: www.nature.com/natureclimatechange
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.

Last Modified: 8/24/2016
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