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Müller, C.; Elliott, J. |
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Title |
The Global Gridded Crop Model Intercomparison – Approaches, insights and caveats of modeling climate change impacts on agriculture at the global scale |
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2013 |
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CropM |
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FAO expert consultation on climate change and trade, Rome, Italy, 2013-11-05 to 2013-11-06 |
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MA @ admin @ |
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2670 |
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Author |
Müller, C., Elliott J |
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Title |
The Global Gridded Crop Model Intercomparison Project |
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2013 |
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4th Annual AgMIP Workshop, New York, USA, 2013-10-28 to 2013-10-30 |
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MA @ admin @ |
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2667 |
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Author |
Müller, C. |
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Title |
Climate change impacts, uncertainties and implications |
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2013 |
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First Workshop Expert Network Management of Climate change induced Risks, Hamburg, Germany, 2013-03-20 to 2013-03-21 |
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no |
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MA @ admin @ |
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2665 |
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Author |
Müller, C. |
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Title |
Multi-sector interaction in climate change impact analysis |
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2013 |
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Impacts World 2013, International Conference on Climate Change Effects, Potsdam, Germany, 2013-05-27 to 2013-05-30 |
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no |
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MA @ admin @ |
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2666 |
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Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Ruane, A.C.; Boote, K.J.; Thorburn, P.J.; Rötter, R.P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P.K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A.J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J.W.; Williams, J.R.; Wolf, J. |
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Title |
Uncertainty in simulating wheat yields under climate change |
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Journal Article |
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2013 |
Publication |
Nature Climate Change |
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Nat. Clim. Change |
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3 |
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9 |
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827-832 |
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Keywords |
crop production; models; food; co2; temperature; projections; adaptation; scenarios; ensemble; impacts |
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Abstract |
Projections of climate change impacts on crop yields are inherently uncertain(1). Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate(2). However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models(1,3) are difficult(4). Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking. |
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English |
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1758-678x |
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Notes |
CropM, ftnotmacsur, IPCC-AR5 |
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no |
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MA @ admin @ |
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4599 |
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