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Multi-wheat-model ensemble responses to interannual climate variability
Ruane A. C.; Hudson, N. I.; Asseng, S.; Camarrano, D.; Ewert, F.; Martre, P.; Boote, K. J.; Thorburn, P. J.; Aggarwal, P. K.; Angulo, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Brisson, N.; Challinor, A. J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R. F.; Heng, L.; Hooker, J.; Hunt, L. A.; Ingwersen, J.; Izaurralde, R. C.; Kersebaum, K. C.; Kumar, S. N.; Muller, C.; Nendel, C.; O'leary, G.; Olesen, J. E.; Osborne, T. M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Rotter, R. P.; Semenov, M. A.; Shcherbak, I.; Steduto, P.; Stockle, C. O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F. L.; Travasso, M.; Waha, K.; Wallach, D.; White, J. W.; Wolf, J.
Source PublicationEnvironmental Modelling & Software
2016
Volume81
Pages86-101
KeywordCrop modeling Uncertainty Multi-model ensemble Wheat AgMIP Climate impacts Temperature Precipitation lnterannual variability simulation-model crop model nitrogen dynamics winter-wheat large-area systems simulation farming systems yield response growth water
AbstractWe compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981-2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R-2 <= 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts. Published by Elsevier Ltd.
Indexed BySCI
Language英语
ISSN1364-8152
DOI10.1016/j.envsoft.2016.03.008
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Document TypeSCI/SSCI论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/43183
Collection历年回溯文献
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GB/T 7714
Ruane A. C.,Hudson, N. I.,Asseng, S.,et al. Multi-wheat-model ensemble responses to interannual climate variability. 2016.
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