Multi-wheat-model ensemble responses to interannual climate variability. (July 2016)

• Record Type: Journal Article
• Authors: Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos; Basso, Bruno; Bertuzzi, Patrick; Biernath, Christian; Brisson, Nadine; Challinor, Andrew J.; Doltra, Jordi; Gayler, Sebastian; Goldberg, Richard; Grant, Robert F.; Heng, Lee; Hooker, Josh; Hunt, Leslie A.; Ingwersen, Joachim; Izaurralde, Roberto C.; Kersebaum, Kurt Christian; Kumar, Soora Naresh; Müller, Christoph; Nendel, Claas; O'Leary, Garry; Olesen, Jørgen E.; Osborne, Tom M.; Palosuo, Taru; Priesack, Eckart; Ripoche, Dominique; Rötter, Reimund P.; Semenov, Mikhail A.; Shcherbak, Iurii; Steduto, Pasquale; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Travasso, Maria; Waha, Katharina; Wallach, Daniel; White, Jeffrey W.; Wolf, Joost;
• Is Part Of: Environmental modelling & software. Volume 81(2016:Jul.)
• Page Start: 86
• Page End: 101
• Publication Date: 2016-07
• Subjects: Crop modeling -- Uncertainty -- Multi-model ensemble -- Wheat -- AgMIP -- Climate impacts -- Temperature -- Precipitation -- Interannual variability; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.03.008
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: We 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. Highlights: Compares interannual climate response of 27 wheat models at four locations. Calculates the diminishing return of constructing multi-model ensembles for assessment. Identifies similarities and major differences of model responses. Differentiates between interannual temperature sensitivity and climate change response.