Multimodel ensembles improve predictions of crop–environment–management interactions

A recent innovation in assessment of climate change impact on agricultural production has been to use crop multimodel ensembles (MMEs). These studies usually find large variability between individual models but that the ensemble mean (e‐mean) and median (e‐median) often seem to predict quite well. H...

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Main Authors:	Wallach, Daniel, Martre, Pierre, Liu, Bing, Asseng, Senthold, Ewert, Frank, Thorburn, Peter J., Ittersum, Martin K. van, Aggarwal, Pramod K., Ahmed, Mukhtar, Basso, Bruno, Biernath, Christian, Cammarano, Davide, Challinor, Andrew J., Sanctis, Giacomo de, Dumont, Benjamin, Eyshi Rezaei, Ehsan, Fereres, Elias, Fitzgerald, Glenn J., Gao, Y, García Vila, Margarita, Gayler, Sebastian, Girousse, Christine, Hoogenboom, Gerrit, Horan, Heidi, Izaurralde, Roberto César, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt-Christian, Klein, Christian, Köhler, Ann-Kristin, Maiorano, Andrea, Minoli, Sara, Müller, Christoph, Naresh Kumar, Soora, Nendel, Claas, O’Leary, Garry J., Palosuo, Taru, Priesack, Eckart, Ripoche, Dominique, Rötter, Reimund P., Semenov, Mikhail A., Stöckle, Claudio O., Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Wolf, Joost, Zhang, Zhao
Format:	Journal Article
Language:	Inglés
Published:	Wiley 2018
Subjects:	climate change cambio climático crop models ensamble mean simulation models environment ecology
Online Access:	https://hdl.handle.net/10568/97157