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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Autores principales:	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
Formato:	Journal Article
Lenguaje:	Inglés
Publicado:	Wiley 2018
Materias:	climate change cambio climático crop models ensamble mean simulation models environment ecology
Acceso en línea:	https://hdl.handle.net/10568/97157