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Journal Article

AgMIP-Wheat multi-model simulations on climate change impact and adaptation for global wheat

Authors

Liu,  Bing
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Martre,  Pierre
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Ewert,  Frank
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Webber,  Heidi
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Waha,  Katharina
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Thorburn,  Peter J.
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Ruane,  Alex C.
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Aggarwal,  Pramod K.
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Ahmed,  Mukhtar
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Balkovič,  Juraj
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Basso,  Bruno
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Biernath,  Christian
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Bindi,  Marco
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Cammarano,  Davide
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Cao,  Weixing
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Challinor,  Andy J.
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De Sanctis,  Giacomo
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Dumont,  Benjamin
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Espadafor,  Mónica
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Eyshi Rezaei,  Ehsan
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Fereres,  Elias
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Ferrise,  Roberto
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Garcia-Vila,  Margarita
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Gayler,  Sebastian
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Gao,  Yujing
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Horan,  Heidi
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Hoogenboom,  Gerrit
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Izaurralde,  Roberto C.
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Jabloun,  Mohamed
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Jones,  Curtis D.
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Kassie,  Belay T.
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Kersebaum,  Kurt C.
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Klein,  Christian
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Koehler,  Ann-Kristin
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Maiorano,  Andrea
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/persons/resource/sara.minoli

Minoli,  Sara
Potsdam Institute for Climate Impact Research;

Montesino San Martin,  Manuel
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/persons/resource/Christoph.Mueller

Müller,  Christoph
Potsdam Institute for Climate Impact Research;

Naresh Kumar,  Soora
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Nendel,  Claas
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O’Leary,  Garry J.
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Eivind Olesen,  Jørgen
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Palosuo,  Taru
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Porter,  John R.
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Priesack,  Eckart
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Ripoche,  Dominique
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Rötter,  Reimund P.
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Semenov,  Mikhail A.
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Stöckle,  Claudio
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Stratonovitch,  Pierre
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Streck,  Thilo
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Supit,  Iwan
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Tao,  Fulu
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Van der Velde,  Marijn
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Wang,  Enli
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Wolf,  Joost
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Xiao,  Liujun
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Zhang,  Zhao
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Zhao,  Zhigan
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Zhu,  Yan
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Asseng,  Senthold
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External Ressource

https://doi.org/10.5281/zenodo.4027033
(Supplementary material)

Fulltext (public)

Manuscript.pdf
(Publisher version), 471KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Liu, B., Martre, P., Ewert, F., Webber, H., Waha, K., Thorburn, P. J., Ruane, A. C., Aggarwal, P. K., Ahmed, M., Balkovič, J., Basso, B., Biernath, C., Bindi, M., Cammarano, D., Cao, W., Challinor, A. J., De Sanctis, G., Dumont, B., Espadafor, M., Eyshi Rezaei, E., Fereres, E., Ferrise, R., Garcia-Vila, M., Gayler, S., Gao, Y., Horan, H., Hoogenboom, G., Izaurralde, R. C., Jabloun, M., Jones, C. D., Kassie, B. T., Kersebaum, K. C., Klein, C., Koehler, A.-K., Maiorano, A., Minoli, S., Montesino San Martin, M., Müller, C., Naresh Kumar, S., Nendel, C., O’Leary, G. J., Eivind Olesen, J., Palosuo, T., Porter, J. R., Priesack, E., Ripoche, D., Rötter, R. P., Semenov, M. A., Stöckle, C., Stratonovitch, P., Streck, T., Supit, I., Tao, F., Van der Velde, M., Wang, E., Wolf, J., Xiao, L., Zhang, Z., Zhao, Z., Zhu, Y., Asseng, S. (2023): AgMIP-Wheat multi-model simulations on climate change impact and adaptation for global wheat. - Open Data Journal for Agricultural Research, 9, 10-25.
https://doi.org/10.18174/odjar.v9i0.18092


Cite as: https://publications.pik-potsdam.de/pubman/item/item_28556
Abstract
The climate change impact and adaptation simulations from the Agricultural Model Intercomparison and Improvement Project (AgMIP) for wheat provide a unique dataset of multi-model ensemble simulations for 60 representative global locations covering all global wheat mega environments. The multi-model ensemble reported here has been thoroughly benchmarked against a large number of experimental data, including different locations, growing season temperatures, atmospheric CO2 concentration, heat stress scenarios, and their interactions. In this paper, we describe the main characteristics of this global simulation dataset. Detailed cultivar, crop management, and soil datasets were compiled for all locations to drive 32 wheat growth models. The dataset consists of 30-year simulated data including 25 output variables for nine climate scenarios, including Baseline (1980-2010) with 360 or 550 ppm CO2, Baseline +2oC or +4oC with 360 or 550 ppm CO2, a mid-century climate change scenario (RCP8.5, 571 ppm CO2), and 1.5°C (423 ppm CO2) and 2.0oC (487 ppm CO2) warming above the pre-industrial period (HAPPI). This global simulation dataset can be used as a benchmark from a well-tested multi-model ensemble in future analyses of global wheat. Also, resource use efficiency (e.g., for radiation, water, and nitrogen use) and uncertainty analyses under different climate scenarios can be explored at different scales. The DOI for the dataset is 10.5281/zenodo.4027033 (AgMIP-Wheat, 2020), and all the data are available on the data repository of Zenodo (doi: 10.5281/zenodo.4027033). Two scientific publications have been published based on some of these data here.