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A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration

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Title A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration
 
Creator Makowski D
Asseng, S.
Ewert, Frank
Bassu S
Durand, J.L.
Li T
Martre, Pierre
Adam M
Aggarwal, Pramod K.
Angulo, Carlos
Baron, C.
Basso, Bruno
Bertuzzi, Patrick
Biernath, Christian
Boogaard, H.
Boote, Kenneth J.
Bouman, B.
Bregaglio, S.
Brisson N
Buis S
Cammarano, Davide
Challinor, Andrew J.
Confalonieri, R.
Conijn JG
Corbeels, Marc
Deryng, Delphine
Sanctis, Giacomo de
Doltra, Jordi
Fumoto T
Gayler, Sebastian
Goldberg, Richard A.
Grassini, Patricio
Hatfield, Jerry L.
Hasegawa, Tomoko
Heng, Lee
Hoek SB
Hooker, Josh
Hunt LA
Ingwersen, Joachim
Izaurralde, Roberto César
Jongschaap, R.E.E.
Jones, James W.
Kemanian RA
Kersebaum, Kurt-Christian
Kim SH
Lizaso J
Marcaida, M.
Müller, Christoph
Nakagawa H
Naresh Kumar, Soora
Nendel, Claas
O'Leary, Garry J.
Olesen, J.E.
Oriol P
Osborne, Tom M.
Palosuo, Taru
Pravia MV
Priesack, Eckart
Ripoche, Dominique
Rosenzweig, Cynthia
Ruane, Alex C.
Ruget, F
Sau F
Semenov, Mikhail A.
Shcherbak, Iurii
Singh B
Singh U
Soo HK
Steduto, Pasquale
Stöckle, Claudio O.
Stratonovitch, Pierre
Streck, Thilo
Supit, Iwan
Tang L
Tao, Fulu
Teixeira E
Thorburn, Peter J.
Timlin D
Travasso, Maria
Roetter RP
Waha, Katharina
Wallach, Daniel
White, Jeffrey W.
Williams JR
Wolf, Joost
Yin, X.
Yoshida H
Zhang, Z.
Zhu Y
 
Subject CLIMATE CHANGE
AGRICULTURE
FOOD SECURITY
CROP MODEL
EMULATOR
META-MODEL
STATISTICAL MODEL
YIELD
 
Description Ensembles of process-based crop models are increasingly used to simulate crop growth for scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of simulated crop yield data. Such datasets potentially provide new information but it is difficult to summarize them in a useful way due to their structural complexities. An associated issue is that it is not straightforward to compare crops and to interpolate the results to alternative climate scenarios not initially included in the simulation protocols. Here we demonstrate that statistical models based on random-coefficient regressions are able to emulate ensembles of process-based crop models. An important advantage of the proposed statistical models is that they can interpolate between temperature levels and between CO2 concentration levels, and can thus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulated by 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to these datasets, and are then used to analyze the variability of the yield response to [CO2] and temperature. Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effect of a temperature increase of +2 °C in the considered sites. Compared to wheat, required levels of [CO2] increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulating climate change impacts increase more with temperature than with elevated [CO2].
 
Date 2016-08-25T11:51:09Z
2016-08-25T11:51:09Z
2015
 
Type Journal Article
 
Identifier Makowski D, Asseng S, Ewert F, Bassu S, Durand JL, Li T, Martre P, Adam M, Aggarwal PK, Angulo C, Baron C, Basso B, Bertuzzi P, Biernath C, Boogaard H, Boote KJ, Bouman B, Bregaglio S, Brisson N, Buis S, Cammarano D, Challinor AJ, Confalonieri R, Conijn JG, Corbeels M, Deryng D, De Sanctis G, Doltra J, Fumoto T, Gayler S, Goldberg R, Grassini P, Hatfield JL, Hasegawa T, Heng L, Hoek SB, Hooker J, Hunt LA, Ingwersen J, Izaurralde C, Jongschaap REE, Jones JW, Kemanian RA, Kersebaum KC, Kim SH, Lizaso J, Marcaida III M, Müller C, Nakagawa H, Naresh Kumar S, Nendel C, O'Leary GJ, Olesen JE, Oriol P, Osborne TM, Palosuo T, Pravia MV, Priesack E, Ripoche D, Rosenzweig C, Ruane AC, Ruget F, Sau F, Semenov MA, Shcherbak I, Singh B, Singh U, Soo HK, Steduto P, Stöckle CO, Stratonovitch P, Streck T, Supit I, Tang L, Tao F, Teixeira E, Thorburn P, Timlin D, Travasso M, Roetter RP, Waha K, Wallach D, White JW, Williams JR, Wolf J, Yin, X, Yoshida H, Zhang Z, Zhu Y. 2015. A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. Agricultural and Forest Meteorology 214-215:383-493.
https://hdl.handle.net/10568/76575
 
Language en
 
Source Agricultural and Forest Meteorology