A Statistical Analysis of Three Ensembles of Crop Model Responses to Temperature and CO2 Concentration
Author | David Makowski | |
Author | Senthold Asseng | |
Author | Frank Ewert | |
Author | Simona Bassu | |
Author | Jean-Louis Durand | |
Author | Tao Li | |
Author | Pierre Martre | |
Author | Myriam Adam | |
Author | P.K. Aggarwal | |
Author | Candy Angulo | |
Author | Christian Baron | |
Author | Bruno Basso | |
Author | Patrick Bertuzzi | |
Author | Christian Biernath | |
Author | H. Boogaard | |
Author | Kenneth J. Boote | |
Author | Bas Bouman | |
Author | Simone Bregaglio | |
Author | Nadine Brisson | |
Author | Samuel Buis | |
Author | Davide Cammarano | |
Author | Andrew J Challinor | |
Author | Roberto Confalonieri | |
Author | Conijn, J.G | |
Author | Marc Corbeels | |
Author | Delphine Deryng | |
Author | Giacomo De Sanctis | |
Author | Jordi Doltra | |
Author | Tamon Fumoto | |
Author | Donald Gaydon | |
Author | Sebastian Gayler | |
Author | R. Goldberg | |
Author | R.F. Grant | |
Author | Patricio Grassini | |
Author | Jerry Hatfield | |
Author | Toshihiro Hasegawa | |
Author | Lee Heng | |
Author | Steven Hoek | |
Author | J. Hooker | |
Author | Leslie Hunt | |
Author | Joachim Ingwersen | |
Author | R.C. Izaurralde | |
Author | Jongschaap, R.E.E. | |
Author | James W. Jones | |
Author | Armen R. Kemanian | |
Author | Kurt Christian Kersebaum | |
Author | Soo-Hyung Kim | |
Author | Jon I. Lizaso | |
Author | Manuel Marcaida | |
Author | Christoph Muller | |
Author | H. Nakagawa | |
Author | Soora Naresh Kumar | |
Author | Claas Nendel | |
Author | Gerard O’Leary | |
Author | Jørgen Eivind Olesen | |
Author | Philippe Oriol | |
Author | Tom Osborne | |
Author | Taru Palosuo | |
Author | M. Virginia Pravia | |
Author | Eckart Priesack | |
Author | Dominique Ripoche | |
Author | C. Rosenzweig | |
Author | Alex C. Ruane | |
Author | Françoise Ruget | |
Author | F. Sau | |
Author | Mikhail A Semenov | |
Author | Iurii Shcherbak | |
Author | Balwinder-Singh | |
Author | Upendra Singh | |
Author | Soo-Hyung Kim | |
Author | Pasquale Steduto | |
Author | Claudio O. Stöckle | |
Author | Pierre Stratonovitch | |
Author | T. Streck | |
Author | I. Supit | |
Author | Liang Tang | |
Author | Fulu Tao | |
Author | Edmar Teixeira | |
Author | Peter J Thorburn | |
Author | Dennis Timlin | |
Author | M. Travasso | |
Author | Reimund P. Rötter | |
Author | Katharina Waha | |
Author | Daniel Wallach | |
Author | Jeffrey W. White | |
Author | Paul W. Wilkens | |
Author | J.R. Williams | |
Author | Jonas Wolf | |
Author | Xinyou Yin | |
Author | Hiroe Yoshida | |
Author | Zhao Zhang | |
Author | Yan Zhu | |
Date of acession | 2024-03-15T11:06:53Z | |
Date of availability | 2024-03-15T11:06:53Z | |
Date of issue | 2015-12-15 | |
Abstract | 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]. | |
URL | https://hub.ifdc.org/handle/20.500.14297/2923 | |
Language | en | |
Subject | Climate change | |
Subject | Crop modelling | |
Subject | Yields | |
Title | A Statistical Analysis of Three Ensembles of Crop Model Responses to Temperature and CO2 Concentration | |
Type | Article |