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Emulating global climate change impacts on crop yields

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Emulating global climate change impacts on crop yields. / Oyebamiji, Oluwole Kehinde; Edwards, Neil; Holden, Philip et al.
In: Statistical Modelling, Vol. 15, No. 6, 18.01.2015, p. 499-525.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Oyebamiji, OK, Edwards, N, Holden, P, Garthwaite, P, Schaphoff, S & Gerten, D 2015, 'Emulating global climate change impacts on crop yields', Statistical Modelling, vol. 15, no. 6, pp. 499-525. https://doi.org/10.1177/1471082X14568248

APA

Oyebamiji, O. K., Edwards, N., Holden, P., Garthwaite, P., Schaphoff, S., & Gerten, D. (2015). Emulating global climate change impacts on crop yields. Statistical Modelling, 15(6), 499-525. https://doi.org/10.1177/1471082X14568248

Vancouver

Oyebamiji OK, Edwards N, Holden P, Garthwaite P, Schaphoff S, Gerten D. Emulating global climate change impacts on crop yields. Statistical Modelling. 2015 Jan 18;15(6):499-525. doi: 10.1177/1471082X14568248

Author

Oyebamiji, Oluwole Kehinde ; Edwards, Neil ; Holden, Philip et al. / Emulating global climate change impacts on crop yields. In: Statistical Modelling. 2015 ; Vol. 15, No. 6. pp. 499-525.

Bibtex

@article{fd24ff79d67f4e2e9327165f07c59369,
title = "Emulating global climate change impacts on crop yields",
abstract = "The potential effects of climate change on the environment and society are many. In order to effectively quantify the uncertainty associated with these effects, highly complex simulation models are run with detailed representations of ecosystem processes. These models are computationally expensive and can involve a computer run of several days. Computationally cheaper models can be obtained from large ensembles of simulations using statistical emulation. The purpose of this article is to construct a cheaper computational model (emulator) from simulations of the Lund-Potsdam-Jena managed Land (LPJmL), which is a dynamic global vegetation and crop model. This article focuses on statistical emulation of potential crop yields from LPJmL and an emulator is constructed using a combination of ordinary least squares, principal component analysis and weighted least squares methods. For five climate models, under cross-validation, the percentage of variance explained ranges from 60 to 88% for the rainfed crops and 62 to 93% for the irrigated crops. The emulator can be used to predict potential crop yield change under any future climate scenarios and management options.",
author = "Oyebamiji, {Oluwole Kehinde} and Neil Edwards and Philip Holden and Paul Garthwaite and Sibyll Schaphoff and Dieter Gerten",
year = "2015",
month = jan,
day = "18",
doi = "10.1177/1471082X14568248",
language = "English",
volume = "15",
pages = "499--525",
journal = "Statistical Modelling",
issn = "1471-082X",
publisher = "SAGE Publications Ltd",
number = "6",

}

RIS

TY - JOUR

T1 - Emulating global climate change impacts on crop yields

AU - Oyebamiji, Oluwole Kehinde

AU - Edwards, Neil

AU - Holden, Philip

AU - Garthwaite, Paul

AU - Schaphoff, Sibyll

AU - Gerten, Dieter

PY - 2015/1/18

Y1 - 2015/1/18

N2 - The potential effects of climate change on the environment and society are many. In order to effectively quantify the uncertainty associated with these effects, highly complex simulation models are run with detailed representations of ecosystem processes. These models are computationally expensive and can involve a computer run of several days. Computationally cheaper models can be obtained from large ensembles of simulations using statistical emulation. The purpose of this article is to construct a cheaper computational model (emulator) from simulations of the Lund-Potsdam-Jena managed Land (LPJmL), which is a dynamic global vegetation and crop model. This article focuses on statistical emulation of potential crop yields from LPJmL and an emulator is constructed using a combination of ordinary least squares, principal component analysis and weighted least squares methods. For five climate models, under cross-validation, the percentage of variance explained ranges from 60 to 88% for the rainfed crops and 62 to 93% for the irrigated crops. The emulator can be used to predict potential crop yield change under any future climate scenarios and management options.

AB - The potential effects of climate change on the environment and society are many. In order to effectively quantify the uncertainty associated with these effects, highly complex simulation models are run with detailed representations of ecosystem processes. These models are computationally expensive and can involve a computer run of several days. Computationally cheaper models can be obtained from large ensembles of simulations using statistical emulation. The purpose of this article is to construct a cheaper computational model (emulator) from simulations of the Lund-Potsdam-Jena managed Land (LPJmL), which is a dynamic global vegetation and crop model. This article focuses on statistical emulation of potential crop yields from LPJmL and an emulator is constructed using a combination of ordinary least squares, principal component analysis and weighted least squares methods. For five climate models, under cross-validation, the percentage of variance explained ranges from 60 to 88% for the rainfed crops and 62 to 93% for the irrigated crops. The emulator can be used to predict potential crop yield change under any future climate scenarios and management options.

U2 - 10.1177/1471082X14568248

DO - 10.1177/1471082X14568248

M3 - Journal article

VL - 15

SP - 499

EP - 525

JO - Statistical Modelling

JF - Statistical Modelling

SN - 1471-082X

IS - 6

ER -