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Emulation and interpretation of high-dimensional climate model outputs

Holden, Philip B.; Edwards, Neil R.; Garthwaite, Paul H. and Wilkinson, Richard D. (2015). Emulation and interpretation of high-dimensional climate model outputs. Journal of Applied Statistics, 42(9) pp. 2038–2055.

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Running complex computer models can be expensive in computer time, while learning about the relationships between input and output variables can be difficult. An emulator is a fast approximation to a computationally expensive model that can be used as a surrogate for the model, to quantify uncertainty or to improve process understanding. Here, we examine emulators based on singular value decompositions and use them to emulate global climate and vegetation fields, examining how these fields are affected by changes in the Earth’s orbit. The vegetation field may be emulated directly from the orbital variables, but an appealing alternative is to relate it to emulations of the climate fields, which involves high-dimensional input and output. The singular value decompositions radically reduce the dimensionality of the input and output spaces and are shown to clarify the relationships between them. The method could potentially be useful for any complex process with correlated, high- dimensional inputs and/or outputs.

Item Type: Journal Item
Copyright Holders: 2015 Taylor & Francis
ISSN: 1360-0532
Project Funding Details:
Funded Project NameProject IDFunding Body
Keywords: climate modelling; coupled models; emulation; principal components; singular value decomposition
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Environment, Earth and Ecosystem Sciences
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Research Group: International Development & Inclusive Innovation
Item ID: 42043
Depositing User: Philip Holden
Date Deposited: 13 Feb 2015 09:56
Last Modified: 24 May 2020 18:03
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