Emulation and interpretation of high-dimensional climate model outputs

被引:29
作者
Holden, Philip B. [1 ]
Edwards, Neil R. [1 ]
Garthwaite, Paul H. [2 ]
Wilkinson, Richard D. [3 ]
机构
[1] Open Univ, Environm Earth & Ecosyst, Milton Keynes MK7 6AA, Bucks, England
[2] Open Univ, Dept Math & Stat, Milton Keynes MK7 6AA, Bucks, England
[3] Univ Nottingham, Sch Math Sci, Nottingham NG7 2RD, England
关键词
climate modelling; coupled models; emulation; principal components; singular value decomposition; SENSITIVITY-ANALYSIS; SELECTION; IMPACTS;
D O I
10.1080/02664763.2015.1016412
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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 (SVDs) 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 SVDs 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.
引用
收藏
页码:2038 / 2055
页数:18
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