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Multi-level emulation of complex climate model responses to boundary forcing data

Tran, Giang T.; Oliver, Kevin I. C.; Holden, Philip B.; Edwards, Neil R.; Sóbester, András and Challenor, Peter (2019). Multi-level emulation of complex climate model responses to boundary forcing data. Climate Dynamics, 52(3-4) pp. 1505–1531.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1007/s00382-018-4205-4
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Abstract

Climate model components involve both high-dimensional input and output fields. It is desirable to e ciently generate spatio-temporal out-puts of these models for applications in integrated assessment modelling or to assess the statistical relationship between such sets of inputs and outputs, for example, uncertainty analysis. However, the need for e ciency often compromises the fidelity of output through the use of low complexity models. Here, we develop a technique which combines statistical emulation with a dimensionality reduction technique to emulate a wide range of outputs from an atmospheric general circulation model, PLASIM, as functions of the boundary forcing prescribed by the ocean component of a lower complexity climate model, GENIE-1. Although accurate and detailed spatial information on atmospheric variables such as precipitation and wind speed is well beyond the capability of GENIE-1’s energy-moisture balance model of the atmosphere, this study demonstrates that the output of this model is useful in predicting PLASIM’s spatio-temporal fields through multi-level emulation. Meaningful information from the fast model, GENIE-1 was extracted by utilising the correlation between variables of the same type in the two models and between variables of di↵erent types in PLASIM. We present here the construction and validation of several PLASIM variable emulators and discuss their potential use in developing a hybrid model with statistical components.

Item Type: Journal Item
Copyright Holders: 2018 Springer-Verlag GmbH Germany
ISSN: 1432-0894
Keywords: Probabilistic prediction; Multi-level emulators; Model hierarchy; Spatio-temporal data; Intermediate complexity model
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Environment, Earth and Ecosystem Sciences
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 54569
Depositing User: Philip Holden
Date Deposited: 19 Apr 2018 14:05
Last Modified: 17 Aug 2019 14:25
URI: http://oro.open.ac.uk/id/eprint/54569
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