Prieß, Malte, Piwonski, Jaroslaw, Koziel, S. and Slawig, Thomas (2012) Parameter identification in climate models using surrogate-based optimization. Journal of Computational Methods in Science and Engineering, 12 (1-2). pp. 47-62. DOI 10.3233/JCM-2012-0403.

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Abstract

We present initial steps and first results of a surrogate-based optimization (SBO) approach for parameter optimization in climate models. In SBO, a computationally cheap, but yet reasonably accurate representation of the original high-fidelity (or fine) model, the so-called surrogate, replaces the fine model in the optimization process. We choose two representatives, namely two marine ecosystem models, to verify our approach. We present two ways to obtain a physics-based low-fidelity (or coarse) model, one based on a coarser time discretization, the other on an inaccurate fixed point iteration. Since in both cases, the low-fidelity model is less accurate, we use a multiplicative response correction technique, aligning the low- and the high-fidelity model output to obtain a reliable surrogate at the current iterate in the optimization process. We verify the approach by using model generated target data. We show that the proposed SBO method leads to a very satisfactory solution at the cost of a few evaluations of the high-fidelity model only.

Document Type:	Article
Keywords:	Climate models, marine ecosystem models, parameter identification, parameter optimization, surrogate-based optimization, low-fidelity models, response correction
Research affiliation:	OceanRep > The Future Ocean - Cluster of Excellence > FO-R07 OceanRep > The Future Ocean - Cluster of Excellence > FO-R05 Kiel University > Kiel Marine Science OceanRep > The Future Ocean - Cluster of Excellence OceanRep > The Future Ocean - Cluster of Excellence > FO-R11 Kiel University
Refereed:	Yes
Open Access Journal?:	No
Publisher:	Elsevier
Projects:	Future Ocean
Date Deposited:	11 Dec 2012 13:34
Last Modified:	23 Sep 2019 18:33
URI:	https://oceanrep.geomar.de/id/eprint/19656

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