Identifying and removing structural biases in climate models with history matching
Identifying and removing structural biases in climate models with history matching
We describe the method of history matching, a method currently used to help quantify parametric uncertainty in climate models, and argue for its use in identifying and removing structural biases in climate models at the model development stage. We illustrate the method using an investigation of the potential to improve upon known ocean circulation biases in a coupled non-flux-adjusted climate model (the third Hadley Centre Climate Model; HadCM3). In particular, we use history matching to investigate whether or not the behaviour of the Antarctic Circumpolar Current (ACC), which is known to be too strong in HadCM3, represents a structural bias that could be corrected using the model parameters. We find that it is possible to improve the ACC strength using the parameters and observe that doing this leads to more realistic representations of the sub-polar and sub-tropical gyres, sea surface salinities (both globally and in the North Atlantic), sea surface temperatures in the sinking regions in the North Atlantic and in the Southern Ocean, North Atlantic Deep Water flows, global precipitation, wind fields and sea level pressure. We then use history matching to locate a region of parameter space predicted not to contain structural biases for ACC and SSTs that is around 1 % of the original parameter space. We explore qualitative features of this space and show that certain key ocean and atmosphere parameters must be tuned carefully together in order to locate climates that satisfy our chosen metrics. Our study shows that attempts to tune climate model parameters that vary only a handful of parameters relevant to a given process at a time will not be as successful or as efficient as history matching.
Tuning, Ensembles, Emulators, HadCM3, Climate model
1299-1324
Williamson, Daniel
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Blaker, Adam T.
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Hampton, Charlotte
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Salter, James
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September 2015
Williamson, Daniel
4c0c5b3b-69ac-48d5-aa6e-1b52219f2c81
Blaker, Adam T.
94efe8b2-c744-4e90-87d7-db19ffa41200
Hampton, Charlotte
6b7b44a4-93b5-4c57-bc26-9497fcdc6379
Salter, James
d13857ac-668f-41bf-ab03-d9ac499feac2
Williamson, Daniel, Blaker, Adam T., Hampton, Charlotte and Salter, James
(2015)
Identifying and removing structural biases in climate models with history matching.
Climate Dynamics, 45 (5), .
(doi:10.1007/s00382-014-2378-z).
Abstract
We describe the method of history matching, a method currently used to help quantify parametric uncertainty in climate models, and argue for its use in identifying and removing structural biases in climate models at the model development stage. We illustrate the method using an investigation of the potential to improve upon known ocean circulation biases in a coupled non-flux-adjusted climate model (the third Hadley Centre Climate Model; HadCM3). In particular, we use history matching to investigate whether or not the behaviour of the Antarctic Circumpolar Current (ACC), which is known to be too strong in HadCM3, represents a structural bias that could be corrected using the model parameters. We find that it is possible to improve the ACC strength using the parameters and observe that doing this leads to more realistic representations of the sub-polar and sub-tropical gyres, sea surface salinities (both globally and in the North Atlantic), sea surface temperatures in the sinking regions in the North Atlantic and in the Southern Ocean, North Atlantic Deep Water flows, global precipitation, wind fields and sea level pressure. We then use history matching to locate a region of parameter space predicted not to contain structural biases for ACC and SSTs that is around 1 % of the original parameter space. We explore qualitative features of this space and show that certain key ocean and atmosphere parameters must be tuned carefully together in order to locate climates that satisfy our chosen metrics. Our study shows that attempts to tune climate model parameters that vary only a handful of parameters relevant to a given process at a time will not be as successful or as efficient as history matching.
Text
Williamson_et_al_StructErrorPaper.pdf
- Accepted Manuscript
More information
Accepted/In Press date: October 2014
e-pub ahead of print date: October 2014
Published date: September 2015
Keywords:
Tuning, Ensembles, Emulators, HadCM3, Climate model
Organisations:
Marine Systems Modelling
Identifiers
Local EPrints ID: 373159
URI: http://eprints.soton.ac.uk/id/eprint/373159
ISSN: 0930-7575
PURE UUID: 42ffa695-d726-4216-8d36-6bc7f0be4ff5
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Date deposited: 08 Jan 2015 14:27
Last modified: 14 Mar 2024 18:49
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Contributors
Author:
Daniel Williamson
Author:
Adam T. Blaker
Author:
Charlotte Hampton
Author:
James Salter
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