Analyzing the Climate Sensitivity of the HadSM3 Climate Model Using Ensembles from Different but Related Experiments.
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| Title: | Analyzing the Climate Sensitivity of the HadSM3 Climate Model Using Ensembles from Different but Related Experiments. |
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| Authors: | Rougier, Jonathan1 j.c.rougier@bristol.ac.uk, Sexton, David M. H.2, Murphy, James M.2, Stainforth, David3 |
| Source: | Journal of Climate. Jul2009, Vol. 22 Issue 13, p3540-3557. 18p. 1 Diagram, 1 Chart, 7 Graphs. |
| Subject Terms: | *Climate change, *Precipitation variability, *Spatio-temporal variation, *Atmospheric temperature, *Atmospheric circulation, *Climatology, Bayesian analysis |
| Abstract: | Global climate models (GCMs) contain imprecisely defined parameters that account, approximately, for subgrid-scale physical processes. The response of a GCM to perturbations in its parameters, which is crucial for quantifying uncertainties in simulations of climate change, can—in principle—be assessed by simulating the GCM many times. In practice, however, such “perturbed physics” ensembles are small because GCMs are so expensive to simulate. Statistical tools can help in two ways. First, they can be used to combine ensembles from different but related experiments, increasing the effective number of simulations. Second, they can be used to describe the GCM’s response in ways that cannot be extracted directly from the ensemble(s). The authors combine two experiments to learn about the response of the Hadley Centre Slab Climate Model version 3 (HadSM3) climate sensitivity to 31 model parameters. A Bayesian statistical framework is used in which expert judgments are required to quantify the relationship between the two experiments; these judgments are validated by detailed diagnostics. The authors identify the entrainment rate coefficient of the convection scheme as the most important single parameter and find that this interacts strongly with three of the large-scale-cloud parameters. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Climate is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | GreenFILE |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 43276945 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Analyzing the Climate Sensitivity of the HadSM3 Climate Model Using Ensembles from Different but Related Experiments. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rougier%2C+Jonathan%22">Rougier, Jonathan</searchLink><relatesTo>1</relatesTo><i> j.c.rougier@bristol.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Sexton%2C+David+M%2E+H%2E%22">Sexton, David M. H.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Murphy%2C+James+M%2E%22">Murphy, James M.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Stainforth%2C+David%22">Stainforth, David</searchLink><relatesTo>3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Climate%22">Journal of Climate</searchLink>. Jul2009, Vol. 22 Issue 13, p3540-3557. 18p. 1 Diagram, 1 Chart, 7 Graphs. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br />*<searchLink fieldCode="DE" term="%22Precipitation+variability%22">Precipitation variability</searchLink><br />*<searchLink fieldCode="DE" term="%22Spatio-temporal+variation%22">Spatio-temporal variation</searchLink><br />*<searchLink fieldCode="DE" term="%22Atmospheric+temperature%22">Atmospheric temperature</searchLink><br />*<searchLink fieldCode="DE" term="%22Atmospheric+circulation%22">Atmospheric circulation</searchLink><br />*<searchLink fieldCode="DE" term="%22Climatology%22">Climatology</searchLink><br /><searchLink fieldCode="DE" term="%22Bayesian+analysis%22">Bayesian analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Global climate models (GCMs) contain imprecisely defined parameters that account, approximately, for subgrid-scale physical processes. The response of a GCM to perturbations in its parameters, which is crucial for quantifying uncertainties in simulations of climate change, can—in principle—be assessed by simulating the GCM many times. In practice, however, such “perturbed physics” ensembles are small because GCMs are so expensive to simulate. Statistical tools can help in two ways. First, they can be used to combine ensembles from different but related experiments, increasing the effective number of simulations. Second, they can be used to describe the GCM’s response in ways that cannot be extracted directly from the ensemble(s). The authors combine two experiments to learn about the response of the Hadley Centre Slab Climate Model version 3 (HadSM3) climate sensitivity to 31 model parameters. A Bayesian statistical framework is used in which expert judgments are required to quantify the relationship between the two experiments; these judgments are validated by detailed diagnostics. The authors identify the entrainment rate coefficient of the convection scheme as the most important single parameter and find that this interacts strongly with three of the large-scale-cloud parameters. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Climate is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=8gh&AN=43276945 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1175/2008JCLI2533.1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 3540 Subjects: – SubjectFull: Climate change Type: general – SubjectFull: Precipitation variability Type: general – SubjectFull: Spatio-temporal variation Type: general – SubjectFull: Atmospheric temperature Type: general – SubjectFull: Atmospheric circulation Type: general – SubjectFull: Climatology Type: general – SubjectFull: Bayesian analysis Type: general Titles: – TitleFull: Analyzing the Climate Sensitivity of the HadSM3 Climate Model Using Ensembles from Different but Related Experiments. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rougier, Jonathan – PersonEntity: Name: NameFull: Sexton, David M. H. – PersonEntity: Name: NameFull: Murphy, James M. – PersonEntity: Name: NameFull: Stainforth, David IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2009 Type: published Y: 2009 Identifiers: – Type: issn-print Value: 08948755 Numbering: – Type: volume Value: 22 – Type: issue Value: 13 Titles: – TitleFull: Journal of Climate Type: main |
| ResultId | 1 |
