Forcing, feedback and internal variability in global temperature trends.
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| Title: | Forcing, feedback and internal variability in global temperature trends. |
|---|---|
| Authors: | Marotzke, Jochem, Forster, Piers M. |
| Source: | Nature. 1/29/2015, Vol. 517 Issue 7536, p565-570. 6p. |
| Subjects: | Global warming research, Surface temperature, Radiative forcing, Climate feedbacks, Greenhouse gases research, Computer simulation of climate change |
| Abstract: | Most present-generation climate models simulate an increase in global-mean surface temperature (GMST) since 1998, whereas observations suggest a warming hiatus. It is unclear to what extent this mismatch is caused by incorrect model forcing, by incorrect model response to forcing or by random factors. Here we analyse simulations and observations of GMST from 1900 to 2012, and show that the distribution of simulated 15-year trends shows no systematic bias against the observations. Using a multiple regression approach that is physically motivated by surface energy balance, we isolate the impact of radiative forcing, climate feedback and ocean heat uptake on GMST-with the regression residual interpreted as internal variability-and assess all possible 15- and 62-year trends. The differences between simulated and observed trends are dominated by random internal variability over the shorter timescale and by variations in the radiative forcings used to drive models over the longer timescale. For either trend length, spread in simulated climate feedback leaves no traceable imprint on GMST trends or, consequently, on the difference between simulations and observations. The claim that climate models systematically overestimate the response to radiative forcing from increasing greenhouse gas concentrations therefore seems to be unfounded. [ABSTRACT FROM AUTHOR] |
| Copyright of Nature is the property of Springer Nature 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: | Psychology and Behavioral Sciences Collection |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 100798787 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Forcing, feedback and internal variability in global temperature trends. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Marotzke%2C+Jochem%22">Marotzke, Jochem</searchLink><br /><searchLink fieldCode="AR" term="%22Forster%2C+Piers+M%2E%22">Forster, Piers M.</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Nature%22">Nature</searchLink>. 1/29/2015, Vol. 517 Issue 7536, p565-570. 6p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Global+warming+research%22">Global warming research</searchLink><br /><searchLink fieldCode="DE" term="%22Surface+temperature%22">Surface temperature</searchLink><br /><searchLink fieldCode="DE" term="%22Radiative+forcing%22">Radiative forcing</searchLink><br /><searchLink fieldCode="DE" term="%22Climate+feedbacks%22">Climate feedbacks</searchLink><br /><searchLink fieldCode="DE" term="%22Greenhouse+gases+research%22">Greenhouse gases research</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation+of+climate+change%22">Computer simulation of climate change</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Most present-generation climate models simulate an increase in global-mean surface temperature (GMST) since 1998, whereas observations suggest a warming hiatus. It is unclear to what extent this mismatch is caused by incorrect model forcing, by incorrect model response to forcing or by random factors. Here we analyse simulations and observations of GMST from 1900 to 2012, and show that the distribution of simulated 15-year trends shows no systematic bias against the observations. Using a multiple regression approach that is physically motivated by surface energy balance, we isolate the impact of radiative forcing, climate feedback and ocean heat uptake on GMST-with the regression residual interpreted as internal variability-and assess all possible 15- and 62-year trends. The differences between simulated and observed trends are dominated by random internal variability over the shorter timescale and by variations in the radiative forcings used to drive models over the longer timescale. For either trend length, spread in simulated climate feedback leaves no traceable imprint on GMST trends or, consequently, on the difference between simulations and observations. The claim that climate models systematically overestimate the response to radiative forcing from increasing greenhouse gas concentrations therefore seems to be unfounded. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Nature is the property of Springer Nature 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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/nature14117 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 6 StartPage: 565 Subjects: – SubjectFull: Global warming research Type: general – SubjectFull: Surface temperature Type: general – SubjectFull: Radiative forcing Type: general – SubjectFull: Climate feedbacks Type: general – SubjectFull: Greenhouse gases research Type: general – SubjectFull: Computer simulation of climate change Type: general Titles: – TitleFull: Forcing, feedback and internal variability in global temperature trends. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Marotzke, Jochem – PersonEntity: Name: NameFull: Forster, Piers M. IsPartOfRelationships: – BibEntity: Dates: – D: 29 M: 01 Text: 1/29/2015 Type: published Y: 2015 Identifiers: – Type: issn-print Value: 00280836 Numbering: – Type: volume Value: 517 – Type: issue Value: 7536 Titles: – TitleFull: Nature Type: main |
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