View in EDS PDF Full Text

Quantification of modelling uncertainties in a large ensemble of climate change simulations.

Saved in:
Bibliographic Details
Title: Quantification of modelling uncertainties in a large ensemble of climate change simulations.
Authors: Murphy, James M., Sexton, David M.H., Barnett, David N., Jones, Gareth S., Webb, Mark J., Collins, Matthew, Stainforth, David A.
Source: Nature. 8/12/2004, Vol. 430 Issue 7001, p768-772. 5p.
Subjects: Climate change, Atmospheric carbon dioxide, Probability theory, Climatology, Uncertainty, Atmospheric density
Abstract: Comprehensive global climate models are the only tools that account for the complex set of processes which will determine future climate change at both a global and regional level. Planners are typically faced with a wide range of predicted changes from different models of unknown relative quality, owing to large but unquantified uncertainties in the modelling process. Here we report a systematic attempt to determine the range of climate changes consistent with these uncertainties, based on a 53-member ensemble of model versions constructed by varying model parameters. We estimate a probability density function for the sensitivity of climate to a doubling of atmospheric carbon dioxide levels, and obtain a 5-95 per cent probability range of 2.4-5.4?°C. Our probability density function is constrained by objective estimates of the relative reliability of different model versions, the choice of model parameters that are varied and their uncertainty ranges, specified on the basis of expert advice. Our ensemble produces a range of regional changes much wider than indicated by traditional methods based on scaling the response patterns of an individual simulation. [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
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 14097088
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Quantification of modelling uncertainties in a large ensemble of climate change simulations.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Murphy%2C+James+M%2E%22">Murphy, James M.</searchLink><br /><searchLink fieldCode="AR" term="%22Sexton%2C+David+M%2EH%2E%22">Sexton, David M.H.</searchLink><br /><searchLink fieldCode="AR" term="%22Barnett%2C+David+N%2E%22">Barnett, David N.</searchLink><br /><searchLink fieldCode="AR" term="%22Jones%2C+Gareth+S%2E%22">Jones, Gareth S.</searchLink><br /><searchLink fieldCode="AR" term="%22Webb%2C+Mark+J%2E%22">Webb, Mark J.</searchLink><br /><searchLink fieldCode="AR" term="%22Collins%2C+Matthew%22">Collins, Matthew</searchLink><br /><searchLink fieldCode="AR" term="%22Stainforth%2C+David+A%2E%22">Stainforth, David A.</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Nature%22">Nature</searchLink>. 8/12/2004, Vol. 430 Issue 7001, p768-772. 5p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br /><searchLink fieldCode="DE" term="%22Atmospheric+carbon+dioxide%22">Atmospheric carbon dioxide</searchLink><br /><searchLink fieldCode="DE" term="%22Probability+theory%22">Probability theory</searchLink><br /><searchLink fieldCode="DE" term="%22Climatology%22">Climatology</searchLink><br /><searchLink fieldCode="DE" term="%22Uncertainty%22">Uncertainty</searchLink><br /><searchLink fieldCode="DE" term="%22Atmospheric+density%22">Atmospheric density</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Comprehensive global climate models are the only tools that account for the complex set of processes which will determine future climate change at both a global and regional level. Planners are typically faced with a wide range of predicted changes from different models of unknown relative quality, owing to large but unquantified uncertainties in the modelling process. Here we report a systematic attempt to determine the range of climate changes consistent with these uncertainties, based on a 53-member ensemble of model versions constructed by varying model parameters. We estimate a probability density function for the sensitivity of climate to a doubling of atmospheric carbon dioxide levels, and obtain a 5-95 per cent probability range of 2.4-5.4?°C. Our probability density function is constrained by objective estimates of the relative reliability of different model versions, the choice of model parameters that are varied and their uncertainty ranges, specified on the basis of expert advice. Our ensemble produces a range of regional changes much wider than indicated by traditional methods based on scaling the response patterns of an individual simulation. [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.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=14097088
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1038/nature02771
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 5
        StartPage: 768
    Subjects:
      – SubjectFull: Climate change
        Type: general
      – SubjectFull: Atmospheric carbon dioxide
        Type: general
      – SubjectFull: Probability theory
        Type: general
      – SubjectFull: Climatology
        Type: general
      – SubjectFull: Uncertainty
        Type: general
      – SubjectFull: Atmospheric density
        Type: general
    Titles:
      – TitleFull: Quantification of modelling uncertainties in a large ensemble of climate change simulations.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Murphy, James M.
      – PersonEntity:
          Name:
            NameFull: Sexton, David M.H.
      – PersonEntity:
          Name:
            NameFull: Barnett, David N.
      – PersonEntity:
          Name:
            NameFull: Jones, Gareth S.
      – PersonEntity:
          Name:
            NameFull: Webb, Mark J.
      – PersonEntity:
          Name:
            NameFull: Collins, Matthew
      – PersonEntity:
          Name:
            NameFull: Stainforth, David A.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 12
              M: 08
              Text: 8/12/2004
              Type: published
              Y: 2004
          Identifiers:
            – Type: issn-print
              Value: 00280836
          Numbering:
            – Type: volume
              Value: 430
            – Type: issue
              Value: 7001
          Titles:
            – TitleFull: Nature
              Type: main
ResultId 1