Scale-dependent regional climate predictability over North America inferred from CMIP3 and CMIP5 ensemble simulations.
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| Title: | Scale-dependent regional climate predictability over North America inferred from CMIP3 and CMIP5 ensemble simulations. |
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| Authors: | Zhang, Fuqing1 fzhang@psu.edu, Li, Wei, Mann, Michael1 |
| Source: | Advances in Atmospheric Sciences. Aug2016, Vol. 33 Issue 8, p905-918. 14p. |
| Subject Terms: | *Computer simulation of climate change, *Computer simulation of weather forecasting, *Simulation methods & models, *Earth temperature |
| Geographic Terms: | North America |
| Abstract: | Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty (noise) in surface temperature predictions (represented by the spread among an ensemble of global climate model simulations) generally exceeds the ensemble mean (signal) at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 116192173 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Scale-dependent regional climate predictability over North America inferred from CMIP3 and CMIP5 ensemble simulations. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Fuqing%22">Zhang, Fuqing</searchLink><relatesTo>1</relatesTo><i> fzhang@psu.edu</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Wei%22">Li, Wei</searchLink><br /><searchLink fieldCode="AR" term="%22Mann%2C+Michael%22">Mann, Michael</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Advances+in+Atmospheric+Sciences%22">Advances in Atmospheric Sciences</searchLink>. Aug2016, Vol. 33 Issue 8, p905-918. 14p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Computer+simulation+of+climate+change%22">Computer simulation of climate change</searchLink><br />*<searchLink fieldCode="DE" term="%22Computer+simulation+of+weather+forecasting%22">Computer simulation of weather forecasting</searchLink><br />*<searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br />*<searchLink fieldCode="DE" term="%22Earth+temperature%22">Earth temperature</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22North+America%22">North America</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty (noise) in surface temperature predictions (represented by the spread among an ensemble of global climate model simulations) generally exceeds the ensemble mean (signal) at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness. [ABSTRACT FROM AUTHOR] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=116192173 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00376-016-6013-2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 905 Subjects: – SubjectFull: Computer simulation of climate change Type: general – SubjectFull: Computer simulation of weather forecasting Type: general – SubjectFull: Simulation methods & models Type: general – SubjectFull: Earth temperature Type: general – SubjectFull: North America Type: general Titles: – TitleFull: Scale-dependent regional climate predictability over North America inferred from CMIP3 and CMIP5 ensemble simulations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhang, Fuqing – PersonEntity: Name: NameFull: Li, Wei – PersonEntity: Name: NameFull: Mann, Michael IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2016 Type: published Y: 2016 Identifiers: – Type: issn-print Value: 02561530 Numbering: – Type: volume Value: 33 – Type: issue Value: 8 Titles: – TitleFull: Advances in Atmospheric Sciences Type: main |
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