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dc.contributor.authorParsons, Luke A.
dc.contributor.authorLoope, Garrison R.
dc.contributor.authorOverpeck, Jonathan T.
dc.contributor.authorAult, Toby R.
dc.contributor.authorStouffer, Ronald
dc.contributor.authorCole, Julia E.
dc.date.accessioned2017-12-21T16:46:17Z
dc.date.available2017-12-21T16:46:17Z
dc.date.issued2017-11
dc.identifier.citationTemperature and Precipitation Variance in CMIP5 Simulations and Paleoclimate Records of the Last Millennium 2017, 30 (22):8885 Journal of Climateen
dc.identifier.issn0894-8755
dc.identifier.issn1520-0442
dc.identifier.doi10.1175/JCLI-D-16-0863.1
dc.identifier.urihttp://hdl.handle.net/10150/626270
dc.description.abstractAccurate assessments of future climate impacts require realistic simulation of interannual-century-scale temperature and precipitation variability. Here, well-constrained paleoclimate data and the latest generation of Earth system model data are used to evaluate the magnitude and spatial consistency of climate variance distributions across interannual to centennial frequencies. It is found that temperature variance generally increases with time scale in patterns that are spatially consistent among models, especially over the mid-and high-latitude oceans. However, precipitation is similar to white noise across much of the globe. When Earth system model variance is compared to variance generated by simple autocorrelation, it is found that tropical temperature variability in Earth system models is difficult to distinguish from variability generated by simple autocorrelation. By contrast, both forced and unforced Earth system models produce variability distinct from a simple autoregressive process over most high-latitude oceans. This new analysis of tropical paleoclimate records suggests that low-frequency variance dominates the temperature spectrum across the tropical Pacific and Indian Oceans, but in many Earth system models, interannual variance dominates the simulated central and eastern tropical Pacific temperature spectrum, regardless of forcing. Tropical Pacific model spectra are compared to spectra from the instrumental record, but the short instrumental record likely cannot provide accurate multidecadal-centennial-scale variance estimates. In the coming decades, both forced and natural patterns of decade-century-scale variability will determine climate-related risks. Underestimating low-frequency temperature and precipitation variability may significantly alter our understanding of the projections of these climate impacts.
dc.description.sponsorshipNational Science Foundation EaSM2 Grant [AGS-1243125]; Directorate for Geosciences [3008610]; Graduate Research Fellowship [DGE-1143953]; Kartchner Caverns scholarship fund; Department of Geosciences at the University of Arizonaen
dc.language.isoenen
dc.publisherAMER METEOROLOGICAL SOCen
dc.relation.urlhttp://journals.ametsoc.org/doi/10.1175/JCLI-D-16-0863.1en
dc.rights© 2017 American Meteorological Society.en
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.titleTemperature and Precipitation Variance in CMIP5 Simulations and Paleoclimate Records of the Last Millenniumen
dc.typeArticleen
dc.contributor.departmentUniv Arizona, Dept Geoscien
dc.contributor.departmentUniv Arizona, Dept Hydrol & Atmospher Scien
dc.identifier.journalJournal of Climateen
dc.description.note6 month embargo; published online: 17 Oct 2017en
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
dc.contributor.institutionDepartment of Geosciences, The University of Arizona, Tucson, Arizona
dc.contributor.institutionDepartment of Geosciences, The University of Arizona, Tucson, Arizona
dc.contributor.institutionDepartment of Geosciences, and Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, Arizona
dc.contributor.institutionDepartment of Earth and Atmospheric Sciences, Cornell University, Ithaca, New York
dc.contributor.institutionDepartment of Geosciences, The University of Arizona, Tucson, Arizona
dc.contributor.institutionDepartment of Geosciences, and Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, Arizona
refterms.dateFOA2018-04-17T00:00:00Z
html.description.abstractAccurate assessments of future climate impacts require realistic simulation of interannual-century-scale temperature and precipitation variability. Here, well-constrained paleoclimate data and the latest generation of Earth system model data are used to evaluate the magnitude and spatial consistency of climate variance distributions across interannual to centennial frequencies. It is found that temperature variance generally increases with time scale in patterns that are spatially consistent among models, especially over the mid-and high-latitude oceans. However, precipitation is similar to white noise across much of the globe. When Earth system model variance is compared to variance generated by simple autocorrelation, it is found that tropical temperature variability in Earth system models is difficult to distinguish from variability generated by simple autocorrelation. By contrast, both forced and unforced Earth system models produce variability distinct from a simple autoregressive process over most high-latitude oceans. This new analysis of tropical paleoclimate records suggests that low-frequency variance dominates the temperature spectrum across the tropical Pacific and Indian Oceans, but in many Earth system models, interannual variance dominates the simulated central and eastern tropical Pacific temperature spectrum, regardless of forcing. Tropical Pacific model spectra are compared to spectra from the instrumental record, but the short instrumental record likely cannot provide accurate multidecadal-centennial-scale variance estimates. In the coming decades, both forced and natural patterns of decade-century-scale variability will determine climate-related risks. Underestimating low-frequency temperature and precipitation variability may significantly alter our understanding of the projections of these climate impacts.


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