Bivariate spatial analysis of temperature and precipitation from general circulation models and observation proxies

Handle URI:
http://hdl.handle.net/10754/597680
Title:
Bivariate spatial analysis of temperature and precipitation from general circulation models and observation proxies
Authors:
Philbin, R.; Jun, M.
Abstract:
This study validates the near-surface temperature and precipitation output from decadal runs of eight atmospheric ocean general circulation models (AOGCMs) against observational proxy data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis temperatures and Global Precipitation Climatology Project (GPCP) precipitation data. We model the joint distribution of these two fields with a parsimonious bivariate Matérn spatial covariance model, accounting for the two fields' spatial cross-correlation as well as their own smoothnesses. We fit output from each AOGCM (30-year seasonal averages from 1981 to 2010) to a statistical model on each of 21 land regions. Both variance and smoothness values agree for both fields over all latitude bands except southern mid-latitudes. Our results imply that temperature fields have smaller smoothness coefficients than precipitation fields, while both have decreasing smoothness coefficients with increasing latitude. Models predict fields with smaller smoothness coefficients than observational proxy data for the tropics. The estimated spatial cross-correlations of these two fields, however, are quite different for most GCMs in mid-latitudes. Model correlation estimates agree well with those for observational proxy data for Australia, at high northern latitudes across North America, Europe and Asia, as well as across the Sahara, India, and Southeast Asia, but elsewhere, little consistent agreement exists.
Citation:
Philbin R, Jun M (2015) Bivariate spatial analysis of temperature and precipitation from general circulation models and observation proxies. Advances in Statistical Climatology Meteorology and Oceanography 1: 29–44. Available: http://dx.doi.org/10.5194/ascmo-1-29-2015.
Publisher:
Copernicus GmbH
Journal:
Advances in Statistical Climatology Meteorology and Oceanography
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
22-May-2015
DOI:
10.5194/ascmo-1-29-2015
Type:
Article
ISSN:
2364-3587
Sponsors:
The authors thank G. North and R. Saravanan for their very constructive and helpful comments regarding this work. This publication is based in part on work supported by
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorPhilbin, R.en
dc.contributor.authorJun, M.en
dc.date.accessioned2016-02-25T12:44:17Zen
dc.date.available2016-02-25T12:44:17Zen
dc.date.issued2015-05-22en
dc.identifier.citationPhilbin R, Jun M (2015) Bivariate spatial analysis of temperature and precipitation from general circulation models and observation proxies. Advances in Statistical Climatology Meteorology and Oceanography 1: 29–44. Available: http://dx.doi.org/10.5194/ascmo-1-29-2015.en
dc.identifier.issn2364-3587en
dc.identifier.doi10.5194/ascmo-1-29-2015en
dc.identifier.urihttp://hdl.handle.net/10754/597680en
dc.description.abstractThis study validates the near-surface temperature and precipitation output from decadal runs of eight atmospheric ocean general circulation models (AOGCMs) against observational proxy data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis temperatures and Global Precipitation Climatology Project (GPCP) precipitation data. We model the joint distribution of these two fields with a parsimonious bivariate Matérn spatial covariance model, accounting for the two fields' spatial cross-correlation as well as their own smoothnesses. We fit output from each AOGCM (30-year seasonal averages from 1981 to 2010) to a statistical model on each of 21 land regions. Both variance and smoothness values agree for both fields over all latitude bands except southern mid-latitudes. Our results imply that temperature fields have smaller smoothness coefficients than precipitation fields, while both have decreasing smoothness coefficients with increasing latitude. Models predict fields with smaller smoothness coefficients than observational proxy data for the tropics. The estimated spatial cross-correlations of these two fields, however, are quite different for most GCMs in mid-latitudes. Model correlation estimates agree well with those for observational proxy data for Australia, at high northern latitudes across North America, Europe and Asia, as well as across the Sahara, India, and Southeast Asia, but elsewhere, little consistent agreement exists.en
dc.description.sponsorshipThe authors thank G. North and R. Saravanan for their very constructive and helpful comments regarding this work. This publication is based in part on work supported byen
dc.publisherCopernicus GmbHen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.titleBivariate spatial analysis of temperature and precipitation from general circulation models and observation proxiesen
dc.typeArticleen
dc.identifier.journalAdvances in Statistical Climatology Meteorology and Oceanographyen
dc.contributor.institutionDepartment of Statistics, Texas A&M University, College Station, TAMU, 77843-3143, USAen
kaust.grant.numberKUS-C1-016-04en
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