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MIKYOUNG JUN - Texas A & M University

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Bivariate Spatial Analysis of Temperature and Precipitation from General Circulation Models and Observations
23 April 2015 from 4:00 PM to 5:00 PM
201 Thomas Bldg.
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This study validates the near-surface temperature and precipitation output from decadal runs of eight atmospheric ocean general circulation models (AOGCMs) against observational data from NCEP/NCAR reanalysis temperatures and GPCP precipitation data. We modeled 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 are rougher than precipitation   fields, while both are increasingly rough with increasing latitude. Models predict rougher fields than observations for the tropics. The estimated spatial cross-correlations of these two fields, however, are quite different for most models in mid-latitudes. Model correlation estimates agree well with those for observations 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. 

This is joint work with a PhD student, Robert Philbin, at Department of Statistics, Texas A&M University.

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