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Activity Number: 129
Type: Contributed
Date/Time: Monday, August 10, 2015 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics and the Environment
Abstract #316353 View Presentation
Title: Bivariate Spatial Analysis of Temperature and Precipitation from General Circulation Models and Observations
Author(s): Robert Philbin* and Mikyoung Jun
Companies: and Texas A&M University
Keywords: multivariate ; spatial ; climate ; Matern ; cross-correlation ; general circulation model
Abstract:

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 Matern spatial covariance model, accounting for the two fields' spatial cross-correlation and smoothness values. We fit 30 year seasonal averages from each AOGCM 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 show temperature fields 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 are quite different for most models in mid-latitudes and southern hemisphere. Model correlation estimates agree well with those for observations for Australia, at high northern latitudes, and some tropical regions, but elsewhere little consistent agreement exists.


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