SLP interannual variability over Southern South America as represented by IPCC-AR4 models

VICENTE BARROS; ALEJANDRO DI LUCA; CAMILLONI, INÉS

San Francisco, USA

Workshop; WGNE Workshop on Systematic Errors in Climate and NWP Models; 2007

Program for Climate Diagnosis and Intercomparison

Global climate model outputs available for the preparation of the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) were evaluated to assess the ability to represent the predominant patterns of SLP interannual variability over a region of the Southern Hemisphere that comprises Southern South America and part of the South Atlantic and South Pacific oceans. Models with good representation of the dominant regional patterns were selected to analyze future scenarios. Predominant patterns of SLP and their evolutions were analyzed under different SRES scenarios. Monthly mean SLP fields of NCEP/NCAR reanalyses and of GCMs were analyzed over an area between 20°S-45°S and 130°W- 0°. Two different periods were studied: one associated with present climate between 1978 and 2000, and the other associated with future climate, between 2001 and 2100. The relatively short period used to represent the present climate was selected because the reanalyses are more representative of real data over the oceanic areas only after 1978 when satellite data began to be fully used. The evaluation of the simulations of present climate was done using Climate of the 20th Century (20C3M) experiments; the scenarios A1B, A2 and B1 were used for the period 2001-2100. The identification of the dominant SLP patterns over the selected region was performed through a T-mode Varimax Rotated Principal Components Analysis (PCA) using the NCEP/NCAR reanalyses and the outputs from some selected models using the correlation matrix as input. To evaluate the ability of the GCMs to represent the ?observed? SLP fields, linear spatial correlation coefficients between monthly mean SLP fields derived from the NCEP/NCAR reanalyses and from GCMs were calculated. Likewise, for the same purpose, linear correlation coefficients between the PCs derived from the NCEP/NCAR reanalyses and from the GCMs outputs were also calculated. The T-mode PCA of the monthly mean SLP obtained from NCEP/NCAR reanalyses shows that there are three predominant patterns that characterize SLP fields over the extended region of the Southern Hemisphere analyzed. PC1 represents the summer surface circulation with the South Atlantic and South Pacific highs in their southernmost positions. PC2 and PC3 represent the winter circulation with the South Atlantic and South Pacific in the northernmost position (PC2) and a surface pattern that characterizes the frontal activity during that season (PC3). Time series of the three PCs show a positive linear trend of the summer mode and slightly negative trends for the winter indicating that the summer mode increased at the expense of the winter ones. Monthly correlation coefficients between the output from the GCMs and the NCEP/NCAR reanalyses show that all of the models represent adequately the SLP fields during most of the year with the lower correlations during the austral autumn (March-April-May). The GCMs with better representation of the monthly mean SLP fields are UKMO_HadGEM1, UKMO_HadCM3, ECHAM5/MPI-OM, IPSL-CM4 and CNRM-CM3, with correlation coefficients higher than 0.75 for all months. Application of PCA to the GCMs outputs of four of these models show that most of them represent the same spatial and temporal variability identified with NCEP/NCAR reanalyses. These GCMs show the same three dominant patterns and also represent adequately the linear trends, showing an increase of the summer mode at expense of the winter ones, especially in UKMO_HadGEM1, ECHAM5/MPI-OM and CNRM-CM3. This result indicates that these set of GCMs are able to represent not only mean fields but also the interannual variability of SLP over the analyzed region. The PCA performed to the GCMs output corresponding to the future period shows approximately the same predominant patterns of SLP obtained for the 20C3M experiments. The time series associated indicate that the increase of the summer mode at the expense of the winter one will continue. These trends are more pronounced in the A2 scenario showing that the changes are related to differences between atmospheric concentrations gases.