Interannual variability of patterns of atmospheric mass distribution.

Kevin E. Trenberth, David P. Stepaniak and Lesley Smith

National Center for Atmospheric Research
P. O. Box 3000
Boulder, CO 80307

voice: (303) 497 1318
fax: (303) 497 1333


Using the ERA-40 reanalyses from the European Centre for Medium Range Weather Forecasts (ECMWF) for 1958 to 2001, adjusted for bias over the southern oceans prior to 1979, an analysis is made of monthly mean anomalies of global atmospheric mass, which is approximately conserved. To the extent that global patterns of behavior exist this also argues against analysis of separate seasons as they are opposite in each hemisphere. It differs from previous analyses of atmospheric circulation by effectively areal weighting of surface or sea level pressure that dimishes the role of high latitudes. Empirical orthogonal function (EOF) analysis, R-mode varimax rotated EOF analysis, and cyclostationary EOF (CSEOF) analysis tools are used to explore patterns and variability on interannual and longer time scales. The dominant global mode of variability overall is revealed to be one associated with the Southern Annular Mode (SAM), which is active in all months of the year. However, it is not very coherent from month to month and exhibits a great deal of natural unforced variability. The third most important mode is Northern Annular Mode (NAM) and the associated North Atlantic Oscillation (NAO), which is the equivalent northern hemisphere expression. Neither of these are global modes, however, except perhaps on long timescales associated with tropical or external forcing. For monthly data, El Nino-Southern Oscillation (ENSO) comes in as the second mode, and is truly global in extent. However, it also exhibits more coherent evolution with time and projects strongest onto the interannual variability, where it stands out by far as the dominant mode in the CSEOF analysis. It is coherent with Nino 3.4 SSTs and thus is a coupled mode. The CSEOF analysis extracts the patterns phase-locked with annual cycle, and reveals evolution throughout the year. Standard EOF and varimax analyses are not able to evolve with time of year, unless the analysis is stratified by season. Varimax analysis is able to extract the SAM, NAM, and ENSO modes very well, however.

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