Characterizing the zonally asymmetric component of

Authors: William R Hobbs Marilyn N Raphael

Publish Date: 2009/09/17

Volume: 35, Issue: 5, Pages: 859-873

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Abstract

Much research concerning the Southern Hemisphere SH zonally asymmetric circulation has focused on the PacificSouth American mode PSA or the major zonal waves However these largescale decompositions may mask important local variability In this paper the monthtomonth variability explained by the zonal waves 1 and 3 is examined and an alternative representation of the SH circulation is presented based on two quasistationary anticyclones in the subAntarctic western hemisphere These anticyclones are related to the zonal waves but features of their variability are masked by the zonal wave decomposition in particular the anticyclones’ strengths are not positively covariant They are also compared with the leading Principal Components of the SH atmosphere We show that they capture variance independent of the Southern Annular Mode Additionally they explain a generally greater fraction of the variability than the PSA and in a manner that also includes information regarding spatial variability These results have implications for analysis of the atmosphericforcing of western Antarctic climateSince recent Antarctic climate change is spatially heterogeneous and has potentially global significance a clear understanding of the high latitude Southern Hemisphere SH circulation at regional scales is critically important Over the late twentieth century the west Antarctic region has shown one of the strongest warming trends globally but by contrast there has been little significant trend elsewhere in Antarctica Marshall et al 2002 Vaughn et al 2003 Turner et al 2006 Monaghan et al 2008 Steig et al 2009 Over the same period there have been observed trends in west Antarctic sea ice since 1979 there has been a significant increase in sea ice extent in the Ross and Amundsen Seas but a decrease in the Bellingshausen and Weddell Seas of approximately 4–10/decade Liu et al 2004 These changes in sea ice and surface temperature have major implications for the stability of the west Antarctic ice sheet and thus for eustatic sea level Thomas et al 2004A possible driver for these observed changes is thought to be the quasizonally symmetric Southern Annular Mode SAM the dominant mode of atmospheric variability in the Southern Hemisphere high latitude Thompson and Wallace 2000 Thompson et al 2000 There is a robust positive correlation between Antarctic Peninsula AP temperature and the strength of the SAM Thompson and Solomon 2002 Kwok and Comiso 2002 Marshall et al 2006 and a significant strengthening of the SAM has been reported over the period of observed AP warming Gong and Wang 1999 Thompson et al 2000 Marshall 2003 However important aspects of the SH climate cannot be explained by the SAM alone Recent results indicate that recent warming has not been restricted to the AP as previously thought but has been significant across the entire west Antarctica ice sheet Also the seasonal pattern of warming is not consistent with a response to SAM trends Steig et al 2009 Liu et al 2004 showed that relatively little of the recent trends in west Antarctic sea ice can be related to the SAM whilst Lefebvre and Goosse 2008 showed that atmospheric influence on total winter sea ice variability does not project onto any of the currently recognized SH climate modesThe zonally asymmetric component of the SH atmosphere is commonly analyzed with regard to either the zonal harmonic waves or the PacificSouth American mode PSA The PSA describes a wavetrain running from the equatorial Pacific to the southern tip of South America before refracting back northwards over the Atlantic Mo and Ghil 1987 Since it is related to tropical Pacific convection it is thought to be partly responsible for the teleconnection of El NinoSouthern Oscillation ENSO variability to the SH high latitudes eg Karoly 1989 Mo and Higgins 1997 Kiladis and Mo 1998 The PSA mode generally appears in the both the second and third Principal Components PCs of the SH pressure field rather than as a single decomposition the second and third PCs were dubbed the PSA1 and PSA2 patterns by Mo and Higgins 1997 This spread across two components may be partly due to the time scales they represent Mo and Paegle 2001 argue that PSA1 represents the response to interannual ENSO variability and PSA2 is associated with the quasibiennial ENSO componentPC analysis is limited as an analysis tool by the timeindependent patterns of variability returned Temporal variability is expressed with respect to the relative importance of the spatial eigenvector at each time step through their amplitude time series the spatial pattern of each mode is inherently unchanging Recent research indicates that spatial changes in the atmospheric circulation are at least as important as changes in the strength of recognized modes Bertler et al 2004 Raphael 2007 Decomposition into zonal waves by the Fourier transform gives a little more information in this regard since the decomposition returns information regarding the phase ie the longitude of the first wave peak as well as the amplitude of each harmonic but with the disadvantage that the spatial pattern returned is constrained to wellbehaved sinusoidal waveforms which may or may not be the best representation of the atmospheric state In the SH the dominant waves are zonal waves 1 ZW1 and 3 ZW3 In the mean ZW1 and ZW3 between them explain over 90 of the SH pressure field’s mean spatial distribution van Loon and Jenne 1972 Trenberth 1980 It has been suggested that the ZW3 crests are generally not covariant in their activity Trenberth and Mo 1985 which raises the question of whether the ZW3 pattern represents a single mode of variability or whether the wave peaks are in fact independent quasistationary features of the SH circulation Hence the major motivation for this research was to ascertain how well the Fourier transform zonal waves actually capture the SH midtroposphere’s variability at monthly and interannual time scalesA feature of the SH circulation that is common to both the PSA and zonal waves discussed above and indeed to the SAM during some seasons is that they all show strong zonally anomalous centers of action in the Pacific sector of the subAntarctic region By considering the variability of quasistationary zonal anomalies directly and individually rather than through largescale decompositions it is hoped that fresh insight will be gained that help to explain the dynamics of the important climate modes that are identified by PC and Fourier analysis This paper presents a statistical analysis characterizing the largescale influence of the subAntarctic quasistationary anticyclones on the SH atmosphere Section 2 outlines the data and the method of analysis in Sect 3 the variability of the subpolar Pacific anticyclones is discussed with reference to their zonal wave representation in Sect 4 the anticyclones are compared with the leading PCs of climate variability the results are summarized in Sect 5The primary dataset used in this analysis is the NCEP/NCAR reanalysis data NRA 500 hPa geopotential height Kalnay et al 1996 Geopotential height at the 500 hPa level 500Z includes many of the patterns of variability that influence SH surface climate and is reasonably independent of the reanalysis model surfaceprocess parameterizations Kalnay et al 1996 Although the aim of reanalysis is a temporally homogeneous dataset the inclusion of satellite data from 1979 onwards is thought to have led to spurious trends in the SH high latitudes eg Marshall 2003 To eliminate these spurious trends this study is limited to postsatellite period of January 1979–December 2007 Additionally remaining linear trends have been removed from the data prior to analysis unless otherwise stated Marshall 2003 and Fogt and Bromwich 2006 suggest that the ECMWF 40year reanalysis ERA40 is a better representation of the high latitude SH climate but ERA40 is only available up to 2001 Uppala et al 2005 To give the longest possible period of analysis with reliable data NRA was chosen as the primary dataset but the results presented here have been compared with those derived from the ERA40 data and are found to be insensitive to the choice of reanalysis

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