Quasi-stationary ENSO wave signals versus the Antarctic Circumpolar Wave scenario

Transcription

1 GEOPHYSICAL RESEARCH LETTERS, VOL. 31, L09315, doi: /2004gl019806, 2004 Quasi-stationary ENSO wave signals versus the Antarctic Circumpolar Wave scenario Young-Hyang Park and Fabien Roquet Département des Milieux et Peuplements Aquatiques, USM402/LODYC, Muséum National d Histoire Naturelle, Paris, France Frédéric Vivier Laboratoire d Océanographie Dynamique et de Climatologie, Université Pierre et Marie Curie, Paris, France Received 24 February 2004; accepted 20 April 2004; published 13 May [1] Two conflicting views on the causal mechanism of the Antarctic interannual variability often appear in the literature, i.e., whether it is remotely teleconnected to tropical ENSO events or is a self-sustained eastward propagating circumpolar wave generated locally by an ocean-atmosphere coupling mechanism. Using a Fourier decomposition into stationary and propagating components of several oceanic and atmospheric variables, we show that most of the Antarctic interannual variability can be explained by a geographically phase-locked standing wave train linked to tropical ENSO episodes. This ENSO-modulated quasi-stationary variability is not zonally uniform, rather, the strongest ENSO impact is consistently concentrated in the Pacific sector of the Southern Ocean. The eastward propagating wave component is found to be not only minor (25% of variability) but also intermittent in phase, yielding little support for the so-called Antarctic Circumpolar Wave scenario. INDEX TERMS: 4215 Oceanography: General: Climate and interannual variability (3309); 4207 Oceanography: General: Arctic and Antarctic oceanography; 4522 Oceanography: Physical: El Nino. Citation: Park, Y.-H., F. Roquet, and F. Vivier (2004), Quasi-stationary ENSO wave signals versus the Antarctic Circumpolar Wave scenario, Geophys. Res. Lett., 31, L09315, doi: /2004gl Introduction [2] The El Niño-Southern Oscillation (ENSO) phenomenon, with a variable period of 2 7 years, results from tight ocean-atmospheric interactions in the tropics, significantly altering the large-scale meridional circulation of the global atmosphere [Bjerkness, 1966]. In recent years, there has been increasing observational evidence that interannual changes in climate and ice cover around Antarctica are strongly linked to tropical ENSO episodes [Simmonds and Jacka, 1995; Ledley and Huang, 1997; Kwok and Comiso, 2002; Renwick, 2002]. However, some other observational studies [e.g., White and Peterson, 1996] noted a coherent, eastward propagating wave in oceanic and atmospheric variables with a circumpolar wavenumber 2 and a dominant periodicity of 4 5 years. This so-called Antarctic Circumpolar Wave (ACW) has been the subject of much debate concerning its generating mechanisms [Qiu and Jin, 1997; White et al., 1998; Colin de Verdière and Blanc, Copyright 2004 by the American Geophysical Union /04/2004GL ], its characteristic or persistence [Bonekamp et al., 1999; Connolley, 2003], and even its very existence [Christoph et al., 1998; Cai et al., 1999; Park, 2001]. One of the most debated points is whether the interannual climate variability around Antarctica is mainly forced by tropical ENSO episodes as proposed by Cai and Baines [2001] or it is a self-sustained circumpolar wave generated within the Southern Ocean by an extratropical ocean-atmosphere coupling mechanism. [3] A simple way to approach this is to quantify the relative importance of the stationary wave component versus eastward propagating wave component of the observed interannual variability, because the former should dominate if the remote quasi-stationary ENSO teleconnection [Renwick and Revell, 1999] is the main mechanism of the Antarctic variability, and vice versa. Here, we propose a method to interpret the Antarctic variability observed during recent decades, in terms of standing and propagating waves. 2. Method and Data [4] Longitude (x)-time (t) variations of a given variable h(x, t) can be expressed as a sum of Fourier harmonics h n,m, h(x, t) = P h n,m, which are composed of westward (W) and eastward (E) propagating, elementary sine and cosine waves, such as: h n;m ¼ C ws sin q w þ C wc cos q w þ C es sin q e þ C ec cos q e where q w = nkx + mwt, q e = nkx mwt are the phase of W-wave and E-wave; k =2p/L, w =2p/T are the angular wavenumber and frequency corresponding to the total record length L in x and T in t; and n and m are the integer wavenumber (0, 1, 2,...) in x and t, respectively. The coefficients C ws (C es ) and C wc (C ec ) are respectively for the sine and cosine component of W-wave (E-wave). These can be easily determined by performing a 2D Fourier analysis of h(x, t) [e.g., Park, 1990]. Equation (1) can be rewritten in the more compact form: h n;m ¼ A w cosðq w j w ÞþA e cosðq e j e Þ ð2þ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi where A w = Cws 2 þ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi C2 wc and A e = Ces 2 þ C2 ec are the amplitude of W-wave and E-wave, respectively; and j w = arctan(c ws /C wc ) and j e = arctan(c es /C ec ) are the corresponding phase lags. ð1þ L of5

2 [5] A standing wave can be defined as the sum of two waves having an equal amplitude but propagating in opposite directions. Using this definition, equation (2) can be rewritten as being composed of a standing wave component and either a W-wave or an E-wave component, depending on the relative magnitude of wave amplitude, as the amplitude of each component should be positive by definition. Therefore, if A w > A e, h n;m ¼ A e cosðq w j w Þþ A e cosðq e j e Þ þ ða w A e Þcosðq w j w Þ ¼ 2A e cos½nkx ðj w þ j e Þ=2Šcos ½mwt ðj w j e Þ=2Š þ ða w A e Þcosðnkx þ mwt j w Þ: ð3þ The first term on the right-hand-side of equation (3) is a standing wave having an amplitude of 2A e, while the second term represents a W-wave with an amplitude of (A w A e ). Similarly, if A e > A w, h n,m is given by 2A w cos½nkx ðj w þ j e Þ=2Šcos ½mwt ðj w j e Þ=2Š þ ða e A w Þcos ðnkx mwt j e Þ: ð4þ In this case, the harmonic h n,m can be considered to be composed of a standing wave having an amplitude 2A w and an E-wave with an amplitude (A e A w ). [6] The reconstruction of a filtered two-dimensional time series can be made by summing harmonics over a desired range of spatial scales (zonal wavenumber n) and time scales (frequency wavenumber m). In order to separate the contribution of the various wave components, the summation is carried out separately for the standing waves, E-waves, and W-waves, according to the component-discrimination formulations (3) and (4). As the Fourier decomposition or reconstruction is a linear operation, the sum of those component waves equals to the total fluctuations within a chosen space-time range. As we are interested in large-scale, interannual variability of an ENSO time scale, only harmonics having a period between 2 and 7 years and a zonal wavenumber less than 4 are retained, although adding several higher wavenumbers does not fundamentally change the results discussed below. [7] The data used consist of a 25-year long series ( ) of gridded (2 2 ) monthly sea surface temperature (SST) data constructed from the Comprehensive Ocean-Atmosphere Data Set (available on Ingrid.ldgo.Columbia.edu), a 9-year long series ( ) of TOPEX/Poseidon satellite altimeter-derived sea surface height (SSH) data and sea level pressure (SLP) data contained in the same altimeter datasets communicated by the AVISO (Archiving, Validation, and Interpretation of Satellite data in Oceanography). Monthly anomalies for each variable are generated by subtracting monthly means computed on the entire record of each dataset, thus eliminating seasonal variations. Anomalies are averaged over boxes with a span of 20 in latitude and of 10 in longitude. These 36 boxes altogether form a circumpolar belt encompassing the Antarctic Circumpolar Current (46 S 66 S). The resulting time series of box-means are low-pass filtered with a cutoff period at 1 year and subsequently resampled at 10-day Figure 1. Longitude-time diagrams of the (a) total, (b) eastward, and (c) stationary SST (in C). The root mean square variability at each longitude is shown in the top panel of each diagram. intervals, which constitute sets of 2D (x t) time series used as input data to our analysis. 3. Results and Discussion [8] The longitude-time diagrams of Figure 1 illustrate the reconstructed, large-scale interannual variations of SST (hereafter, total SST), those from all E-waves (hereafter, eastward SST), and from all standing waves (hereafter, stationary SST). In terms of the relative root mean square variability, the stationary SST represents 65%, while the eastward SST accounts for 25% and the westward SST (not shown) is negligible. Hence, a striking result from this analysis is that most of the non-seasonal SST variability is accounted for by stationary waves rather than eastward propagating waves, consistent with a previous suggestion from altimetry by Park [2001]. Another noticeable feature is that the variability is not uniform along the circumpolar circle. The largest variability is observed in the Pacific sector (centered at 140 W), with a second peak in the western Atlantic sector (centered at 50 W). The eastern Atlantic and western Indian sectors (0 60 E) reveal the least variability in all wave components. This is also in line with a previous remark by Christoph et al. [1998] and Cai and Baines [2001], among others. [9] Although accounting for a minor fraction of variability, one might wonder whether the eastward SST is compatible with the scenario of a self-sustained ACW. To address this question, we examine the continuity of the circumpolar propagation of individual anomaly patterns in a time-longitude plot of the eastward SST (Figure 2). Figure 2 prompts four comments. First, the propagation speed of temperature anomalies is not constant during the 25-year period examined, but varies by a factor of almost two. The propagation speed is slower during the period, with an average speed of 45 per year, while it is 60 and 70 per year before and after that period. Second, previous studies [Bonekamp et al., 1999; 2of5

3 Figure 2. Zoom of the eastward SST shown in Figure 1b, but repeated twice in the zonal direction. Several phase speed lines are superimposed to examine the continuity of the wave propagation. Cai and Baines, 2001; Connolley, 2003] noted that an eastward propagating zonal wavenumber-2 signal is significant only during a limited time period (between 1985 and 1994), and that such propagation is much less evident before and after that period, when a zonal wavenumber-3 pattern is suggested to dominate. Our analysis indicates instead that a mixture of several wavenumbers is critical during any time period to faithfully represent the zonally asymmetric variability. Third, individual anomalies (positive or negative) rarely complete their circumpolar journey, but are instead damped and interrupted at least once by other anomalies of opposite polarity. Finally, a series of positive SST peaks in the central Pacific sector centered at 140 W occur synchronously with major ENSO events (1982/3, 1987/8, 1991/2, 1997/8, 2002), which is also true with the stationary SST (see Figure 1). [10] Evidence of a close link of both the stationary and eastward propagating SST components to ENSO events is given in Figure 3 [see also Renwick, 2002]. Almost every positive and negative peak in the eastward SST at 140 W match those of the much more energetic stationary SST. These peaks mostly coincide with warm and cold phases of ENSO events, with a significant (p < 0.05) correlation of This is consistent with a detailed map of correlation between SST and the Southern Oscillation Index (SOI) in Kwok and Comiso [2002] who showed two centers of action in the South Pacific: a sector of strong negative correlation (peak 0.7) centered between the Ross and western Bellingshausen Seas and a positive correlation (peak 0.5) south of Tasmania (A negative SOI corresponds to a warm phase of ENSO). These two centers are both part of the Pacific South American pattern teleconnected to ENSO [Cai and Baines, Figure 3. Temporal variations at 140 W of the total (black line), stationary (red line), and eastward (blue line) SST. Values are normalized by a standard deviation of the total SST. The Southern Oscillation Index (available on is shown by a microdashed line, but with its sign being reversed and its zero axis being displaced by +2 to better compare with peaks of SST. 2001, Figure 7a], whereby the stationary signals in the Southern Ocean are generated. All of above information clearly suggests that ENSO is a major forcing to the quasi-stationary interannual variability, especially in the Pacific sector of the Southern Ocean, and that only a part of the local ENSO impact propagates eastward but without maintaining its initial state, probably due to a gradual dissipation. Hence, our analysis does not support the scenario of a self-sustained, long-lasting wave encircling Antarctica. [11] Consistent results are obtained with the SSH and SLP data sets, although their short data length ( ) does not permit comparison with different ENSO events other than the 1997/8 ENSO, the strongest event during the 20th century. During this limited time period, the three variables (SST, SSH, SLP) considered here show a similar pattern in their spatio-temporal variations. An example of this is shown in Figure 4 for the temporal variations at 140 W, and in Figure 5 for the zonal variations in mid-june The predominance of the stationary component over the eastward propagating component is verified for all three variables. However, they are Figure 4. Comparison of temporal variations at 140 Wof the normalized SST (solid line), SSH (micro-dashed line), and SLP (dash-dotted line), shown separately according to their (a) total, (b) stationary, and (c) eastward propagating anomalies. 3of5

4 been found to affect significantly the underlying ocean s climate [Cai and Baines, 2001]. This asymmetry in the zonal distribution of atmospheric and oceanic variables of the Southern Ocean, both observed and reproduced in numerical models, is difficult to explain by the passage of an eastward propagating wave persistently encircling Antarctica. Figure 5. Same as Figure 4, but for zonal variations in mid-june not strictly in phase but co-vary within a variable range of time and space lags. Lagged cross-correlations obtained from the entire 2D time series of these variables show that at a given longitude, high SLPs precede high SSTs by 4 months (r = 0.50) and high SSHs trail high SSTs by about 2 months (r = 0.41), while at a given time, high SLPs locate 10 east of high SSTs (r = 0.44) and high SSHs are at the same place as high SSTs (r = 0.38). All these values are significant at the 5% level and represent the overall statistics for the period and over the entire circumpolar circle, although both the time and space lags between variables and their correlation coefficient vary through time and longitude. [12] Note that the zonal phase lag between SLP and SST (10 in longitude) estimated here is only one fourth of a theoretical lag (45 ) required by the ACW scenario put forward by Qiu and Jin [1997] and White et al. [1998]. In fact, for the ACW having a circumpolar wavenumber 2, the latter phase lag is in quadrature between SLP and SST (with high SLP to the east of high SST), which implies, by geostrophy, a poleward (warm) wind anomaly coinciding with a positive SST anomaly. Such a mechanism is regarded by these authors as an atmosphere-ocean positive feedback that would maintain the eastward propagating ACW against dissipation. Here, we observe a similar quadrature phase relation between SLP and SST during the 1997/8 ENSO period, particularly for the dominant stationary component of the anomalies, and in the Pacific sector. This suggests that such a relation is not a sufficient condition for the existence of the ACW. Moreover, our analysis indicates that this relation is not maintained during the whole observational period or over the entire circumpolar circle. [13] As typically shown in Figure 5, we emphasize that all the three variables exhibit a highly non-uniform zonal distribution, with their primary ridge or trough located in the Pacific sector, and a secondary wave train in the other sectors of the Southern Ocean. This is consistent with the fact that the main high latitude impact of ENSO occurs in the Pacific sector, which is also supported by studies of the upper atmosphere. For example, Renwick and Revell [1999] showed from a series of simple numerical experiments that the atmospheric teleconnection of tropical ENSO forcing to the southern high latitudes occurs by an extratropical propagation of Rossby waves generated by ENSO-modulated anomalous convection over the equatorial Pacific. These teleconnected quasi-stationary planetary waves in the upper troposphere, which are strongest across the South Pacific from Australia to southern South America [Renwick and Revell, 1999], have 4. Conclusions [14] Using space-time Fourier decomposition, together with supporting information from the literature, we have shown that most of interannual variations of three climate variables (SST, SSH, SLP) of the Southern Ocean appear as a geographically fixed quasi-stationary wave train, with its modulation being governed by tropical ENSO events, especially in the Pacific sector. This apparent linkage of the Southern Ocean s climate to the tropics suggests that the frequency of occurrence of interannual variability of the Southern Ocean is somewhat predictable [Renwick and Revell, 1999]. This study shows also that the eastward propagating anomalies not only represent a minor fraction (25%) of the large-scale interannual variability of the Southern Ocean but also that they are rapidly dissipated and are unable to complete their circumpolar journey, which contradicts the scenario of a self-sustained Antarctic Circumpolar Wave. [15] Acknowledgments. This work is a contribution (YHP as a Principal Investigator) to the National Aeronautics and Space Administration/Centre National d Etudes Spatiales (NASA/CNES) Joint Research Project for the TOPEX/Poseidon and JASON altimeter missions and has been partially supported by the Programme National d Etudes de la Dynamique du Climat (PNEDC) and the CNES. References Bjerkness, J. (1966), A possible response of the atmospheric Hadley circulation to equatorial anomalies of ocean temperature, Tellus, 18, Bonekamp, H., A. Sterl, and G. J. Komen (1999), Interannual variability in the Southern Ocean from an ocean model forced by European Centre for Medium-Range Weather Forecasts reanalysis fluxes, J. Geophys. Res., 104, 13,317 13,331. Cai, W., and P. G. Baines (2001), Forcing of the Antarctic Circumpolar Wave by El Niño-Southern Oscillation teleconnections, J. Geophys. Res., 106, Cai, W., P. G. Baines, and H. B. Gordon (1999), Southern mid- to highlatitude variability, a zonal wavenumber-3 pattern, and the Antarctic Circumpolar Wave in the CSIRO coupled model, J. Clim., 12, Christoph, M., T. P. Barnett, and E. Roekner (1998), The Antarctic Circumpolar Wave in a coupled ocean-atmosphere GCM, J. Clim., 11, Colin de Verdière, A., and M. L. Blanc (2001), Thermal resonance of the atmosphere to SST anomalies: Implications for the Antarctic Circumpolar Wave, Tellus, Ser. A, 53, Connolley, W. M. (2003), Long-term variation of the Antarctic Circumpolar Wave, J. Geophys. Res., 108(C4), 8076, doi: /2000jc Kwok, R., and J. C. Comiso (2002), Southern Ocean climate and sea ice anomalies associated with the Southern Oscillation, J. Clim., 15, Ledley, T. S., and Z. Huang (1997), A possible ENSO signal in the Ross Sea, Geophys. Res. Lett., 24, Park, Y.-H. (1990), Mise en évidence d ondes planétaires semi-annuelles baroclines au sud de l Océan Indien par altimètre satellitaire, C. R. Acad. Sci. Paris, 310(II), Park, Y.-H. (2001), Interannual sea level variability in the Southern Ocean within the context of global climate change, AVISO Newsl., 8, Qiu, B., and F.-F. Jin (1997), Antarctic Circumpolar Waves: An indication of ocean-atmospheric coupling in the extratropics, Geophys. Res. Lett., 24, of5

5 Renwick, J. A. (2002), Southern Hemisphere circulation and relations with sea ice and sea surface temperature, J. Clim., 15, Renwick, J. A., and M. J. Revell (1999), Blocking over the South Pacific and Rossby wave propagation, Mon. Weather Rev., 127, Simmonds, I., and T. H. Jacka (1995), Relationship between the interannual variability of Antarctic sea ice and Southern Oscillation, J. Clim., 8, White, W. B., and R. G. Peterson (1996), An Antarctic Circumpolar Wave in surface pressure, wind, temperature and sea-ice extent, Nature, 380, White, W. B., S.-C. Chen, and R. G. Peterson (1998), The Antarctic Circumpolar Wave: A beta effect in ocean-atmosphere coupling over the Southern Ocean, J. Phys. Oceanogr., 28, Y.-H. Park and F. Roquet, Département des Milieux et Peuplements Aquatiques, USM402/LODYC, Muséum National d Histoire Naturelle, 43 rue Cuvier, F Paris, France. (yhpark@mnhn.fr) F. Vivier, Laboratoire d Océanographie Dynamique et de Climatologie, Université Pierre et Marie Curie, Tour 15, Etage 2, Boite 100, 4 Place Jussieu, F Paris cedex 05, France. 5of5