Atmospheric circulation changes over the 21st century

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This page is part of the topic Atmospheric change over the next 100 years

The atmospheric circulation over Antarctica and the Southern Ocean is critical for the future evolution of global climate in a number of ways. Perhaps most important is the role of circulation in defining accumulation over the Antarctic ice sheet. Other aspects of importance include the role of circulation in the warming of the Antarctic Peninsula, the distribution of sea ice, and the seasonal to interannual variability of the Southern Hemisphere.

The role of modes of circulation variability

Mean sea level pressure changes associated with the long-term variability of circulation of the Southern Hemisphere have been reported for many decades (e.g. van Loon, 1967[1]; Hurrell and van Loon, 1994[2]). More recently, analyses of sea level pressure have revealed secular decreases over the Antarctic, associated with increases in mid-latitude westerlies, a poleward displacement of the polar front jet stream, and a more zonal circulation. The robustness of these observed changes is open to question, given that spurious trends are evident in reanalysis products (Bromwich et al., 2007[3]). Further, there are significant differences between the ERA-40 and NRA re-analyses in the Southern Hemisphere, in which the ERA-40 has a tendency towards more intense cyclones in all seasons (Wang et al., 2006[4]). Nevertheless, tendencies consistent with these changes in circulation have been demonstrated in station-based data and climate model realizations of the Twentieth and Twenty First Centuries.

Given the large inter-annual variability of the high southern latitudes, secular trends must be put in the context of responses to changes in the modes of variability that are dominant in the region, namely the El Niño Southern Oscillation (ENSO) and the Southern Annular Mode (SAM) (Turner, 2004[5]; Sen Gupta and England, 2007[6]). The long-term changes forced by increases of GHG concentrations have been found to possess a similar spatial pattern to the observed short-term (month to month) variability (Brandefelt and Källén, 2004[7]). Of less significance, due largely to its contested nature (Park Y. et al., 2004), is the Antarctic Circumpolar Wave (ACW) (White and Peterson, 1996[8]), a postulated pattern of variability with an approximately four-year period characterised by the eastward propagation of anomalies in sea ice extent.

The Southern Oscillation Index has a negative trend over recent decades, corresponding to a tendency towards more frequent El Niño conditions in the equatorial Pacific. This trend is associated with negative sea ice cover anomalies in the Ross and Amundsen Sea and positive sea ice anomalies in the Bellingshausen and Weddell Seas (Kwok and Comiso, 2002[9]).

The SAM index has a positive trend over recent decades during the summer and winter, which reflects trends in the zonally averaged mid-latitude westerlies. The increases in the SAM index are associated with strong warming on the eastern side of the Antarctic Peninsula and low pressure west of the Peninsula (Orr et al., 2004[10]; Lefebvre et al., 2004[11]) – this reflects increased poleward flow, resulting in both the eastern Peninsula warming and reduced sea ice in the region (Liu et al., 2004[12]). The SAM index trends are also related to the observed and projected (in the near term) East Antarctic surface cooling (Shindell and Schmidt, 2004[13]; Marshall, 2007[14]). However, changes in the SAM are not thought to be responsible for the large winter season warming on the western side of the Antarctic Peninsula.

Progress in simulating ENSO variability has led to significant improvements in representing the spatial pattern of sea surface temperatures in the equatorial Pacific (Randall et al., 2007[15]). Uncoupled models have demonstrated similar ENSO variability to that observed (e.g. Marshall et al., 2007[16]). However, serious discrepancies remain in the attempts of coupled models to represent the ENSO (Joseph and Nigam, 2006[17]). Atmosphere-ocean interaction leads to inaccuracies in the sea surface temperature and in the structure of the thermocline (Cai et al., 2003[18]; Davey et al., 2002[19]). Furthermore, the timescale of variability in the coupled system is generally too short (van Oldenborgh et al., 2005[20]), although in some models a peak at around 7 years is observed (Marshall et al., 2007[16]). The interaction between climate change and ENSO variability is also subject to substantial uncertainty, with no coupled model consensus on the likelihood of a relationship between more frequent El Niño conditions and increasing GHG concentrations (van Oldenborgh et al., 2005[20]; Collins et al., 2005[21]; Wang, 2007[22]).

Model outputs submitted to the IPCC AR4 simulate the SAM with a high degree of accuracy (e.g., Miller et al., 2006[23]), generally with spatial correlations greater than 0.95 (Randall et al., 2007[15]). The SAM signature in the surface warming anomaly over the Antarctic Peninsula is also captured by some models (e.g. Delworth et al., 2006[24]). Other features, including the zonal structure and the temporal signal, exhibit large variance between outputs even in a single model (Miller et al., 2006[23]; Raphael and Holland, 2006[25]). Hence, the extent of discrepancies in the simulated SAM due to model shortcomings alone is difficult to gauge. As an added complexity, new evidence has emerged that ENSO variability can influence SAM variability in the southern summer (L’Heureux and Thompson, 2006[26]).

Projected changes in modes of circulation variability

5.4 Base state change in average tropical Pacific SSTs and change in El Niño variability simulated by AOGCMs. The base state change (horizontal axis) is denoted by the spatial anomaly pattern correlation coefficient between the linear trend of SST in the 1%/yr CO2 increase climate change experiment and the first Empirical Orthogonal Function (EOF) of SST in the control experiment over the area 10ºS to 10ºN, 120ºE to 80ºW (reproduced from Yamaguchi and Noda, 2006[27]). The change in El Niño variability (vertical axis) is denoted by the ratio of the standard deviation of the first EOF of sea level pressure (SLP) between the current climate and the last 50 years of the IPCC A2 experiments (2051–2100), in the region 30ºS to 30ºN, 30ºE to 60ºW (reproduced from van Oldenborgh et al., 2005[20]). Error bars indicate the 95% confidence interval; from IPCC (2007[28]).

In the range of studies reported by the IPCC’s AR4, it has been demonstrated that the ENSO response of climate system models in the Twenty First Century is highly model dependent (see Figure 5.4; (Meehl et al., 2007[29]). This outcome has changed little in the most recent analyses (e.g. Yeh and Kirtman, 2007[30]), and represents a major challenge in projecting Antarctic variability. Currently, there is some consensus that there will be little change in the magnitude of ENSO variability in the Twenty First Century, although some of the models that simulated Twentieth Century ENSO variability well do indicate Twenty First Century increases in the amplitude of El Niño events (Meehl et al., 2007[29]). If such a trend is manifest, it would contribute to changes in sea ice cover and circulation over Antarctica of a similar sense to those observed in the last few decades, but the reliability of such a projection is confounded by the apparent decadal variability in the system (e.g. Fogt and Bromwich, 2006[31]).

5.5 Multi-model mean of the regression of the leading EOF of ensemble mean Southern Hemisphere sea level pressure. The time series of regression coefficients has zero mean between year 1900 and 1970. The thick red line is a 10-year low-pass filtered version of the mean with ozone forcing; the blue line is without ozone forcing. The grey shading represents the inter-model spread at the 95% confidence level and is filtered. A filtered version of the observed SLP from the Hadley Centre (HadSLP1) is shown in black. Adapted from (Miller et al., 2006[23]). From IPCC (2007[28]).

The future trend in the SAM, as characterized by the leading Empirical Orthogonal Function (EOF) of sea level pressure, has been reported from a number of model projections (e.g. GISSII - Shindell and Schmidt, 2004[13]; CCSM - Arblaster and Meehl, 2006[32]). Most models support a continuing positive trend in the SAM index, as manifest by a strong intensification of the polar vortex. The observed SAM index trend has been related to stratospheric ozone depletion (Sexton, 2001[33]) and to greenhouse gas increases (Hartmann et al., 2000[34]). Specifically, a larger positive trend was projected during the late Twentieth Century by models that included stratospheric ozone changes (e.g. Cai and Cowan, 2007[35]; see Figure 5.5). Further evidence for this relationship is found in the fact that the signal is largest in the lower stratosphere in austral spring through summer (Arblaster and Meehl, 2006[32]). Though somewhat uncertain, it is expected that ozone will continue to slow its decline in the Twenty First Century, as has been observed since 1997 (Yang et al., 2006[36]). Hence, in future projections, the SAM index trends for simulations with and without ozone are comparable. However, the increase in greenhouse gases is also an important factor that supports a continued increase in the SAM index on an annual basis, forced by trends in the meridional temperature gradient (Brandefelt and Källén, 2004[7]). Like the uncertainties surrounding the sources of model error in simulating the SAM in the Twentieth Century, the confounding element of future trajectories in stratospheric ozone concentration makes precise projection of the SAM more problematic than other elements of Antarctic climate; nevertheless the general trend is clear.

Impacts on synoptic climate

Observed changes in weather systems are consistent with the trends in the dominant modes of variability, although these results too are strongly dependent on the quality of reanalysis products. In the Southern Hemisphere, cyclonic activity is strikingly different between the ERA-40 and NRA re-analyses (Bromwich et al., 2007[3]). Nevertheless, consistent signals include a decrease in the frequency and increases in the size and intensity of extratropical cyclones in recent decades (e.g. Simmonds and Keay, 2000[37]) with a moderate increase in frequency over the Southern Ocean (e.g. Fyfe, 2003[38]).

A consistent result that has emerged recently from Twenty First Century projections is a tendency for a poleward shift of several degrees latitude in mid-latitude storm tracks (e.g. Fischer-Bruns et al., 2005[39]; Bengtsson et al., 2006[40]). Consistent with these shifts, Lynch et al. (2006[41]) demonstrated increasing cyclonicity and stronger westerlies in high southern latitudes in a 10-member multi-model ensemble simulation of the Twenty First Century. One study (Fyfe, 2003[38]) has suggested a reduction in sub-Antarctic cyclones of more than 30% by the end of the century. Fyfe (2003[38]) did not definitively identify a poleward shift of storm tracks, but the relatively coarse grid of the CCCma climate model (T32, or approximately 600 km grid spacing) may not have been able to detect such a shift. These changes have been related to a simulated circumpolar signal of increased precipitation off the coast of Antarctica (Lynch et al., 2006[41]; see also Precipitation changes over the 21st century), which perhaps, though loosely, argues against the frequency trend being related to increased data availability, as suggested by Hines et al. (2000[42]).

Impacts on accumulation

The Antarctic ice sheet constitutes the largest reservoir of freshwater on Earth, representing tens of metres of sea-level rise if it were to melt completely. Hence, the mass balance of the Antarctic ice sheet is an important contributor to the impacts of sea-level change over the next century. The circulation provides an important component of forcing, particularly through precipitation. The relationships between the major modes of variability and precipitation over the Antarctic continent have been studied, but while there seems to be a correlation between increased coastal precipitation and the SAM index (within the limits of the data), Noone and Simmonds (2002[43]) have demonstrated that, in at least one climate model, eddy moisture convergence (i.e. associated with depressions) represents a large fraction of net precipitation. Synoptic activity intensification over the Southern Ocean would suggest a potential for increase in accumulation along the coasts (Sinclair et al., 1997[44]). However, significant correlations with the SOI appear to be intermittent (e.g. Bromwich et al., 2000[45]; Genthon and Cosme, 2003[46]). More recently, a nonlinear interaction between the Southern Oscillation and the SAM that varies on decadal time scales has been identified as a possible reason for this irregularity (Fogt and Bromwich, 2006[31]).


  1. Van Loon, H. 1967. The half yearly oscillations in middle and high southern latitudes and the coreless winter, J. Atmos. Sci., 24, 472-486.
  2. Hurrell, J.W. and Van Loon, H. 1994. A Modulation of the Atmospheric Annual Cycle in the Southern Hemisphere, Tellus, 46A, 325-338.
  3. 3.0 3.1 Bromwich, D.H., Fogt, R.L., Hodges, K.I. and Walsh, J.E. 2007. A tropospheric assessment of the ERA-40, NCEP, and JRA-25 global reanalyses in the polar regions, J. Geophys. Res., 112, Art. No. D10111.
  4. Wang, X.L., Swail, V.R. and Zwiers, F.W. 2006. Climatology and changes of extratropical storm tracks and cyclone activity: Comparison of ERA-40 with NCEP/NCAR Reanalysis for 1958-2001, J. Climate, 19, 3145−3166.
  5. Turner, J. 2004. The El Niño-Southern Oscillation and Antarctica, International Journal of climatology, 24, 1-31.
  6. Sen Gupta, A. and England, M.H. 2007. Coupled ocean-atmosphere feedback in the Southern Annular Mode, J. Climate, 20, 3677-3692.
  7. 7.0 7.1 Brandefelt, J. and Källén, E. 2004: The response of the Southern Hemisphere atmospheric circulation to an enhanced greenhouse gas forcing, J. Climate, 17, 4425-4442.
  8. White, W.B. and Peterson, R. 1996. An Antarctic Circumpolar Wave in surface pressure, wind, temperature, and sea ice extent, Nature, 380, 699-702.
  9. Kwok, R. and Comiso, J.C. 2002. Southern ocean climate and sea ice anomalies associated with the Southern Oscillation, J. Climate, 15, 487-501.
  10. Orr, A., Cresswell, D., Marshall, G.J., Hunt, J.C.R., Sommeria, J., Wang, C.G. and Light, M. 2004. A ‘low-level’ explanation for the recent large warming trend over the western Antarctic Peninsula involving blocked winds and changes in zonal circulation, Geophys. Res. Lett., 31, L06204, doi:10.1029/2003GL019160.
  11. Lefebvre, W., Goosse, H., Timmermann, R. and Fichefet, T. 2004. Influence of the Southern Annular Mode on the sea ice-ocean system, J. Geophys. Res., 109, C09005, doi:10.1029/2004JC002403.
  12. Liu, J., Curry, J.A. and Martinson, D.G. 2004. Interpretation of recent Antarctic sea ice variability, Geophys. Res. Lett., 31, L02205, doi:10.1029/2003GL018732.
  13. 13.0 13.1 Shindell, D.T. and Schmidt, G.A. 2004. Southern hemisphere climate response to ozone changes and greenhouse gas increases, Geophys. Res. Lett., 31, L18209, doi:10.1029/2004GL020724.
  14. Marshall, G.J. 2007. Half-century seasonal relationships between the Southern Annular Mode and Antarctic temperatures, Int. J. Climatol., 27, 373-383.
  15. 15.0 15.1 Randall, D.A., Wood, R.A., Bony, S., Colman, R., Fichefet, T., Fyfe, J., Kattsov, V., Pitman, A., Shukla, J., Srinivasan, J., Stouffer, R.J., Sumi, A. and Taylor, K.E. 2007. Climate Models and Their Evaluation. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
  16. 16.0 16.1 Marshall, D. P. and Naveira Garabato A. C. 2007. A conjecture on the role of bottom-enhanced diapycnal mixing in the parameterization of geostrophic eddies, J. Phys. Oceanogr., in press.
  17. Joseph, R. and Nigam, S. 2006. ENSO evolution and teleconnections in IPCC's twentieth-century climate simulations: Realistic representation?, J. Climate, 19, 4360-4377.
  18. Cai, W., Whetton, P.H. and Karoly, D.J. 2003. The response of the Antarctic Oscillation to increasing and stabilized atmospheric CO2, J. Climate, 16, 1525-1538.
  19. Davey, M.K., Huddleston, M., Sperber, K., Braconnot, P., Bryan, F., Chen, D., Colman, R., Cooper, C., Cubasch, U., Delecluse, P., Dewitt, D., Fairhead, L., Flato, G., Gordon, C., Hogan, T., Ji, M., Kimoto, M., Kitoh, A., Knutson, T., Latif, M., Le Treut, H., Li, T., Manabe, S., Mechoso, C., Meehl, G., Power, S., Roeckner, E., Terray, L., Vintzileos, A., Voss, R., Wang, B., Washington, W., Yoshikawa, I., Yu, J., Yukimoto, S. and Zebiak, S. 2002. STOIC: A study of coupled model climatology and variability in tropical ocean regions, Clim. Dyn., 18, 403-420.
  20. 20.0 20.1 20.2 Van Oldenborgh, G.J., Philip, S.Y. and Collins, M. 2005. El Nino in a changing climate: a multi-model study, Ocean Sci., 1, 81-95.
  21. Collins, M. and The CMIP Modelling Groups. 2005. El Niño- or La Niña-like climate change? Climate Dynamics, 24, 89-104.
  22. Wang, F.M. 2007. Investigating ENSO sensitivity to mean climate in an intermediate model using a novel statistical technique, Geophys. Res. Lett., 34, L07705.
  23. 23.0 23.1 23.2 Miller, R.L., Schmidt, G.A. and Shindell, D.T. 2006. Forced annular variations in the 20th century Intergovernmental Panel on Climate Change Fourth Assessment Report models, J. Geophys. Res., 111, doi:10.1029/2005JD006323.
  24. Delworth, T.L., Broccoli, A.J. , Rosati, A., Stouffer, R.J., Balaji, V., Beesley, J.A., Cooke, W.F., Dixon, K.W., Dunne, J., Dunne, K.A., Durachta, J.W., Findell, K.L., Ginoux, P., Gnanadesikan, A., Gordon, C.T., Griffies, S.M., Gudgel, R., Harrison, M.J., Held, I.M., Hemler, R.S., Horowitz, L.W., Klein, S.A., Knutson, T.R., Kushner, P.J., Langenhorst, A.R., Lee, H.C., Lin, S.J., Lu, J., Malyshev, S.L., Milly, P.C.D., Ramaswamy, V., Russell, J., Schwarzkopf, M.D., Shevliakova, E., Sirutis, J.J., Spelman, M.J., Stern, W.F., Winton, M., Wittenberg, A.T., Wyman, B., Zeng, F. and Zhang, R. 2006. GFDL's CM2 Global Coupled Climate Models. Part I: Formulation and Simulation Characteristics, J. Climate, 19, 643-674.
  25. Raphael, M.N. and Holland, M.M. 2006. Twentieth century simulation of the Southern Hemisphere climate in coupled models. Part 1: Large scale circulation variability, Clim. Dyn., 26, 217-228, doi:10.1007/s00382-005-0082-8.
  26. L’Heureux, M.L. and Thompson, D.W.J. 2006. Observed relationships between the El-Niño/Southern Oscillation and the extratropical zonal mean circulation, J. Climate, 19, 276-287.
  27. Yamaguchi, K. and Noda, A. 2006. Global Warming Patterns over the North Pacific: ENSO versus AO, J. Meteor. Soc. Japan, 84, 221-241.
  28. 28.0 28.1 IPCC 2007. Climate Change 2007: The Physical Science Basis. Contribution of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge.
  29. 29.0 29.1 Meehl, G.A., T.F. Stocker, W.D. Collins, P. Friedlingstein, A.T. Gaye, J.M. Gregory, A. Kitoh, R. Knutti, J.M. Murphy, A. Noda, S.C.B. Raper, I.G. Watterson, A.J. Weaver, and Z.-C. Zhao, 2007: Global Climate Projections. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 749-845.
  30. Yeh, S.-W. and Kirtman, B.P. 2007. ENSO amplitude changes due to climate change projections in different coupled models, J. Climate, 20, 203-217.
  31. 31.0 31.1 Fogt, R.L. and Bromwich, D.H. 2006. Decadal Variability of the ENSO Teleconnection to the High-Latitude South Pacific Governed by Coupling with the Southern Annular Mode, J. Climate, 19, 979-997.
  32. 32.0 32.1 Arblaster, J.M. and Meehl G.A. 2006. Contributions of external forcings to Southern Annual Mode trends, Journal of Climate, 19, 2896-2905.
  33. Sexton, D.M.H. 2001. The effect of stratospheric ozone depletion on the phase of the Antarctic Oscillation, Geophys. Res. Lett., 28, 3697-3700.
  34. Hartmann, D.L., Wallace, J.M., Limpasuvan, V., Thompson, D.W.J. and Holton, J.R. 2000. Can ozone depletion and global warming interact to produce rapid climate change?, Proc. Natl. Acad. Sci. U.S.A., 97, 1412-1417.
  35. Cai, W.J. and Cowan, T. 2007. Trends in Southern Hemisphere circulation in IPCC AR4 models over 1950-99: Ozone depletion versus greenhouse forcing, J. Climate, 20, 681-693.
  36. Yang, E.-S., Cunnold, D.M., Salawitch, R.J., McCormick, M.P., Russell III, J., Zawodny, J.M., Oltmans, S., and Newchurch, M.J. 2006. Attribution of recovery in lower-stratospheric ozone, J. Geophys. Res., 111, D17309, doi:10.1029/2005JD006371.
  37. Simmonds, I. and Keay, K. 2000. Variability of Southern Hemisphere extratropical cyclone behaviour, 1958-97, J. Climate, 13(3), 550-561.
  38. 38.0 38.1 38.2 Fyfe, J.C. 2003. Extratropical southern hemisphere cyclones: Harbingers of climate change? J. Climate, 16, 2802-2805.
  39. Fischer-Bruns, I., Von Storch, H., Gonzalez-Rouco, J.F. and Zorita, E. 2005. Modelling the variability of midlatitude storm activity on decadal to century time scales, Clim. Dyn., 25, 461-476.
  40. Bengtsson, L., Hodges, K. and Roeckner, E. 2006. Storm tracks and climate change, J. Climate, 19, 3518-3543.
  41. 41.0 41.1 Lynch, A., Uotila, P. and Cassano, J.J. 2006. Changes in synoptic weather patterns in the polar regions in the twentieth and twenty-first centuries, Part 2: Antarctic, Int. J. Climatol., 26, 1181-1199.
  42. Hines K.M., Bromwich, D.H. and Marshall, G.J. 2000. Artificial surface pressure trends in the NCEP–NCAR reanalysis over the Southern Ocean and Antarctica, J. Climate, 13, 3940-3952.
  43. Noone, D. and Simmonds, I. 2002. Annular variations in moisture transport mechanisms and the abundance of delta18O in Antarctic snow, J. Geophys. Res., 107, 4742, doi:10.1029/2002JD002262.
  44. Sinclair, M.R., Renwick, J.A. and Kidson, J.W. 1997. Low-frequency variability of Southern Hemisphere sea level pressure and weather system activity, Mon. Weather Rev., 125, 2531-2543.
  45. Bromwich, D.H., Rogers, A.N., Kallberg, P., Cullather, R.I., White, J.W.C. and Kreutz, K.J. 2000. ECMWF analyses and reanalyses depiction of ENSO signal in Antarctic precipitation, J. Climate, 13, 1406-1420.
  46. Genthon, C. and Cosme, E. 2003. Intermittent signature of ENSO in west-Antarctic precipitation, Geophys. Res. Lett., 30, 2081, doi:10.1029/2003GL018280.