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Zonal wave 3 pattern in the Southern Hemisphere generated by tropical convection

Abstract

A distinctive feature of the Southern Hemisphere extratropical atmospheric circulation is the quasi-stationary zonal wave 3 pattern. This pattern is present in both the mean atmospheric circulation and its variability on daily, seasonal and interannual timescales. While the zonal wave 3 pattern has substantial impacts on meridional heat transport and Antarctic sea ice extent, the reason for its existence remains uncertain, although it has long been assumed to be linked to the presence of three major landmasses in the Southern Hemisphere extratropics. Here we use an atmospheric general circulation model to show that the stationary zonal wave 3 pattern is instead driven by zonally asymmetric deep convection in the tropics, with little influence from extratropical orography or landmasses. Localized regions of deep convection in the tropics form a local Hadley cell, which in turn creates a wave source in the subtropics that excites a poleward- and eastward-propagating wave train, forming quasi-stationary waves in the Southern Hemisphere high latitudes. Our findings suggest that changes in tropical deep convection, either due to natural variability or climate change, fundamentally control the zonal wave 3 pattern, with implications for southern high-latitude climate, ocean circulation and sea ice.

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Fig. 1: Sea level pressure variability and projected 21st century change in the SH extratropics.
Fig. 2: ZW3 amplitude and phase in model simulations with different land–sea configurations.
Fig. 3: Vertical velocity, perturbation vorticity and geopotential height (corresponding to zonal wavenumber 3) for the tropical South America simulation.
Fig. 4: Schematic summarizing the role of tropical convection in generating ZW3 in the SH extratropics.

Data availability

ERA-Interim data used in the study can be downloaded from https://apps.ecmwf.int/datasets/data/interim-full-moda/levtype=sfc/. Data from CESM coupled model simulations can be downloaded from https://www.cesm.ucar.edu/models/ccsm4.0/model_esg/. Data generated from the atmospheric general circulation model simulations can be downloaded from ref. 48.

Code availability

Python scripts used for the analysis described in this study can be obtained from the corresponding author on reasonable request.

References

  1. 1.

    Raphael, M. N. The influence of atmospheric zonal wave three on Antarctic sea ice variability. J. Geophys. Res. 112, D12112 (2007).

    Article  Google Scholar 

  2. 2.

    Raphael, M. N. & Hobbs, W. The influence of the large-scale atmospheric circulation on Antarctic sea ice during ice advance and retreat seasons. Geophys. Res. Lett. 41, 5037–5045 (2014).

    Article  Google Scholar 

  3. 3.

    Raphael, M. N. A zonal wave 3 index for the Southern Hemisphere. Geophys. Res. Lett. 31, L23212 (2004).

    Article  Google Scholar 

  4. 4.

    Keppler, L. & Landschützer, P. Regional wind variability modulates the Southern Ocean carbon sink. Sci. Rep. 9, 7384 (2019).

    Article  Google Scholar 

  5. 5.

    Renwick, J. A. Persistent positive anomalies in the Southern Hemisphere circulation. Mon. Weather Rev. 133, 977–988 (2005).

    Article  Google Scholar 

  6. 6.

    Turner, J., Hosking, J. S., Bracegirdle, T. J., Phillips, T. & Marshall, G. J. Variability and trends in the Southern Hemisphere high latitude, quasi-stationary planetary waves. Int. J. Climatol. 37, 2325–2336 (2017).

    Article  Google Scholar 

  7. 7.

    van Loon, H. & Jenne, R. L. The zonal harmonic standing waves in the southern hemisphere. J. Geophys. Res. 77, 992–1003 (1972).

    Article  Google Scholar 

  8. 8.

    Lejenas, H. Southern Hemisphere planetary-scale waves and blocking. J. Meteorol. Soc. Jpn Ser. II 66, 777–781 (1988).

    Article  Google Scholar 

  9. 9.

    Raphael, M. N. Quasi-stationary waves in the Southern Hemisphere: an examination of their simulation by the NCAR Climate System Model, with and without an interactive ocean. J. Clim. 11, 1405–1418 (1998).

    Article  Google Scholar 

  10. 10.

    Yuan, X. & Li, C. Climate modes in southern high latitudes and their impacts on Antarctic sea ice. J. Geophys. Res. 113, C06S91 (2008).

    Google Scholar 

  11. 11.

    Teng, H. & Branstator, G. A zonal wavenumber 3 pattern of Northern Hemisphere wintertime planetary wave variability at high latitudes. J. Clim. 25, 6756–6769 (2012).

    Article  Google Scholar 

  12. 12.

    Hoskins, B. J. & Karoly, D. J. The steady linear response of a spherical atmosphere to thermal and orographic forcing. J. Atmos. Sci. 38, 1179–1196 (1981).

    Article  Google Scholar 

  13. 13.

    Trenberth, K. E. et al. Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J. Geophys. Res. Ocean. 103, 14291–14324 (1998).

    Article  Google Scholar 

  14. 14.

    Inatsu, M. & Hoskins, B. J. The zonal asymmetry of the Southern Hemisphere winter storm track. J. Clim. 17, 4882–4892 (2004).

    Article  Google Scholar 

  15. 15.

    Quintanar, A. I. & Mechoso, C. R. Quasi-stationary waves in the Southern Hemisphere. Part II: generation mechanisms. J. Clim. 8, 2673–2690 (1995).

    Article  Google Scholar 

  16. 16.

    Peña-Ortiz, C., Manzini, E. & Giorgetta, M. A. Tropical deep convection impact on southern winter stationary waves and its modulation by the quasi-biennial oscillation. J. Clim. 32, 7453–7467 (2019).

    Article  Google Scholar 

  17. 17.

    James, I. N. On the forcing of planetary-scale Rossby waves by Antarctica. Q. J. R. Meteorol. Soc. 114, 619–637 (1988).

    Article  Google Scholar 

  18. 18.

    Watterson, I. G. & James, I. N. Baroclinic waves propagating from a high-latitude source. Q. J. R. Meteorol. Soc. 118, 23–50 (1992).

    Article  Google Scholar 

  19. 19.

    Mo, K. C. & Ghil, M. Statistics and dynamics of persistent anomalies. J. Atmos. Sci. 44, 877–902 (1987).

    Article  Google Scholar 

  20. 20.

    Hansen, A. R. & Sutera, A. Planetary-scale flow regimes in midlatitudes of the southern hemisphere. J. Atmos. Sci. 48, 952–964 (1991).

    Article  Google Scholar 

  21. 21.

    Mo, K. C. & White, G. H. Teleconnections in the Southern Hemisphere. Mon. Weather Rev. 113, 22–37 (1985).

    Article  Google Scholar 

  22. 22.

    Trenberth, K. E. Planetary waves at 500 mb in the Southern Hemisphere. Mon. Weather Rev. 108, 1378–1389 (1980).

    Article  Google Scholar 

  23. 23.

    Irving, D. & Simmonds, I. A novel approach to diagnosing Southern Hemisphere planetary wave activity and its influence on regional climate variability. J. Clim. 28, 9041–9057 (2015).

    Article  Google Scholar 

  24. 24.

    Trenberth, K. F. & Mo, K. C. Blocking in the Southern Hemisphere. Mon. Weather Rev. 113, 3–21 (1985).

    Article  Google Scholar 

  25. 25.

    Mo, K. C. Quasi-stationary states in the Southern Hemisphere. Mon. Weather Rev. 114, 808–823 (1986).

    Article  Google Scholar 

  26. 26.

    Wang, G. et al. Compounding tropical and stratospheric forcing of the record low Antarctic sea-ice in 2016. Nat. Commun. 10, 13 (2019).

    Article  Google Scholar 

  27. 27.

    Purich, A. & England, M. H. Tropical teleconnections to Antarctic sea ice during austral spring 2016 in coupled pacemaker experiments. Geophys. Res. Lett. 46, 6848–6858 (2019).

    Article  Google Scholar 

  28. 28.

    Meehl, G. A. et al. Sustained ocean changes contributed to sudden Antarctic sea ice retreat in late 2016. Nat. Commun. 10, 14 (2019).

    Article  Google Scholar 

  29. 29.

    Hobbs, W. R. & Raphael, M. N. Characterizing the zonally asymmetric component of the SH circulation. Clim. Dyn. 35, 859–873 (2010).

    Article  Google Scholar 

  30. 30.

    Dee, D. P. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597 (2011).

    Article  Google Scholar 

  31. 31.

    Hendon, H. H. & Hartmann, D. L. Variability in a nonlinear model of the atmosphere with zonally symmetric forcing. J. Atmos. Sci. 42, 2783–2797 (1985).

    Article  Google Scholar 

  32. 32.

    Robinson, W. The dynamics of the zonal index in a simple model of the atmosphere. Tellus A 43, 295–305 (1991).

    Article  Google Scholar 

  33. 33.

    Watanabe, M. On the presence of annular variability in an aquaplanet model. Geophys. Res. Lett. 32, L05701 (2005).

    Google Scholar 

  34. 34.

    Zappa, G., Lucarini, V. & Navarra, A. Baroclinic stationary waves in aquaplanet models. J. Atmos. Sci. 68, 1023–1040 (2011).

    Article  Google Scholar 

  35. 35.

    Held, I. M., Ting, M. & Wang, H. Northern winter stationary waves: theory and modeling. J. Clim. 15, 2125–2144 (2002).

    Article  Google Scholar 

  36. 36.

    Garfinkel, C. I., White, I., Gerber, E. P. & Jucker, M. The impact of SST biases in the tropical East Pacific and Agulhas Current region on atmospheric stationary waves in the Southern Hemisphere. J. Clim. 33, 9351–9374 (2020).

    Article  Google Scholar 

  37. 37.

    Baines, P. G. & Fraedrich, K. Topographic effects on the mean tropospheric flow patterns around Antarctica. J. Atmos. Sci. 46, 3401–3415 (1989).

    Article  Google Scholar 

  38. 38.

    Gill, A. E. Some simple solutions for heat-induced tropical circulation. Q. J. R. Meteorol. Soc. 106, 447–462 (1980).

    Article  Google Scholar 

  39. 39.

    Wills, R. C. J., White, R. H. & Levine, X. J. Northern Hemisphere stationary waves in a changing climate. Curr. Clim. Chang. Rep. 5, 372–389 (2019).

    Article  Google Scholar 

  40. 40.

    Held, I. M. The vertical scale of an unstable baroclinic wave and its importance for eddy heat flux parameterizations. J. Atmos. Sci. 35, 572–576 (1978).

    Article  Google Scholar 

  41. 41.

    Müller, W. A. & Roeckner, E. ENSO teleconnections in projections of future climate in ECHAM5/MPI-OM. Clim. Dyn. 31, 533–549 (2008).

    Article  Google Scholar 

  42. 42.

    Goyal, R., Sen Gupta, A., Jucker, M. & England, M. H. Historical and projected changes in the Southern Hemisphere surface westerlies. Geophys. Res. Lett. 48, e2020GL090849 (2021).

    Google Scholar 

  43. 43.

    Kent, C., Chadwick, R. & Rowell, D. P. Understanding uncertainties in future projections of seasonal tropical precipitation. J. Clim. 28, 4390–4413 (2015).

    Article  Google Scholar 

  44. 44.

    Neale, R. B. et al. Description of the NCAR Community Atmosphere Model (CAM 4.0) NCAR Technical Note TN-485 (National Center for Atmospheric Research, 2010).

  45. 45.

    Oleson, K. W. et al. Technical Description of Version 4.0 of the Community Land Model (CLM) NCAR Technical Note TN-478 (National Center for Atmospheric Research, 2010).

  46. 46.

    Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).

    Article  Google Scholar 

  47. 47.

    Kalnay, E. et al. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc. 77, 437–472 (1996).

    Article  Google Scholar 

  48. 48.

    Goyal, R., Jucker, M., Sen Gupta, A., Hendon, H. & England, M. Zonal Wave 3 Pattern in the Southern Hemisphere Generated by Tropical Convection Mendeley Data v.1 (2021); https://doi.org/10.17632/hvn5568tzh.1

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Acknowledgements

This study was supported by the Australian Research Council (grants CE170100023 and FL150100035). R.G. is supported by the Scientia PhD scholarship from the University of New South Wales. M.H.E. is also supported by the Earth Science and Climate Change Hub of the Australian Government’s National Environmental Science Programme (NESP) and the Centre for Southern Hemisphere Oceans Research (CSHOR), a joint research centre between QNLM, CSIRO, UNSW and UTAS. Analyses were conducted on the National Computational Infrastructure (NCI) facility based in Canberra, Australia. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. ERA-Interim data were obtained from the Climate Data Store (CDS) service at ECMWF.

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Contributions

R.G. conceived the study and, along with M.J., A.S.G. and M.H.E., formulated the experimental design. R.G. conducted the atmospheric model simulations and produced all the analyses examined in the study. All authors contributed to interpreting the results, discussion of the associated dynamics and writing the paper.

Corresponding author

Correspondence to Rishav Goyal.

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The authors declare no competing interests.

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Peer review information Primary Handling Editor: Tom Richardson. Nature Geoscience thanks the anonymous reviewers for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Zonal wavenumber 3 in reanalysis and models.

Fourier filtered zonal wavenumber 3 in a) reanalysis (ERA-Interim) and b) model control (CTRL). Panel c) shows the comparison between three reanalysis (ERA-Interim, ERA-5 and NCEP-NCAR) products and different Atmospheric Model Intercomparison Project (AMIP) model simulations on their ability to represent the ZW3 pattern in the SH extratropics and panel d) shows the comparison between d) different coupled model simulations from the Coupled Model Intercomparison Project 5 (CMIP5). 30-year long simulations from 1979-2008 are considered from all three reanalysis and for AMIP simulations from CMIP models. 100-year long simulations are used for coupled pre-industrial control simulations from CMIP models Fourier transforms are used to calculate the amplitude and the phase (location of the first maximum) of the climatological mean ZW3 pattern. Bias is calculated by subtracting the mean amplitude and phase of reanalysis and modelled ZW3 from the ZW3 obtained from ERA-Interim reanalysis. CESM is marked as black star.

Extended Data Fig. 2 Wave energy in model simulations.

Total wave energy (m2/s2) computed from meridional winds at 300 hPa as a function of wavenumber and latitude in a) aquaplanet, b) SA-only and c) SA-tropics simulations.

Extended Data Fig. 3 Waves in the Aquaplanet simulation.

Zonal waves 1, 2 and 3 are shown in first, second and third column respectively. Zonal waves are filtered using 300 hPa geopotential height field at 55°S. Top row shows the total amplitude of each zonal wave. Thick black line in the second row shows the mean amplitude of the wave and the thin grey lines represent the mean amplitude in each year for 100 years of simulation. Dashed black line in the bottom row represents the zero line.

Extended Data Fig. 4 Waves in the South America only (SA) simulation.

Zonal waves 1, 2 and 3 are shown in first, second and third column respectively. Zonal waves are filtered using 300 hPa geopotential height field at 55°S. Top row shows the total amplitude of each zonal wave. Thick black line in the second row shows the mean amplitude of the wave and the thin grey lines represent the mean amplitude in each year for 100 years of simulation. Dashed black line in the bottom row represents the zero line.

Extended Data Fig. 5 Amplitude of ZW3 in different arrangements of landmasses in the tropics.

Grey lines represent simulations with individual landmasses in the tropics with dotted, solid and dashed grey lines respectively for tropical South America (SA-Tropics), tropical Africa (Africa-Tropics) and tropical Maritime continent (Maritime-Tropics) simulations. Solid blue line is the linear sum of the three grey lines. Black line represents Tropics simulation in which all three tropical landmasses are present and red line represents reanalysis.

Extended Data Fig. 6 Zonal wave 3 in the simulation in which only Antarctica (with orography) is present in the model.

First row shows a longitude-time plot of ZW3 at 55°S in each month for 100 years showing the time evolution of ZW3 phase and amplitude. Thick black line in the second row shows the time mean amplitude of the wave and the thin grey lines represent the time mean amplitude in each year for 100 years of simulation. Dashed black line in the bottom row represents the zero line.

Extended Data Fig. 7 Tropical convection and wave propagation for tropical South American (SA-tropics) simulation.

Panel a) shows Outgoing longwave radiation (OLR). Panel b) shows streamfunction and wave propagation in the SA-tropics simulation. Shading in panel b) represents streamfunction at 300 hPa calculated from the perturbation zonal and meridional velocities (zonal mean removed) and vectors represent wave activity flux for the SA-tropics simulation.

Extended Data Fig. 8 Wave energy and stationary wave number profile in the Southern Hemisphere.

Shading shows the total wave energy (m2/s2) computed from 300 hPa meridional winds in the tropical South America (SA-tropics) simulation. Dashed black line represents the stationary wavenumber (Ks) computed from Hoskins and Karoly (1981)8 and blue solid line shows zonal mean zonal wind profile in the tropical South America simulation.

Extended Data Fig. 9 Vertical Velocity, Perturbation vorticity and eddy geopotential height for midlatitude South America (SA-midlat) simulation.

Panel a) shows vertical velocity at 300 hPa (Pa/sec). Panels b) and c) represent the perturbation vorticity (units are W, where W = 7.29 × 10-5 rad/sec, is rotational rate of earth) at 300 hPa and 850 hPa respectively. Panels d) and e) represent eddy geopotential height corresponding to wavenumber 3 (shading, in meters) at 300 hPa and 850 hPa respectively.

Extended Data Fig. 10 Vertical Velocity, Perturbation vorticity and eddy geopotential height for control (CTRL) simulation.

Panel a) shows vertical velocity at 300 hPa (Pa/sec). Panels b) and c) represent the perturbation vorticity (units are W, where W = 7.29 × 10-5 rad/sec, is rotational rate of earth) at 300 hPa and 850 hPa respectively. Panels d) and e) represent eddy geopotential height corresponding to wavenumber 3 (shading, in meters) at 300 hPa and 850 hPa respectively.

Supplementary information

Supplementary Video 1

Video explaining the complete process of how tropical convection generates stationary waves in the SH extratropics.

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Goyal, R., Jucker, M., Sen Gupta, A. et al. Zonal wave 3 pattern in the Southern Hemisphere generated by tropical convection. Nat. Geosci. 14, 732–738 (2021). https://doi.org/10.1038/s41561-021-00811-3

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