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The intensification of winter mid-latitude storm tracks in the Southern Hemisphere


The strength of mid-latitude storm tracks shapes weather and climate phenomena in the extra-tropics, as these storm tracks control the daily to multi-decadal variability of precipitation, temperature and winds. By the end of this century, winter mid-latitude storms are projected to intensify in the Southern Hemisphere, with large consequences over the entire extra-tropics. Therefore, it is critical to be able to accurately assess the impacts of anthropogenic emissions on these storms to improve societal preparedness for future changes. Here we show that current climate models severely underestimate the intensification in mid-latitude storm tracks in recent decades. Specifically, the intensification obtained from reanalyses has already reached the model-projected end-of-the-century intensification. The biased intensification is found to be linked to biases in the zonal flow. These results question the ability of climate models to accurately predict the future impacts of anthropogenic emissions in the Southern Hemisphere mid-latitudes.

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Fig. 1: Recent changes in Southern Hemisphere winter mid-latitude storm tracks.
Fig. 2: Time of emergence of mid-latitude storm tracks.
Fig. 3: Linear normal-mode instability analysis.

Data availability

The data used in the manuscript are publicly available: CMIP6 data (, NCEP2 (, JRA-55 (, ERA-I and ERA5 (, NOAA-CIRES-DOE ( and CESM (

Code availability

Any codes used in the manuscript are available at


  1. Pfahl, S. & Wernli, H. Quantifying the relevance of cyclones for precipitation extremes. J. Clim. 25, 6770–6780 (2012).

    Google Scholar 

  2. Catto, J. L., Madonna, E., Joos, H., Rudeva, I. & Simmonds, I. Global relationship between fronts and warm conveyor belts and the impact on extreme precipitation. J. Clim. 28, 8411–8429 (2015).

    Google Scholar 

  3. Ma, C. G. & Chang, E. K. M. Impacts of storm-track variations on wintertime extreme weather events over the continental United States. J. Clim. 30, 4601–4624 (2017).

    Google Scholar 

  4. Yau, A. M. W. & Chang, E. K. M. Finding storm track activity metrics that are highly correlated with weather impacts. Part I: frameworks for evaluation and accumulated track activity. J. Clim. 33, 10169–10186 (2020).

    Google Scholar 

  5. Yin, J. H. A consistent poleward shift of the storm tracks in simulations of 21st century climate. Geophys. Res. Lett. 32, L18701 (2005).

    Google Scholar 

  6. O’Gorman, P. A. Understanding the varied response of the extratropical storm tracks to climate change. Proc. Natl Acad. Sci. USA 107, 19176–19180 (2010).

    Google Scholar 

  7. Wu, Y., Ting, M., Seager, R., Huang, H. & Cane, M. A. Changes in storm tracks and energy transports in a warmer climate simulated by the GFDL CM2.1 model. Clim. Dyn. 37, 53–72 (2011).

    Google Scholar 

  8. Chang, E. K. M., Guo, Y. & Xia, X. CMIP5 multimodel ensemble projection of storm track change under global warming. J. Geophys. Res. 117, D23118 (2012).

    Google Scholar 

  9. Harvey, B. J., Shaffrey, L. C. & Woollings, T. J. Equator-to-pole temperature differences and the extra-tropical storm track responses of the CMIP5 climate models. Clim. Dyn. 43, 1171–1182 (2014).

    Google Scholar 

  10. Lehmann, J., Coumou, D., Frieler, K., Eliseev, A. V. & Levermann, A. Future changes in extratropical storm tracks and baroclinicity under climate change. Environ. Res. Lett. 9, 084002 (2014).

    Google Scholar 

  11. Shaw, T. A. et al. Storm track processes and the opposing influences of climate change. Nat. Geosci. 9, 656–664 (2016).

    CAS  Google Scholar 

  12. Chang, E. K. M. Projected significant increase in the number of extreme extratropical cyclones in the Southern Hemisphere. J. Clim. 30, 4915–4935 (2017).

    Google Scholar 

  13. Blazquez, J. & Solman, S. A. Relationship between projected changes in precipitation and fronts in the austral winter of the Southern Hemisphere from a suite of CMIP5 models. Clim. Dyn. 52, 5849–5860 (2019).

    Google Scholar 

  14. Bengtsson, L., Hodges, K. I. & Keenlyside, N. Will extratropical storms intensify in a warmer climate?. J. Clim. 22, 2276–2301 (2009).

    Google Scholar 

  15. Yettella, V. & Kay, J. E. How will precipitation change in extratropical cyclones as the planet warms? Insights from a large initial condition climate model ensemble. Clim. Dyn. 49, 1765–1781 (2017).

    Google Scholar 

  16. Reboita, M. S., da Rocha, R. P., Ambrizzi, T. & Gouveia, C. D. Trend and teleconnection patterns in the climatology of extratropical cyclones over the Southern Hemisphere. Clim. Dyn. 45, 1929–1944 (2015).

    Google Scholar 

  17. Kidston, J. & Gerber, E. P. Intermodel variability of the poleward shift of the austral jet stream in the CMIP3 integrations linked to biases in 20th century climatology. Geophys. Res. Lett. 37, L09708 (2010).

    Google Scholar 

  18. Simpson, I. R. & Polvani, L. M. Revisiting the relationship between jet position, forced response, and annular mode variability in the southern midlatitudes. Geophys. Res. Lett. 43, 2896–2903 (2016).

    Google Scholar 

  19. Bracegirdle, T. J. et al. Improvements in circumpolar Southern Hemisphere extratropical atmospheric circulation in CMIP6 compared to CMIP5. Earth Space Sci. 7, 01065 (2020).

    Google Scholar 

  20. Priestley, M. D. K. et al. An overview of the extratropical storm tracks in CMIP6 historical simulations. J. Clim. 33, 6315–6343 (2020).

    Google Scholar 

  21. Coumou, D., Lehmann, J. & Beckmann, J. The weakening summer circulation in the Northern Hemisphere mid-latitudes. Science 348, 324–327 (2015).

    CAS  Google Scholar 

  22. Chemke, R. & Ming, Y. Large atmospheric waves will get stronger, while small waves will get weaker by the end of the 21st century. Geophys. Res. Lett. 47, e2020GL090441 (2020).

    Google Scholar 

  23. Eyring, V. et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9, 1937–1958 (2016).

    Google Scholar 

  24. Thompson, D. W. J., Barnes, E. A., Deser, C., Foust, W. E. & Phillips, A. S. Quantifying the role of internal climate variability in future climate trends. J. Clim. 28, 6443–6456 (2015).

    Google Scholar 

  25. Hodges, K., Cobb, A. & Vidale, P. L. How well are tropical cyclones represented in reanalysis datasets? J. Clim. 30, 5243–5264 (2017).

    Google Scholar 

  26. Chemke, R. & Polvani, L. M. Opposite tropical circulation trends in climate models and in reanalyses. Nat. Geosci. 12, 528–532 (2019).

    CAS  Google Scholar 

  27. Hawkins, E. & Sutton, R. Time of emergence of climate signals. Geophys. Res. Lett. 39, L01702 (2012).

    Google Scholar 

  28. Santer, B. D. et al. Human and natural influences on the changing thermal structure of the atmosphere. Proc. Natl Acad. Sci. USA 110, 17235–17240 (2013).

    CAS  Google Scholar 

  29. Chemke, R. & Polvani, L. M. Linking midlatitudes eddy heat flux trends and polar amplification. NPJ Clim. Atmos. Sci. 3, 8 (2020).

    Google Scholar 

  30. Hawkins, E. & Sutton, R. The potential to narrow uncertainty in regional climate predictions. Bull. Am. Meteorol. Soc. 90, 1095–1107 (2009).

    Google Scholar 

  31. Deser, C., Phillips, A., Bourdette, V. & Teng, H. Uncertainty in climate change projections: the role of internal variability. Clim. Dyn. 38, 527–546 (2012).

    Google Scholar 

  32. Deser, C., Knutti, R., Solomon, S. & Phillips, A. S. Communication of the role of natural variability in future North American climate. Nat. Clim. Change 2, 775–779 (2012).

    Google Scholar 

  33. Kay, J. E. et al. The Community Earth System Model (CESM) Large Ensemble Project: a community resource for studying climate change in the presence of internal climate variability. Bull. Am. Meteorol. Soc. 96, 1333–1349 (2015).

    Google Scholar 

  34. Jones, J. M. et al. Assessing recent trends in high-latitude Southern Hemisphere surface climate. Nat. Clim. Change 6, 917–926 (2016).

    Google Scholar 

  35. James, I. N. Suppression of baroclinic instability in horizontally sheared flows. J. Atmos. Sci. 44, 3710–3720 (1987).

    Google Scholar 

  36. Simmons, A. J. & Hoskins, B. J. The life cycles of some nonlinear baroclinic waves. J. Atmos. Sci. 35, 414–432 (1978).

    Google Scholar 

  37. Vallis, G. K. Atmospheric and Oceanic Fluid Dynamics (Cambridge Univ. Press, 2006).

  38. Pedlosky, J. Geophysical Fluid Dynamics 2nd edn (Springer-Verlag, 1987).

  39. Kidston, J. & Vallis, G. K. Relationship between eddy-driven jet latitude and width. Geophys. Res. Lett. 37, L21809 (2010).

    Google Scholar 

  40. Kobayashi et al., S. The JRA-55 reanalysis: general specifications and basic characteristics. J. Meteorol. Soc. Jpn 93, 5–48 (2015).

    Google Scholar 

  41. Kanamitsu, M. et al. NCEP-DOE AMIP-II reanalysis (R-2). Bull. Am. Meteorol. Soc. 83, 1631–1643 (2002).

    Google Scholar 

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

    Google Scholar 

  43. Slivinski et al., L. C. Towards a more reliable historical reanalysis: improvements for version 3 of the Twentieth Century Reanalysis system. Q. J. R. Meteorol. Soc. 145, 2876–2908 (2019).

    Google Scholar 

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

    Google Scholar 

  45. Chemke, R. & Kaspi, Y. The latitudinal dependence of atmospheric jet scales and macroturbulent energy cascades. J. Atmos. Sci. 72, 3891–3907 (2015).

    Google Scholar 

  46. Chemke, R. & Kaspi, Y. The effect of eddy–eddy interactions on jet formation and macroturbulent scales. J. Atmos. Sci. 73, 2049–2059 (2016).

    Google Scholar 

  47. Chemke, R. & Kaspi, Y. The latitudinal dependence of the oceanic barotropic eddy kinetic energy and macroturbulence energy transport. Geophys. Res. Lett. 43, 2723–2731 (2016).

    Google Scholar 

  48. Chemke, R., Dror, T. & Kaspi, Y. Barotropic kinetic energy and enstrophy transfers in the atmosphere. Geophys. Res. Lett. 43, 7725–7734 (2016).

    Google Scholar 

  49. Chemke, R. Atmospheric energy transfer response to global warming. Q. J. R. Meteorol. Soc. 143, 2296–2308 (2017).

    Google Scholar 

  50. Chemke, R. Codes for calculating the eddy growth rate. Zenodo (2022).

  51. Peixoto, J. P. & Oort, A. H. Physics of Climate (American Institute of Physics, 1992).

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R.C. is grateful to the WIS support of young scientists and to A. Novoselsky for downloading the data.

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R.C. analysed the data and together with Y.M. and J.Y. discussed and wrote the paper.

Corresponding author

Correspondence to Rei Chemke.

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Extended data

Extended Data Fig. 1 Recent trends in Southern Hemisphere winter mid-latitude storm tracks.

The mean of all 10-year, 20-year and 30-year trends over the 1979-2018 period in a, eddy kinetic energy and b, poleward eddy moist static energy flux in reanalyses mean (blue) and CMIP6 mean (gray). The black circles show the trends from the individual reanalyses/models.

Extended Data Fig. 2 Latitudinal distribution of poleward eddy moist static energy flux trends.

The 1979-2018 trends in poleward eddy moist static energy flux as a function of latitude in reanalyses mean (blue line) and CMIP6 mean (black line). Shadings show two standard deviations across reanalyses/CMIP6 models.

Extended Data Fig. 3 Variability of winter mid-latitude storm tracks trends.

One standard deviation across all 10-year, 20-year and 30-year trends in a, eddy kinetic energy and b, poleward eddy moist static energy flux in reanalyses mean (blue), CMIP6 mean (gray), and pre-industrial runs (red). The trends in CMIP6 and reanalyses were calculated over the detrended 1979-2018 period. The black circles show the results from individual reanalyses/models.

Extended Data Fig. 4 Recent trends in the meridional structure of the zonal wind.

The 1979-2018 trends in the second meridional derivative of the tropospheric (averaged between 850 mb − 300 mb) mean zonal wind, \(\frac{\partial }{r\partial \phi }\frac{1}{r\cos \phi }\frac{\partial \bar{u}\cos \phi }{\partial \phi }\), in mean reanalyses (blue lines) and CMIP6 models (black lines). Shadings show the 95% confidence interval of the trends. The vertical lines mark the climatological position of the mean zonal wind’s core in reanalyses mean (blue) and CMIP6 models (black). Green line marks the zero line. The latitudinal structure is smoothed with a 3-point running mean for plotting purposes.

Extended Data Fig. 5 Recent trends in eddy momentum flux convergence.

The 1979-2018 trends in vertically averaged eddy momentum flux convergence, \(-\frac{1}{r{\cos }^{2}\phi }\frac{\partial \overline{{u}^{\prime}{v}^{\prime}}{\cos }^{2}\phi }{\partial \phi }\), in mean reanalyses (blue lines) and CMIP6 models (black lines). Shadings show the 95% confidence interval of the trends. The vertical lines mark the climatological position of the mean zonal wind’s core in reanalyses mean (blue) and CMIP6 models (black). Green line marks the zero line. The latitudinal structure is smoothed with a 3-point running mean for plotting purposes.

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Chemke, R., Ming, Y. & Yuval, J. The intensification of winter mid-latitude storm tracks in the Southern Hemisphere. Nat. Clim. Chang. 12, 553–557 (2022).

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