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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.

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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.

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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.

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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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