Climate Dynamics

, Volume 46, Issue 5–6, pp 1683–1698 | Cite as

Why the South Pacific Convergence Zone is diagonal

  • Karin van der WielEmail author
  • Adrian J. Matthews
  • Manoj M. Joshi
  • David P. Stevens


During austral summer, the majority of precipitation over the Pacific Ocean is concentrated in the South Pacific Convergence Zone (SPCZ). The surface boundary conditions required to support the diagonally (northwest–southeast) oriented SPCZ are determined through a series of experiments with an atmospheric general circulation model. Continental configuration and orography do not have a significant influence on SPCZ orientation and strength. The key necessary boundary condition is the zonally asymmetric component of the sea surface temperature (SST) distribution. This leads to a strong subtropical anticyclone over the southeast Pacific that, on its western flank, transports warm moist air from the equator into the SPCZ region. This moisture then intensifies (diagonal) bands of convection that are initiated by regions of ascent and reduced static stability ahead of the cyclonic vorticity in Rossby waves that are refracted toward the westerly duct over the equatorial Pacific. The climatological SPCZ is comprised of the superposition of these diagonal bands of convection. When the zonally asymmetric SST component is reduced or removed, the subtropical anticyclone and its associated moisture source is weakened. Despite the presence of Rossby waves, significant moist convection is no longer triggered; the SPCZ disappears. The diagonal SPCZ is robust to large changes (up to ±6 °C) in absolute SST (i.e. where the SST asymmetry is preserved). Extreme cooling (change <−6 °C) results in a weaker and more zonal SPCZ, due to decreasing atmospheric temperature, moisture content and convective available potential energy.


SPCZ SST IGCM4 Asymmetry Rossby waves  Moisture transport 



The CMAP and NOAA IO V2 data were provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their web site at 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. The CMIP5 data was downladed from The research presented in this article was carried out on the High Performance Computing Cluster supported by the Research Computing Service at the University of East Anglia. The authors would like to thank two anonymous reviewers for comments which helped to improve the manuscript.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Karin van der Wiel
    • 1
    • 2
    Email author
  • Adrian J. Matthews
    • 1
    • 2
    • 3
  • Manoj M. Joshi
    • 1
    • 2
    • 4
  • David P. Stevens
    • 1
    • 3
  1. 1.Centre for Ocean and Atmospheric SciencesUniversity of East AngliaNorwichUK
  2. 2.School of Environmental SciencesUniversity of East AngliaNorwichUK
  3. 3.School of MathematicsUniversity of East AngliaNorwichUK
  4. 4.Climatic Research UnitUniversity of East AngliaNorwichUK

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