Sensitivity of QBO teleconnection to model circulation biases
Abstract The Quasi‐biennial oscillation (QBO) in the equatorial stratospheric winds is known to modulate the extratropical atmospheric circulation so that an easterly QBO phase is associated with a weaker Arctic stratospheric vortex and a negative North Atlantic Oscillation in winter. The link can p...
Published in: | Quarterly Journal of the Royal Meteorological Society |
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Main Authors: | , , |
Other Authors: | |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
2021
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Subjects: | |
Online Access: | http://dx.doi.org/10.1002/qj.4014 https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4014 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/qj.4014 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4014 |
Summary: | Abstract The Quasi‐biennial oscillation (QBO) in the equatorial stratospheric winds is known to modulate the extratropical atmospheric circulation so that an easterly QBO phase is associated with a weaker Arctic stratospheric vortex and a negative North Atlantic Oscillation in winter. The link can potentially be used to improve seasonal forecasts and is usually captured by climate models but with a smaller magnitude than that in observations. Here, the sensitivity of the QBO teleconnection to biases in model circulation is explored in an atmosphere‐only model ECHAM6 with an internally generated QBO, by contrasting simulations by an original, biased model, and a model version in which biases are artificially reduced. We find that the strength of the winter mean Arctic stratospheric vortex response is better reproduced by the bias‐corrected model. On the other hand, the response is delayed by 1 month and there is no improvement in the tropospheric response. Stronger response of the polar vortex in the bias‐corrected model is likely associated with larger magnitude of QBO winds and better‐represented stratospheric mean climate and planetary wave fluxes, but the exact mechanism remains unclear. The results of this study have implications for seasonal forecast model development. |
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