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Sensitivity of QBO teleconnection to model circulation biases
Author(s) -
Karpechko Alexey Yu.,
Tyrrell Nicholas L.,
Rast Sebastian
Publication year - 2021
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.4014
Subject(s) - teleconnection , polar vortex , arctic oscillation , climatology , extratropical cyclone , quasi biennial oscillation , environmental science , stratosphere , atmospheric sciences , atmospheric circulation , north atlantic oscillation , climate model , troposphere , atmospheric model , atmosphere (unit) , general circulation model , climate change , geology , physics , meteorology , northern hemisphere , el niño southern oscillation , oceanography
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.