Observational constraints on the tropospheric and near-surface winter signature of the Northern Hemisphere stratospheric polar vortex

Abstract

A composite analysis of Northern Hemisphere’s mid-winter tropospheric anomalies under the conditions of strong and weak stratospheric polar vortex was performed on NCEP/NCAR reanalysis data from 1948 to 2013 considering, as additional grouping criteria, the coincidental states of major seasonally relevant climate phenomena, such as El Nino-Southern Oscillation (ENSO), Quasi Biennial Oscillation and strong volcanic eruptions. The analysis reveals that samples of strong polar vortex nearly exclusively occur during cold ENSO states, while a weak polar vortex is observed for both cold and warm ENSO. The strongest tropospheric and near-surface anomalies are found for warm ENSO and weak polar vortex conditions, suggesting that internal tropospheric circulation anomalies related to warm ENSO constructively superpose on dynamical effects from the stratosphere. Additionally, substantial differences are found between the continental winter warming patterns under strong polar vortex conditions in volcanically-disturbed and volcanically-undisturbed winters. However, the small-size samples obtained from the multi-compositing prevent conclusive statements about typical patterns, dominating effects and mechanisms of stratosphere-troposphere interaction on the seasonal time scale based on observational/reanalysis data alone. Hence, our analysis demonstrates that patterns derived from observational/reanalysis time series need to be taken with caution as they not always provide sufficiently robust constraints to the inferred mechanisms implicated with stratospheric polar vortex variability and its tropospheric and near-surface signature. Notwithstanding this argument, we propose a limited set of mechanisms that together may explain a relevant part of observed climate variability. These may serve to define future numerical model experiments minimizing the sample biases and, thus, improving process understanding.