Abstract/Summary

Large-scale, quasi-stationary atmospheric waves (QSWs) have long been known to be associated with weather extremes such as the European heatwave in 2003. There is much debate in the scientific literature as to whether QSW activity may increase under a changing climate, providing a strong motivation for developing a better understanding of the behaviour and drivers of QSWs. This paper presents the first steps in this regard: the development of a robust objective method for a simple identification and characterisation of these waves. A clear connection between QSWs and European weather and extreme events is confirmed for all seasons, indicating that blocking anticyclones are often part of a broader scale wave pattern. Investigation of the QSW climatology in the Northern Hemisphere reveals that wave activity is typically strongest in midlatitudes, particularly at the exit of the Atlantic and Pacific storm track with weaker intensities in summer. In general, the structure of individual QSW events tends to follow the climatological pattern, except in winter where the strongest and most persistent QSWs are typically shifted polewards, indicating a distinct evolution of the ’strongest’ QSW events. Modes of inter-annual variability are calculated to better understand their importance and connection to European temperatures and to identify relevant QSW patterns. This analysis highlights that European winter temperatures are strongly associated with the meridional location of QSW activity whereas warm European summer temperatures are associated with increases in the overall intensity of midlatitude QSW activity. QSWs are shown to be strongly connected to commonly used indices to describe the large scale atmospheric circulation (NAO, AO, Ni˜no 3.4, PNA) but offer a more direct link to understanding their impact on regional weather events. It is therefore hoped that objective identification of QSWs will provide a useful new viewpoint for interpreting large-scale weather alongside more traditional measures and metrics.