Persistent anomalies of the North Atlantic jet stream and associated surface extremes over Europe

Abstract

Unusual, persistent configurations of the North Atlantic jet stream affect the weather and climate over Europe. We focus on winter and on intraseasonal and seasonal time scales, and study persistent jet anomalies through the lens of large deviation theory using CMIP6 simulations of the MPI-ESM-LR model and ERA5 reanalysis data. The configurations of interest are defined as long-lasting anomalies of few months in jet latitude, speed and zonality. Our results show that persistent temperature and precipitation extremes over large European regions are anomalously frequent during the unusual, persistent jet configurations we identify. Furthermore, the relative increase in frequency of surface extremes is larger for more intense surface extremes and/or more extreme jet anomalies. This is relevant in the context of the predictability of these extremes. The highest extreme event frequencies at the surface are observed in case of precipitation over the Mediterranean and Western Europe during anomalously zonal and/or fast jet events, pointing to these jet anomalies matching rather homogeneous large scale atmospheric configurations with a clear surface footprint. Additionally, our results emphasise the usefulness of large deviation rate functions to estimate the frequency of occurrence of persistent jet anomalies. They therefore provide a tool to statistically describe long-lasting anomalies, much like extreme value theory may be used to investigate shorter-lived extreme events.

Multiple Large‐Scale Dynamical Pathways for Pan–Atlantic Compound Cold and Windy Extremes

“…The large-scale configuration projects onto a significantly negative NAO phase in the days preceding the cold spell, shifting toward more neutral to positive conditions as the cold spell unfolds (Figure S3a in Supporting Information S1). The anomalous configuration of the upper-level jet stream is also visible using classical jet indices, which indicate a stronger, more equatorward-displaced and zonal jet than usual (see Figures S3b-S3d and Text S2 in Supporting Information S1; jet indices as in Galfi & Messori, 2023).…”

Jet Configurations Leading to Extreme Winter Temperatures Over Europe

“…This represents a step forward with respect to the usual approach based only on one EDJ feature (e.g., Mahlstein et al., 2012; Röthlisberger et al., 2016), as it can account for more complex configurations. Very recently, and following the same rationale, Galfi and Messori (2023) have used three EDJ parameters (intensity, latitude, and zonality) to analyze the relationship between persistent anomalies of the NATL EDJ and long‐lasting precipitation and temperature extremes. They highlight that the zonality of the EDJ (a metric related to our Departure and Tilt parameters) affects the occurrence of temperature extreme events, as much as latitude and intensity.…”

CMIP6 Models Overestimate the North Atlantic Eddy-Driven Jet Persistence

“…For instance, persistent shifts in the jet stream and storm tracks (e.g., 2007 UK floods; Blackburn et al, 2008), persistent blocking highs (e.g., 2003 European heatwave, 2010 Russian heatwave), or persistent stationary wave patterns (e.g., Kornhuber et al, 2017). In a recent study, Galfi and Messori (2023) analyzed a 1000-year-long pre-industrial control simulation of the MPI-ESM-LR and found that long-lasting anomalies in the NATL jet latitude position, speed and zonality are associated with more frequent and persistent episodes of extreme temperatures and precipitation across Europe during winter.…”

“…It is crucial to evaluate the accuracy of climate models in capturing this persistence for reliable long-term projections, especially regarding high-impact weather phenomena (e.g., Tuel and Martius, 2023). In particular, studies have consistently highlighted the strong association between latitudinal shifts in the jet stream and extreme weather occurrences over Europe (Galfi & Messori, 2023;Mahlstein et al, 2012;Cattiaux et al, 2010;Trigo et al, 2013). Hence, it is imperative for models to capture these dynamics accurately.…”