Environmental Research Letters (Jan 2023)

Added value of a multiparametric eddy-driven jet diagnostic for understanding European air stagnation

  • J W Maddison,
  • B Ayarzagüena,
  • D Barriopedro,
  • R García-Herrera

DOI
https://doi.org/10.1088/1748-9326/ace72e
Journal volume & issue
Vol. 18, no. 8
p. 084022

Abstract

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Air stagnation refers to an extended period of clear, stable conditions which can favour the accumulation of pollutants in the lower atmosphere. In Europe, weather conditions are strongly mediated by the North Atlantic eddy-driven jet stream. Descriptions of the jet stream typically focus on its latitudinal position or the strength of its wind speed, and its impacts are often studied under different latitudinal regimes of the jet. Herein, we evaluate the influence of the jet stream on European air stagnation using a new multiparametric jet diagnostic that provides a more complete description of jet stream characteristics. We report large influences of the jet stream on regional stagnation and uncover links with jet structure that go beyond knowledge of its latitude. Accordingly, air stagnation anomalies show different, and often opposite, responses to jets in a given latitudinal position but with different additional characteristics. Statistical modelling reveals that the monthly variability in air stagnation explained by the new jet diagnostic is substantially higher compared to one that only considers the jet’s latitude and intensity. Knowledge of the average location of the jet in a given month, as described by a latitude or longitude parameter, together with the variability in the jet’s shape, appear key for the statistical models of air stagnation. The relationship between air stagnation and the jet stream is often nonlinear, particularly for regions in southern Europe. For northern regions it is generally more linear, but the additional jet parameters are essential for describing stagnation variability. These results have implications for studying air stagnation and its pollution impacts in seasonal forecasts and climate change projections.

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