Stationary Rossby waves in a baroclinic atmospheric waveguide

02 May 2024
Seminars and colloquia
Dobson Room, Atmospheric Physics Building & Online

Peiqiang Xu (Institute of Atmospheric Physics, Chinese Academy of Sciences)

Seminar series
AOPP seminar
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Abstract: Stationary Rossby waves can counteract the eastward drift of westerly wind and persist over a region for extended periods. This prolonged influence over a fixed region makes it highly conducive to the occurrence of extreme event. The propagation of stationary Rossby wave is significantly influenced by the configuration of mean flow. The jet stream, characterized by a narrow region in the atmosphere with high zonal wind speed, is particularly favorable for the propagation of stationary Rossby wave. The jet stream affects the propagation of stationary Rossby wave primarily through the strong lateral wind shear, so can be seen as a barotropic waveguide. In a three-dimensional basic state, a waveguide can form without the presence of strong lateral wind shear. Instead, it can arise due to significant variations in stratification, forming a baroclinic waveguide. The baroclinic waveguide is particularly pronounced during summertime over northern Eurasia and can effectively traps significant portions of stationary Rossby waves in high latitudes. These stationary Rossby waves are believed to be directly responsible for the occurrence of extreme heatwaves in Europe, such as those experienced in 2010 and 2019, as well as the Northern China heatwave in 2023. In this talk, I will introduce the characteristics and dynamics of these stationary Rossby waves in the baroclinic waveguide. In addition, I will also discuss the predictability of these stationary Rossby waves in current operational numerical models. It will be shown that these stationary Rossby waves exhibit a zonally-oriented spatial structure along the baroclinic waveguide. The evolution of these waves is primarily determined by the nonlinear interactions with transient eddies. This strong nonlinearity poses a significant challenge for current operational numerical models in accurately predicting them.