Weather variability in the Earth’s midlatitudes is closely related to the behavior of the jet stream, whose anomalous meandering often brings about extreme weather.  Although the mean position of the jet stream is predicted (and confirmed by observation) to shift poleward under a warming climate, the long-term change in the variability of the jet stream is still poorly constrained.  For example, while the intensity of extreme heat event in the midlatitude summer is expected to increase, atmospheric blocking, one of the main drivers of heat waves, is predicted to decrease in frequency.  The difficulty is twofold: 1) jet stream is influenced by a number of competing dynamical processes, and 2) to build a robust probability distribution of the jet stream and test its sensitivity to climate forcing requires a resource-intensive climate simulations.  

 

In this talk, I will advocate the use of a reduced-order model of the jet stream based on the observed budget of wave activity (a measure of the waviness of the jet stream) to bridge the dynamics and statistics — i.e. how the dynamics shapes the probability distribution of the jet stream’s meander.  The low-order model allows an economical integration to obtain a decent sample size for rare, large wave events, which helps to study the sensitivity of the probability distribution to various forcing types.

 

The same wave activity framework can also be used for extreme event attribution.  As an example, I will show that the 2021 Pacific Northwest heat wave was significantly boosted by an upstream release of latent heating and present a crude estimate of the imprint of global warming on this event without running a climate model.