English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Atmospheric regime transitions are highly impactful as drivers of extremeweather events, but pose two formidable modeling challenges: predicting thenext event (weather forecasting), and characterizing the statistics of eventsof a given severity (the risk climatology). Each event has a different durationand spatial structure, making it hard to define an objective "average event."We argue here that transition path theory (TPT), a stochastic processframework, is an appropriate tool for the task. We demonstrate TPT's capacitieson a wave-mean flow model of sudden stratospheric warmings (SSWs) developed byHolton and Mass (1976), which is idealized enough for transparent TPT analysisbut complex enough to demonstrate computational scalability. Whereas a recentarticle (Finkel et al. 2021) studied near-term SSW predictability, the presentarticle uses TPT to link predictability to long-term SSW frequency. Thisrequires not only forecasting forward in time from an initial condition, butalso \emph{backward in time} to assess the probability of the initialconditions themselves. TPT enables one to condition the dynamics on the regimetransition occurring, and thus visualize its physical drivers with a vectorfield called the \emph{reactive current}. The reactive current shows thatbefore an SSW, dissipation and stochastic forcing drive a slow decay of vortexstrength at lower altitudes. The response of upper-level winds is late andsudden, occurring only after the transition is almost complete from aprobabilistic point of view. This case study demonstrates that TPT quantities,visualized in a space of physically meaningful variables, can help oneunderstand the dynamics of regime transitions.

Data-driven transition path analysis yields a statistical understanding of sudden stratospheric warming events in an idealized model