skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Learning Forecasts of Rare Stratospheric Transitions from Short Simulations
Abstract Rare events arising in nonlinear atmospheric dynamics remain hard to predict and attribute. We address the problem of forecasting rare events in a prototypical example, sudden stratospheric warmings (SSWs). Approximately once every other winter, the boreal stratospheric polar vortex rapidly breaks down, shifting midlatitude surface weather patterns for months. We focus on two key quantities of interest: the probability of an SSW occurring, and the expected lead time if it does occur, as functions of initial condition. These optimal forecasts concretely measure the event’s progress. Direct numerical simulation can estimate them in principle but is prohibitively expensive in practice: each rare event requires a long integration to observe, and the cost of each integration grows with model complexity. We describe an alternative approach using integrations that are short compared to the time scale of the warming event. We compute the probability and lead time efficiently by solving equations involving the transition operator, which encodes all information about the dynamics. We relate these optimal forecasts to a small number of interpretable physical variables, suggesting optimal measurements for forecasting. We illustrate the methodology on a prototype SSW model developed by Holton and Mass and modified by stochastic forcing. While highly idealized, this model captures the essential nonlinear dynamics of SSWs and exhibits the key forecasting challenge: the dramatic separation in time scales between a single event and the return time between successive events. Our methodology is designed to fully exploit high-dimensional data from models and observations, and has the potential to identify detailed predictors of many complex rare events in meteorology.  more » « less
Award ID(s):
1852727
PAR ID:
10329444
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Monthly Weather Review
Volume:
149
Issue:
11
ISSN:
0027-0644
Page Range / eLocation ID:
3647 to 3669
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; (, Journal of the Atmospheric Sciences)
    Abstract Atmospheric regime transitions are highly impactful as drivers of extreme weather events, but pose two formidable modeling challenges: predicting the next event (weather forecasting) and characterizing the statistics of events of a given severity (the risk climatology). Each event has a different duration and spatial structure, making it hard to define an objective “average event.” We argue here that transition path theory (TPT), a stochastic process framework, is an appropriate tool for the task. We demonstrate TPT’s capacities on a wave–mean flow model of sudden stratospheric warmings (SSWs) developed by Holton and Mass, which is idealized enough for transparent TPT analysis but complex enough to demonstrate computational scalability. Whereas a recent article (Finkel et al. 2021) studied near-term SSW predictability, the present article uses TPT to link predictability to long-term SSW frequency. This requires not only forecasting forward in time from an initial condition, but also backward in time to assess the probability of the initial conditions themselves. TPT enables one to condition the dynamics on the regime transition occurring, and thus visualize its physical drivers with a vector field called the reactive current . The reactive current shows that before an SSW, dissipation and stochastic forcing drive a slow decay of vortex strength at lower altitudes. The response of upper-level winds is late and sudden, occurring only after the transition is almost complete from a probabilistic point of view. This case study demonstrates that TPT quantities, visualized in a space of physically meaningful variables, can help one understand the dynamics of regime transitions. 
    more » « less
  2. ; ; ; ; ; ; (, Journal of the Atmospheric Sciences)
    null (Ed.)
    Abstract The Whole Atmosphere Community Climate Model, version 4 (WACCM4), is used to investigate the influence of stratospheric conditions on the development of sudden stratospheric warmings (SSWs). To this end, targeted experiments are performed on selected modeled SSW events. Specifically, the model is reinitialized three weeks before a given SSW, relaxing the surface fluxes, winds, and temperature below 10 km to the corresponding fields from the free-running simulation. Hence, the tropospheric wave evolution is unaltered across the targeted experiments, but the stratosphere itself can evolve freely. The stratospheric zonal-mean state is then altered 21 days prior to the selected SSWs and rerun with an ensemble of different initial conditions. It is found that a given tropospheric evolution concomitant with the development of an SSW does not uniquely determine the occurrence of an event and that the stratospheric conditions are relevant to the subsequent evolution of the stratospheric flow toward an SSW, even for a fixed tropospheric evolution. It is also shown that interpreting the meridional heat flux at 100 hPa as a proxy of the tropospheric injection of wave activity into the stratosphere should be regarded with caution and that stratospheric dynamics critically influence the heat flux at that altitude. 
    more » « less
  3. ; ; ; ; ; (, Journal of Climate)
    The tropospheric response to midwinter sudden stratospheric warmings (SSWs) is examined using an idealized model. SSW events are triggered by imposing high-latitude stratospheric heating perturbations of varying magnitude for only a few days, spun off from a free-running control integration (CTRL). The evolution of the thermally triggered SSWs is then compared with naturally occurring SSWs identified in CTRL. By applying a heating perturbation, with no modification to the momentum budget, it is possible to isolate the tropospheric response directly attributable to a change in the stratospheric polar vortex, independent of any planetary wave momentum torques involved in the initiation of an SSW. Zonal-wind anomalies associated with the thermally triggered SSWs first propagate downward to the high-latitude troposphere after ~2 weeks, before migrating equatorward and stalling at midlatitudes, where they straddle the near-surface jet. After ~3 weeks, the circulation and eddy fluxes associated with thermally triggered SSWs evolve very similarly to SSWs in CTRL, despite the lack of initial planetary wave driving. This suggests that at longer lags, the tropospheric response to SSWs is generic and it is found to be linearly governed by the strength of the lower-stratospheric warming, whereas at shorter lags, the initial formation of the SSW potentially plays a large role in the downward coupling. In agreement with previous studies, synoptic waves are found to play a key role in the persistent tropospheric jet shift at long lags. Synoptic waves appear to respond to the enhanced midlatitude baroclinicity associated with the tropospheric jet shift, and preferentially propagate poleward in an apparent positive feedback with changes in the high-latitude refractive index. 
    more » « less
  4. ; ; ; ; ; ; (, Atmospheric Chemistry and Physics)
    Abstract. Stratospheric circulation is a critical part of the Arctic ozone cycle.Sudden stratospheric warming events (SSWs) manifest the strongest alterationof stratospheric dynamics. During SSWs, changes in planetary wavepropagation vigorously influence zonal mean zonal wind, temperature, andtracer concentrations in the stratosphere over the high latitudes. In thisstudy, we examine six persistent major SSWs from 2004 to 2020 using theModern-Era Retrospective analysis for Research and Applications, Version 2(MERRA-2). Using the unique density of observations around the Greenlandsector at high latitudes, we perform comprehensive comparisons of high-latitude observations with the MERRA-2 ozone dataset during the six majorSSWs. Our results show that MERRA-2 captures the high variability of mid-stratospheric ozone fluctuations during SSWs over high latitudes. However,larger uncertainties are observed in the lower stratosphere and troposphere.The zonally averaged stratospheric ozone shows a dramatic increase of9 %–29 % in total column ozone (TCO) near the time of each SSW, which lastsup to 2 months. This study shows that the average shape of the Arcticpolar vortex before SSWs influences the geographical extent, timing, andmagnitude of ozone changes. The SSWs exhibit a more significant impact onozone over high northern latitudes when the average polar vortex is mostlyelongated as seen in 2009 and 2018 compared to the events in which the polarvortex is displaced towards Europe. Strong correlation (R2=90  %) isobserved between the magnitude of change in average equivalent potentialvorticity before and after SSWs and the associated averaged total columnozone changes over high latitudes. This paper investigates the differentterms of the ozone continuity equation using MERRA-2 circulation, whichemphasizes the key role of vertical advection in mid-stratospheric ozoneduring the SSWs and the magnified vertical advection in elongated vortexshape as seen in 2009 and 2018. 
    more » « less
  5. ; ; ; (, AGU Advances)
    Abstract Extreme weather events have significant consequences, dominating the impact of climate on society. While high‐resolution weather models can forecast many types of extreme events on synoptic timescales, long‐term climatological risk assessment is an altogether different problem. A once‐in‐a‐century event takes, on average, 100 years of simulation time to appear just once, far beyond the typical integration length of a weather forecast model. Therefore, this task is left to cheaper, but less accurate, low‐resolution or statistical models. But there is untapped potential in weather model output: despite being short in duration, weather forecast ensembles are produced multiple times a week. Integrations are launched with independent perturbations, causing them to spread apart over time and broadly sample phase space. Collectively, these integrations add up to thousands of years of data. We establish methods to extract climatological information from these short weather simulations. Using ensemble hindcasts by the European Center for Medium‐range Weather Forecasting archived in the subseasonal‐to‐seasonal (S2S) database, we characterize sudden stratospheric warming (SSW) events with multi‐centennial return times. Consistent results are found between alternative methods, including basic counting strategies and Markov state modeling. By carefully combining trajectories together, we obtain estimates of SSW frequencies and their seasonal distributions that are consistent with reanalysis‐derived estimates for moderately rare events, but with much tighter uncertainty bounds, and which can be extended to events of unprecedented severity that have not yet been observed historically. These methods hold potential for assessing extreme events throughout the climate system, beyond this example of stratospheric extremes. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email