[Eoas-seminar] Doctoral Defense - Michael Secor

[eoas-seminar at lists.fsu.edu]

Good afternoon,

Please join us for Michael Secor's Doctoral Defense on Wednesday, March 11th from 2:30-4:30 PM (EST).

Title: A Yearly Varying Elliptical Orbit Representation for Long-Lead Prediction of the Stratospheric Polar Vortex

Name:  Michael Secor
Date:  March 11th, 2:30 - 4:30 PM
Major Professor:  Dr. Ming Cai
Location: EOAS 6067
Zoom: https://fsu.zoom.us/j/4865193607<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Ffsu.zoom.us%2Fj%2F4865193607&data=05%7C02%7Ceoas-seminar%40lists.fsu.edu%7C35de7094721e4e9beb5208de7888c60b%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C639080725982814494%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=xZyiKcjxcK4mNxPMGUNxKTKGYeUA8u5FaUPXG171gHM%3D&reserved=0>

Abstract:
The yearly varying annual evolution of the Northern Hemisphere stratospheric polar vortex (SPV) is shaped by the interplay between the annually consistent seasonal progression of radiative forcing and intermittent, dynamically driven interactions between planetary-scale waves and the mean flow. Variations in external factors such as climate modes modulate wave-mean flow interactions from year to year, driving interannual variability in the SPV's seasonal evolution. During winter, active stratosphere-troposphere coupling allows planetary-scale waves to propagate into the stratosphere, where they can break and disrupt the vortex. The subsequent recovery of the circulation, governed by radiative processes and suppressed wave propagation, gives rise to the observed vacillating behavior of the SPV. Given that these vacillation cycles evolve over multiple months, the opportunity for the SPV to undergo multiple independent strengthening and weakening phases within a single winter
is limited.

Motivated by the premise that interannual variability in the SPV's annual evolution is governed by low-frequency vacillation cycles modulated by external factors, the SPV is represented by fitting an ellipse to the yearly phase space trajectory formed by the daily time series of MU (stratospheric mass-weighted zonally integrated zonal wind at 60N) and M (total polar stratospheric air mass over 60-90N). To capture the full cold-season progression of the SPV within each trajectory, the SPV year is defined from July 1 to June 30 of the following calendar year. This representation achieves a substantial reduction in dimensionality by distilling the full 365 day SPV evolution into six ellipse parameters. A diagnostic evaluation demonstrates that the observed annual evolution of the SPV is accurately reproduced by the representation, capturing year-to-year variability in the observed daily evolution across subseasonal-to-seasonal (S2S) timescales along with the magnitude and timing of cold season
extrema.
Building on this diagnostic framework, long-lead hindcasts of wintertime SPV variability are generated by first predicting the yearly ellipse parameters prior to the onset of the cold season, and then using those predictions to reconstruct daily MU and M trajectories. A multivariate Bayesian regression model is developed to jointly predict yearly values of the six parameters from a set of 17 predictors derived exclusively from information available before October 1 of the forecast year, including indices describing external climate factors, isentropic mass circulation indices, and phase space trajectory precursors. Out of sample validation demonstrates high predictive accuracy across all six parameters. When translated through the elliptical orbit representation, ellipse parameters produce skillful hindcasts of continuously evolving SPV anomalies from November through the end of the cold season, with robust skill at lead times of one to six months. The predicted phase space trajectories also capture the amplitude and timing of wintertime extrema of MU and M. These results demonstrate that representing the SPV through its annual phase space evolution provides a robust framework for generating long-lead predictions of stratospheric polar vortex variability across S2S time scales.

Best,
Adea

Adea Arrison
Sr. Academic Program Specialist
Department of Earth, Ocean & Atmospheric Science
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