Long-Term Climatological Impacts of Major Sudden Stratospheric Warming Events on Arctic Tropopause and Tropopause Inversion Layer as Revealed by GNSS Radio Occultation and Reanalysis Data Sets

Abstract

This study explores Arctic tropopause and tropopause inversion layer (TIL) characteristics during major sudden stratospheric warming (SSW) events, along with the underlying dynamical mechanisms, using Global Navigation Satellite System Radio Occultation (GNSS RO) data and multiple reanalysis products, including Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), Japanese 55-year Reanalysis (JRA-55), and ERA5. Winter-spring climatology reveals a pronounced TIL during major SSW events. The strength of TIL (STIL) decreases from November to January, reaching a minimum in January before rebounding through April, while tropopause height follows an inverse trend. For SSW years, STIL strengthens by 1–3 × 10⁻⁵ s⁻² and tropopause height depresses by 200–600 m relative to non-SSW years from January to March. Multi year composite analysis identifies distinct TIL enhancement and tropopause depression within ±5 days of SSW central date, attributed to planetary wave-induced easterly forcing at the stratosphere. These waves trigger westerly wind reversal, and modify residual circulation. Dynamical and adiabatic heating linked to residual vertical velocity amplifies STIL and reduces the tropopause height, with stronger anomalies occurring at higher latitudes. Multi-data set comparisons demonstrate robust consistency in capturing TIL structures and tropopause variability across reanalyses, despite resolution-dependent differences in static stability magnitudes. Notably, coarse-resolution data sets (JRA-55, MERRA-2) effectively resolve TIL features, thereby validating their utility for such studies. This work provides the first long-term climatology of the impact of major SSWs on Arctic TIL, elucidates the mechanism of planetary wave-driven tropopause and TIL anomalies, and establishes methodological frameworks for leveraging diverse data sets in polar atmospheric research.