Characterizing small-scale gravity waves generated by hurricanes through convective generation and wind filtering effects

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Authors: Panagiotis Vergados
Cited by: 0

Abstract

Small-scale gravity waves (GWs) generated by Hurricane Sam (2021), Fiona (2022) and Dora (2023) are studied using COSMIC-2 GNSS-Radio Occultation (RO) temperature retrievals and ERA5 reanalysis dataset, from which we categorize three GW types that are commonly observed in the hurricanes studied. Using Least Squares Wavelet Analysis (LSWA), our results show that these GW characteristics align well with the conceptual GW theories. Based on GW properties, we introduce a new convention to name these three GW bands as Type A (πœ†πœ†π‘§π‘§ β‰ˆ 12 km) generated by thermal forcing, dominant in the troposphere; Type B (πœ†πœ†π‘§π‘§ β‰ˆ 3-10 km) that is usually shifted towards shorter wavelength by wind filtering effects, including the small-scale waves (πœ†πœ†π‘§π‘§ = 2-3 km) induced by overshooting convection; and Type C (πœ†πœ†π‘§π‘§ β‰ˆ 3-10 km) produced by a combination of thermal forcing and the obstacle effect, prevailing in the stratosphere. GWs observed in Sam and Fiona reveal the spiral propagation and the concentric structure that agree with previous investigations, while displaying an asymmetric east-west wave field in the lower stratosphere. We ascribe this asymmetry as a joint result of wind filtering and obstacle effects. Although the GWs from Dora lack a consistent pattern at different altitudes due to a small-scale GW interference in the UTLS region, distinct GW bands remain evident in the spectral results. Considering the GW similarities among the three hurricanes studied, we reckon the observed GW patterns might be present in other hurricanes, although a hurricane might not reveal all the suggested GW types.

Fields of Study & Subjects

Meteorological Phenomena and Simulations Ionosphere and magnetosphere dynamics Tropical and Extratropical Cyclones Research

Publication details

Journal / source
JPL Data
Publication date
1 January 2026
Language
EN
Document type
Dataset