Long‐Lived Concentric Eyewalls and Integrated Kinetic Energy in Tropical Cyclones

Abstract Long‐lived concentric eyewalls (CEs) and short‐lived CEs are accompanied by diverse structural parameters such as intensity ( V max ) and integrated kinetic energy (IKE). This study used a CE data set and an AI‐based tropical cyclone (TC) wind profile reanalysis to examine the impact of CEs on TC evolution revealed by IKE‐V max diagrams. AI‐based wind profiles are a fusion of multichannel satellite imagery and ERA5 data, representing 0–750 km profiles of axisymmetric surface winds. The AI‐derived IKE has an R = 0.996 against aircraft observations. Composite results show that short‐lived CEs (duration <20 h) tend to maintain IKE, while long‐lived CEs (25% of all CEs) favor further IKE growth, contributing to TCs with an enormous circulation. It is suggested that CEs may modulate the TC life cycle, evolving from small, intense storms to large, mature storms to large, weak‐intensity storms before their ultimate demise.

Authors

Institutions

Publication Details

Journal
Geophysical Research Letters
Published
2025-09-19
DOI
https://doi.org/10.1029/2024gl114429
Primary Topic
Tropical and Extratropical Cyclones Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Long‐Lived Concentric Eyewalls and Integrated Kinetic Energy in Tropical Cyclones

Buo‐Fu Chen, Hung‐Chi Kuo, Chih-Chieh Chen
Geophysical Research Letters
Tropical and Extratropical Cyclones Research
article

Long‐Lived Concentric Eyewalls and Integrated Kinetic Energy in Tropical Cyclones

Buo‐Fu Chen, Hung‐Chi Kuo, Chih-Chieh Chen
article en

Abstract

Abstract Long‐lived concentric eyewalls (CEs) and short‐lived CEs are accompanied by diverse structural parameters such as intensity ( V max ) and integrated kinetic energy (IKE). This study used a CE data set and an AI‐based tropical cyclone (TC) wind profile reanalysis to examine the impact of CEs on TC evolution revealed by IKE‐V max diagrams. AI‐based wind profiles are a fusion of multichannel satellite imagery and ERA5 data, representing 0–750 km profiles of axisymmetric surface winds. The AI‐derived IKE has an R = 0.996 against aircraft observations. Composite results show that short‐lived CEs (duration <20 h) tend to maintain IKE, while long‐lived CEs (25% of all CEs) favor further IKE growth, contributing to TCs with an enormous circulation. It is suggested that CEs may modulate the TC life cycle, evolving from small, intense storms to large, mature storms to large, weak‐intensity storms before their ultimate demise.

Geophysical Research LettersVol. 52(18)
National Science and Technology Center for Disaster Reduction (TW), National Taiwan University (TW)
Openalex Percentile: Top 69%
Tropical and Extratropical Cyclones Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.