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Record W4405780550 · doi:10.2151/jmsj.2025-008

Recent Research and Operational Tools for Improved Understanding and Diagnosis of Tropical Cyclone Inner Core Structure

2024· article· en· W4405780550 on OpenAlexaff
Kosuke Ito, Yoshiaki Miyamoto, Chun‐Chieh Wu, Anthony C. Didlake, James Hlywiak, Yi-Hsuan HUANG, Tsz‐Kin Lai, Lauren Pattie, Nannan Qin, Udai Shimada, Dandan Tao, Yohei Yamada, Jun A. Zhang, Sachie Kanada, Derrick Herndon

Bibliographic record

VenueJournal of the Meteorological Society of Japan Ser II · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsEnvironment and Climate Change Canada
FundersMoonshot Research and Development ProgramOffice of Naval ResearchMinistry of Education, Culture, Sports, Science and TechnologyJapan Society for the Promotion of ScienceNational Science and Technology CouncilNational Oceanic and Atmospheric AdministrationNational Science Foundation
KeywordsTropical cycloneInner coreCore (optical fiber)Cyclone (programming language)ClimatologyMeteorologyComputer scienceGeologyGeographyGeophysics

Abstract

fetched live from OpenAlex

The inner core of a tropical cyclone (TC) is vital for TC energetics and often undergoes dramatic changes. This article provides a review on the understanding and operational practices of the structural changes in the TC inner core, mainly focusing on recent literature and activities. The inner core structure of a TC is generally described as an axisymmetric vortex in the vicinity of a hydrostatic and gradient wind-balanced state. However, this schematic can sometimes be oversimplified. Recent studies have documented small-scale features of the inner core, structural changes in TC rapid intensification, secondary eyewall formation, and eyewall replacement cycles using observational data, and idealized and sophisticated models. In line with the progress in understanding the inner core structure, several operational agencies have recently analyzed TC structural changes using their subjective analyses or diagnostic tools, contributing to disaster prevention. We also discuss potential impacts of climate change on the inner core structure, for which further work is required to reach a solid conclusion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.149
GPT teacher head0.328
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Meteorological Society of Japan Ser IISame topicTropical and Extratropical Cyclones ResearchFrench-language works237,207