MétaCan
Menu
Back to cohort
Record W3217071176 · doi:10.1109/tgrs.2021.3131004

Tropical Cyclone Center and Symmetric Structure Estimating From SMAP Data

2021· article· en· W3217071176 on OpenAlexafffund
Guosheng Zhang, Chao Xu, Xiaofeng Li, Ziqiang Zhu, William Perrie

Bibliographic record

VenueIEEE Transactions on Geoscience and Remote Sensing · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
FundersNational Key Research and Development Program of ChinaDalhousie UniversityChinese Academy of SciencesEuropean Space AgencyNational Natural Science Foundation of ChinaStartup Foundation for Introducing Talent of Nanjing University of Information Science and TechnologyMarine Environmental Observation Prediction and Response Network
KeywordsTropical cycloneRemote sensingMeteorologyCenter (category theory)Data centerGeologyEnvironmental scienceClimatologyComputer sciencePhysics

Abstract

fetched live from OpenAlex

We propose a methodology to estimate the tropical cyclone (TC) center location associated with the additional TC parameters of the radius of maximum wind (RMW) and intensity, purely from ocean winds observed by the Soil Moisture Active Passive (SMAP) radiometer. This method assumes a symmetric vortex. To demonstrate the method, we analyze 28 SMAP wind fields collected during 11 TCs. Verification of the estimated hurricane centers and wind distributions along the radius is compared with measurements provided by the airborne stepped-frequency microwave radiometer (SFMR) collected during its flying through hurricane cores and to sea surface wind fields derived from spaceborne synthetic aperture radar data. The significance of this simple method is that TC centers, intensities, and RMW can be estimated purely from SMAP wind products, despite SMAP’s low spatial resolution. Comparing these 28 model results to the aircraft measurement (f-deck) and the best track (BT) data, we show that, for the latitudes and longitudes of the TC centers, the standard deviations are 0.28° and 0.29°, respectively, both with a correlation of 1.00. For the detected intensity, the standard deviation is 8.11 m/s, and the correlation is 0.84. We note that the TC intensity detected by this method can be even stronger than the maximum winds observed by the relatively low-resolution SMAP observations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.763

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.257
Teacher spread0.227 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations20
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Transactions on Geoscience and Remote SensingSame topicTropical and Extratropical Cyclones ResearchFrench-language works237,207