Tropical Cyclone Center Estimates Purely From FY‐3E WindRAD Measurements in the Dawn‐Dusk Orbit
Bibliographic record
Abstract
Abstract The first C‐ and Ku‐band dual‐frequency scatterometer instrument (WindRAD) on board the world's first early‐morning‐orbiting meteorological satellite Fengyun‐3E (FY‐3E) has the capability to measure global ocean surface winds. However, WindRAD cannot determine the center locations of tropical cyclones (TCs) because it is limited by coarse spatial resolution. In this work, a relatively simple model is applied to identify the storm centers, using ocean wind measurements collected by the WindRAD scatterometer. The model—estimated storm centers are determined to minimize the errors between model—simulated winds and WindRAD measurements. Our data set consists of all WindRAD overpasses of TCs during 2022 and 2023 in the West Pacific, East Pacific, North Atlantic and Northern Indian Oceans. The average errors between the WindRAD model estimates and the reported best‐track storm center locations are 51, 40, and 25 km, for tropical storms, category 1–2 storms and major storms (>49 m s −1 ), respectively. Our model is both objective and automatic, thereby avoiding subjectivity and possible errors related to manual analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".