High Resolution Tropical Cyclone Vortex and Wind Structure from SAR Imagery for ESA MAXSS Project
Bibliographic record
Abstract
The main objective of this dataset is to gather the ocean surface wind fields measured by two C-band synthetic aperture radar (SAR) satellites (e.g, RADARSAT-2 and Sentinel-1) under extreme weather conditions. This dataset aims at providing high-resolution tropical cyclone (TC) ocean surface wind speeds, directions, 34-, 50-, and 64-kt wind radii in each geographical quadrant. TC ocean surface wind speeds and directions were retrieved from RADARSAT-2 and Sentinel-1 dual-polarization (VV, VH) SAR imagery, based on the Bayesian method and local gradient approach, respectively. The procedure for estimating wind radii can be summarized as three steps. First, the contours of each wind radii are computed, which consists of a number of line segments. Then, the distances from the storm center to each point of the longest line segment in each quadrant are calculated. Finally, the 90% cumulative distribution of this distance is defined as the wind radii of a given wind threshold at that quadrant. The SAR-retrieved high-resolution TC ocean surface wind fields and add-values (e.g., 34-, 50-, and 64-kt wind radii) haven been validated using observations from buoys, airborne stepped-frequency microwave radiometer, GPS dropsonde, and spaceborne radiometers. This dataset was produced in the frame of the ESA funded Marine Atmosphere eXtreme Satellite Synergy (MAXSS) project. The primary objective of the ESA Marine Atmosphere eXtreme Satellite Synergy (MAXSS) project is to provide guidence and innovative methodologies to maximize the synergetic use of available Earth Observation data (satellite, in situ) to improve understanding about the multi-scale dynamical characteristics of extreme air-sea interaction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".