Remote Sensing of Tropical Cyclones by Spaceborne Synthetic Aperture Radar: Past, present, and future
Bibliographic record
Abstract
Spaceborne synthetic aperture radar (SAR) is a unique microwave satellite sensor to monitor tropical cyclones (TC), with high-resolution and large coverage under all weather conditions. This article provides a comprehensive review of the research progress in the field of TC remote sensing by SAR over the last two decades. The representative advances focus on various observations of fine-scale oceanic and atmospheric features, retrieval of surface wind fields, and estimation of TC intensity, structure, and movement parameters. The challenges associated with rain interference on the radar backscatter measurements and the resulting impacts on high wind retrievals are also addressed. We also present perspectives on future development trends. For example, these include utilization of multi-frequency and multipolarization SAR observations and artificial intelligence techniques to accurately obtain TC intensity, size and movement information, the monitoring of TC dynamic processes using SAR constellations, as well as the improvement of TC simulation and prediction accuracy, based on assimilation of surface wind fields derived from multi-mission satellites.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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 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".