Sea Ice Freeboard Extrapolation from ICESat-2 to Sentinel-1
Bibliographic record
Abstract
Abstract. The ICESat-2 laser altimeter can capture sea ice freeboard along track at both high vertical and high spatial resolution. The measurement occurs along three strong and three weak parallel beams. Thus the across track-direction is only very sparsely covered and capturing the two-dimensional spatial distribution of freeboard at high resolution by this instrument alone is not possible. This work shows how in early Arctic Winter (October, November) Sentinel-1 synthetic aperture radar (SAR) acquisitions can help bridge this gap and meaningfully extrapolate the freeboard measurements to a full two-dimensional mapping. To achieve this it is sufficient to use the SAR HV backscatter to sort the pixels by intensity and then map freeboards measured from altimetry in the area via the cumulative distribution functions. With the presented algorithm, snow and ice freeboard derived from altimetry can be meaningfully extrapolated to Sentinel-1 SAR acquisitions, unlocking an extra dimension of Arctic freeboard monitoring at high spatial resolution, with errors between 10.5 cm and 6 cm for resolutions between 100 m and 400 m.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".