Sea ice freeboard extrapolation from ICESat-2 to Sentinel-1
Bibliographic record
Abstract
Abstract. The Ice, Cloud and Land Elevation Satellite (ICESat-2) laser altimeter can capture sea ice freeboard along-track at both high vertical and high spatial resolutions. 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 a high resolution using this instrument alone is not possible. This work shows how, in the early Arctic winter months of October and November, Sentinel-1 synthetic aperture radar (SAR) acquisitions help bridge this gap. Freeboard measurements are shown to be meaningfully extrapolated to a full two-dimensional mapping. To achieve this, it is sufficient to use the cross-polarised (HV) SAR 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, the snow and ice freeboard derived from altimetry can be extrapolated to Sentinel-1 SAR scenes, unlocking an additional dimension of Arctic freeboard monitoring at a high spatial resolution, with ice freeboard errors between 6 and 10.5 cm for spatial resolutions between 100 and 400 m.
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 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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".