Evaluation of CryoSat-2 derived sea-ice freeboard over fast ice in McMurdo Sound, Antarctica
Bibliographic record
Abstract
Abstract Using in situ data from 2011 and 2013, we evaluate the ability of CryoSat-2 (CS-2) to retrieve sea-ice freeboard over fast ice in McMurdo Sound. This provides the first systematic validation of CS-2 in the coastal Antarctic and offers insight into the assumptions currently used to process CS-2 data. European Space Agency Level 2 ( ESAL2 ) data are compared with results of a Waveform Fitting ( WfF ) procedure and a Threshold-First-Maximum-Retracker-Algorithm employed at 40% ( TFMRA40 ). A supervised freeboard retrieval procedure is used to reduce errors associated with sea surface height identification and radar velocity in snow. We find ESAL2 freeboards located between the ice and snow freeboard rather than the frequently assumed snow/ice interface. WfF is within 0.04 m of the ice freeboard but is influenced by variable snow conditions causing increased radar backscatter from the air/snow interface. Given such snow conditions and additional uncertainties in sea surface height identification, a positive bias of 0.14 m away from the ice freeboard is observed. TFMRA40 freeboards are within 0.03 m of the snow freeboard. The separation of freeboard estimates is primarily driven by the different assumptions of each retracker, although waveform alteration by variations in snow properties and surface roughness is evident. Techniques are amended where necessary, and automatic freeboard retrieval procedures for ESAL2 , WfF and TFMRA40 are presented. CS-2 detects annual fast-ice freeboard trends using all three automatic procedures that are in line with known sea-ice growth rates in the region.
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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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".