The role of cross-polarization in producing high-resolution pan-Arctic sea ice motion from the RADARSAT Constellation Mission over several years
Bibliographic record
Abstract
We introduce a new pan-Arctic Environment and Climate Change Canada (ECCC) HIgh-Resolution sea Ice Tracking System (HIRITS) operating with the RADARSAT Constellation Mission (RCM) HH and HV synthetic aperture radar (SAR) images resampled at a resolution of 80 m. The spacing between neighbour output vectors was often around 1 km. When combining HH and HV, the resulting ice displacements (over 2 h to 3.5 days) derived for June 1, 2022 – May 31, 2025 were in an excellent agreement with International Arctic Buoy Programme data with the overall root-mean square error (RMSE) of 1.48 km, and correlation of 0.996 for the x and y components. Ice motion vectors provided by HV had consistently greater tracking cross-correlation coefficients (with the average value of 0.56) than those derived from HH (average value of 0.45), implying a higher confidence. The RCM HH + HV ice motion agreed well with the existing passive microwave products from the National Snow and Ice Data Center (NSIDC) and Ocean and Sea Ice Satellite Application Facility (OSI SAF) with RMSEs of 4.19 km/d and 5.03 km/d respectively. We introduced an aggregated sea ice motion pan-Arctic gridded product at 2 km resolution that combines individual RCM ice motion products (HH and HV) derived over 3- and 7-day rolling time windows. A greater number of vectors was derived from HV compared to HH across the pan-Arctic domain, except for the situations where the HV signal is low, such as over smooth land fast ice. The new RCM HH + HV products generated since mid-May 2022 will substantially benefit various applications that require sea ice motion at high spatial resolution including accurate computation of sea ice deformation.
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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 | 0.000 | 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) | 0.000 | 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".