iSWOT: Project Updates and Initial Results on Cryosphere Monitoring
Bibliographic record
Abstract
Monitoring sea ice is critical for advancing our understanding of climate change, maintaining polar ecosystems, and ensuring safe navigation in the Arctic and Antarctic regions. The SWOT (Surface Water and Ocean Topography) satellite mission aims to provide high-precision measurements of the Earth's water bodies, including oceans, lakes, and rivers. SWOT uses radar interferometry to accurately measure water surface elevation, which helps in understanding and monitoring changes in water levels, currents, and other hydrological dynamics on a global scale. Early findings from the SWOT mission indicate the prospect of new discoveries, extending beyond its main goals in oceanography and hydrology to encompass emerging applications such as cryosphere. This is particularly significant due to SWOT’s wide-swath radar altimeter, which offers unparalleled high-resolution two-dimensional maps of surface elevation. The iSWOT project (ice-SWOT: Unlocking Impacts and Opportunities) is one of the initiatives selected under the new International SWOT Science Team. Its primary objective is to explore innovative cryosphere applications by leveraging the high-resolution data products of the SWOT mission to enhance ice monitoring and characterization in the Canadian Arctic. The project also incorporates Synthetic Aperture Radar (SAR) data from the Canadian RADARSAT Constellation Mission (RCM) to support multi-sensor analysis and validation efforts. This presentation provides first results and key insights from the analysis of SWOT data over sea ice in several experimental sites in Canada. We present results from field measurements in Nain over landfast sea ice. Field measurements include the ice temperature profile and thickness. We also include comparison analysis of sea ice types with RCM imagery over the Canadian Arctic and Beaufort Sea. We also provide preliminary results demonstrating the potential of SWOT for monitoring lake ice and detecting open water in Lake Athabasca, supported by comparisons with RADARSAT Constellation Mission (RCM) and Sentinel-2 imagery. The expedition will take place in the Labrador Sea during the winter, and in the Parry Channel as well as the surrounding channels, sounds, and straits near Prince of Wales Island—including Barrow Strait—during the summer.
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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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".