Observations of Coherent L-Band Emission from Snow-Covered Arctic Sea Ice
Bibliographic record
Abstract
This study examines L-band (1.4 GHz) radiometric measurements of snow-covered Arctic sea ice collected in January 2024 at the Canadian High Arctic Research Station (CHARS) using the ARIEL microwave radiometer. Significant fluctuations in brightness temperatures (TB) observed, despite relatively homogeneous ice and snow conditions. TBs are modeled using a coherent approach that incorporates interference effects at the snow-ice interface. A cost function is minimized through an optimization-based method to infer optimal snow depth and density, and sea ice brine inclusion geometry, in accordance with the observed brightness temperatures. Results closely match the modeled TB with the in situ data within the expected variability that can be associated with coherence, highlighting the importance of coherence effects in low-frequency microwave radiative transfer modeling. Despite the clear impacts on local, small-scale measurements shown here, the implications on the satellite footprint scale need further evaluation.
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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 | 0.000 |
| 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 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".