Incidence Angle Dependence of HH-Polarized C- and L-Band Wintertime Backscatter Over Arctic Sea Ice
Bibliographic record
Abstract
Synthetic aperture radar (SAR) incidence angle has a significant effect on the microwave backscatter from sea ice. This paper investigates the incidence angle dependence of C- and L-band HH-polarized microwave backscatter coefficient over Arctic first-year sea ice (FYI) and multiyear sea ice (MYI) in winter. Advanced Land Observation Satellite Phased Array type L-band SAR (L-band) and RADARSAT-2 (C-band) images are used to derive ice type-specific incidence angle dependencies calculated using linear regression models. For L-band, mean ice type-specific incidence angle dependencies for FYI and MYI are -0.21 and -0.30 dB/1°, respectively; and for C-band, they are -0.22 and -0.16 dB/1°, respectively. To validate our results, we calculated root-mean-square deviation (RMSD) by comparing the ice type-specific dependence from 2010 with individual dependencies from 2009 based on ice types and frequencies. The RMSD is found to be smaller than the standard deviation of ice type-specific dependencies for both frequencies. The RMSD values for the L-band incidence angle dependencies are 0.03 and 0.04 dB/1° for FYI and MYI, respectively. For C-band, the RMSD values for the FYI and MYI dependencies are 0.03 and 0.01 dB/1°, respectively. Subsequently, we demonstrate that after applying incidence angle normalization, the variability of C- and L-band SAR backscatter reduces and separability of ice types increase substantially.
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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 | 0.001 | 0.001 |
| 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".