Inferring inherent optical properties of sea ice using 360° camera radiance measurements
Bibliographic record
Abstract
Abstract. In this work, we demonstrate the utilization of a compact, consumer-grade 360° camera for measuring the in-ice spectral angular radiance distribution. This novel technique allows for the instantaneous acquisition of all radiometric quantities at a given depth with a non-intrusive probe. This gives the opportunity to monitor the light field structure (mean cosines) from the atmosphere to the underlying ocean beneath ice. In this study, we report vertical profiles of the light field geometric distribution measured at two sites representative of distinct ice types: High Arctic multi-year ice and Chaleur Bay (Quebec, Canada) landfast first-year ice. We also propose a technique to empirically retrieve the depth-resolved inherent optical properties by matching simulated profiles of spectral irradiances calculated with the HydroLight radiative transfer model to the observed ones. As reported in other studies, the derived reduced scattering coefficients were high (641.57 m−1; 72.85 m−1) at the top (2 cm; 5 cm) for both sites (High Arctic; Chaleur Bay) and lower in the interior part of the ice (0.48–4.10 m−1; 0.021–7.79 m−1). Due to the inherent underdetermined nature of the inversion problem, we emphasize the importance of using a similarity parameter that considers both the absorption and the reduced scattering coefficients. Finally, we believe that this radiometric device, combined with the proposed inversion technique, will allow the research community to scale up the measurements of the inherent optical properties of different kinds of sea ice, making it possible to take better account of terrain variability in radiative transfer models.
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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".