Toward a polar stratospheric cloud climatology using advanced very high resolution radiometer thermal infrared data
Bibliographic record
Abstract
Polar stratospheric clouds (PSCs) play a critical role in ozone depletion over both polar regions. To date, the most complete PSC records consist of measurements from limb-viewing satellites that offer limited spatial and temporal coverage. To construct a more complete and long-term PSC climatology, we investigated the use of advanced very high resolution radiometer (AVHRR) satellite imagery for detecting PSCs. Two approaches were examined: (1) a correlative approach relating image-derived data to verification data, and (2) an interpretation of the image-derived data based on a radiative transfer model. The model determined that Type II or ice PSCs can be detected using the AVHRR thermal infrared channels. The image-derived data, namely density-sliced channel 5 temperature data, color composites, and density-sliced channel 4‐5 brightness temperature difference images, provide quick views of potential PSC locations. The model-based approach provides the best method for constructing a long-term ice PSC climatology from the AVHRR archive.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".