Cloud optical depths and TOA fluxes: Comparison between satellite and surface retrievals from multiple platforms
Bibliographic record
Abstract
Performances of two cloud property retrieval schemes are assessed by comparison with each other. The study is limited to liquid phase clouds. Two parameters are assessed: cloud optical depth in the visible band and broadband shortwave (SW) flux at the top‐of‐atmosphere (TOA). Retrievals are based on look‐up tables for a variety of conditions using an adding‐doubling code coupled with LOWTRAN‐7 transmittance models. Comparisons of cloud optical depths retrieved from ground measurements with those from ISCCP DX data agree better than previously reported comparisons with the original ISCCP CX data. Likewise, good agreement is obtained between retrieved and inferred TOA SW fluxes. Differences fall within uncertainties of input parameters, as well as shortcomings in the use of a plane‐parallel radiative transfer model and in the inversion schemes themselves.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".