Assessing Simulated Clouds and Radiative Fluxes Using Properties of Clouds Whose Tops are Exposed to Space
Bibliographic record
Abstract
Abstract Coincident top-of-atmosphere (TOA) radiative fluxes and cloud optical properties for portions of clouds whose tops are exposed to space within several pressure ranges are used to evaluate how a GCM realizes its all-sky radiative fluxes and vertical structure. In particular, observations of cloud properties and radiative fluxes from the Clouds and the Earth’s Radiant Energy System (CERES) Science Team are used to assess the Canadian Centre for Climate Modeling and Analysis atmospheric global climate model (CanAM4). Through comparison of CanAM4 with CERES observations it was found that, while the July-mean all-sky TOA shortwave and longwave fluxes simulated by CanAM4 agree well with those observed, this agreement rests on compensating biases in simulated cloud properties and radiative fluxes for low, middle, and high clouds. Namely, low and middle cloud albedos simulated by CanAM4 are larger than those observed by CERES attributable to CanAM4 simulating cloud optical depths via large liquid water paths that are too large but are partly compensated by too small cloud fractions. It was also found that CanAM4 produces 2D histograms of cloud fraction and cloud albedo for low, middle, and high clouds that are significantly different than generated using the CERES observations.
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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 | 0.001 |
| 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".