The second compare exercise: A model intercomparison using a case of a typical mesoscale orographic flow, the pyrex iop3
Bibliographic record
Abstract
Abstract Fifteen models have been evaluated for their ability to simulate the various phenomena of a mesoscale orographic flow sampled during the Pyrénées experiment (PYREX). A pure forecast exercise has been conducted and model performances were assessed using numerous observations. for additional experiments were also performed in order to discriminate between small‐scale errors and large‐scale induced errors, and to discuss an optimal specification of model terrain height and roughness for use with envelope orography and effective roughness length parametrizations. The comparison results reveal systematic errors for all the models: the local winds are too weak, the mountain‐wave amplitude is too large and the lee vortices are poorly represented. Since forcing by analyses did not correct the errors, they can be therefore mainly attributed to the model representation of orography. The blocking created by the model topography at low level is under‐represented and the model topography does not sufficiently slow the flow. A positive consequence of the effective roughness length parametrization is to reduce the mountain‐wave amplitude. Negligible benefit occurs from the use of an envelope orography parametrization. Although it favours the appearance of the lee vortices, the latter appear too early, the local winds remain too weak, and the mountain‐wave amplitude is enhanced. The comparison of the computed pressure drag with the observed one is reasonably good for most of the models but the pressure drag is found to be more correlated to the lee vorticity than to the mountain wave.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".