COnstraining ORographic Drag Effects (COORDE): A Model Comparison of Resolved and Parametrized Orographic Drag
Bibliographic record
Abstract
Abstract The parametrization of orographic drag processes is a major source of circulation uncertainty in models. The COnstraining ORographic Drag Effects (COORDE) project makes a coordinated effort to narrow this uncertainty by bringing together the modeling community to: explore the variety of orographic drag parametrizations employed in current operational models; assess the resolution sensitivity of resolved and parametrized orographic drag across models; and to validate the parametrized orographic drag in low‐resolution simulations using explicitly resolved orographic drag from high‐resolution simulations. Eleven models from eight major modeling centers are used to estimate resolved orographic drag from high‐resolution (km‐scale) simulations and parametrized orographic drag from low‐resolution simulations, typically used for seasonal forecasting ( ∼ 40 km) and climate projections ( ∼ 100 km). In most models, at both seasonal and climate resolutions, the total (resolved plus parametrized) orographic gravity wave drag over land is shown to be underestimated by a considerable amount (up to 50%) over the Northern and Southern Hemisphere and by more than 60% over the Middle East region, with respect to the resolved gravity wave drag estimated from km‐scale simulations. The km‐scale simulations also provide evidence that the parametrized surface stress and the parametrized low‐level orographic drag throughout the troposphere are overestimated in most models over the Middle East region, particularly at climate resolutions. Through this process‐based evaluation, COORDE provides model developers new valuable information on the current representation of orographic drag at seasonal and climate resolutions and the vertical partitioning of orographic low‐level and gravity wave drag.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".