Modernization of Atmospheric Physics Parameterization in Canadian NWP
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Atmospheric physics is represented in numerical models by parameterizations that use resolved‐scale information to estimate the effects of physical processes on the atmospheric state. Over time, our understanding of these processes improves, new techniques are introduced to represent physics in a numerical model, and increased resolution changes the relative importance of different parameterizations within the system. As a result, the physical parameterization packages of numerical weather prediction (NWP) models undergo regular updates as older schemes are replaced with newer ones that offer an improved, and often more complex, depiction of relevant physical processes. Such changes are typically combined with a rebalancing of the physics suite because of strong interactions between parameterization schemes and the presence of compensating errors in the system. In this study, a major update to the package of physical parameterizations used in Canadian operational NWP is introduced. The primary goals of this effort were to improve the global energy budget and to facilitate an increase in the vertical resolution of operational configurations. Both of these objectives were achieved, along with a significant improvement in guidance quality for global and regional prediction systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it