A Detailed Limited-Area Atmospheric Energy Cycle for Climate and Weather Studies
Bibliographic record
Abstract
Lorenz’ seminal work on global atmospheric energetics improved our understanding of the general circulation. With the advent of Regional Climate Models (RCMs), it is important to have a limited-area energetic budget available that is applicable for both weather and climate, analogous to Lorenz’ global atmospheric energetics. A regional-scale energetic budget is obtained in this study by applying Reynolds decomposition rules to quadratic forms of the kinetic energy K and the available enthalpy A, to obtain time mean and time deviation contributions. According to the employed definition, the time mean energy contributions are decomposed in a component associated with the time-averaged atmospheric state and a component due to the time-averaged statistics of transient eddies; these contributions are suitable for the study of the climate over a region of interest. Energy fluctuations (the deviations of instantaneous energies from their climate value) that are appropriate for weather studies are split into quadratic and linear contributions. The sum of all the contributions returns exactly to the total primitive kinetic energy and available enthalpy equations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".