A detailed limited-area energy cycle for climate and weather studies: application over the West African climate during three contrasting summers 1997 (dry), 1999 (wet) and 2006 (normal).
Bibliographic record
Abstract
Abstract The West African Monsoon (WAM) is an atmospheric circulation that involves a complex chain of interacting physical processes ranging from small to large temporal and spatial scales. In this work, a detailed atmospheric energy cycle is formulated for limited-area domains in order to understand the WAM intra-seasonal and interannual variability. The energy cycle is cast in terms of available enthalpy and kinetic energy reservoirs. According to the employed definition, the time-averaged (climate) energy reservoirs are decomposed in a component associated with the time-averaged atmospheric state and a component due to the time-averaged statistics of transient. With this approach, a storm energy is defined as the deviation of instantaneous energy from its climate value. The application of energy cycle on the simulated WAM climatology reveals that the available enthalpy of the time-averaged state (AM) is the largest energy reservoir, while the transient-eddy component (AE) is the smallest. On the other hand, the time-averaged and the time-variability kinetic energy reservoirs (KM and KE) are the same order of magnitude, confirming previous studies linking the African Easterly Waves with a mixed barotropic/baroclinic mechanism. A detailed analysis reveals that, in the time-mean state, there is a huge loss of energy flux due to time-averaged pressure work in boundary fluxes, with the result that only a little fraction of AM associated with the ageostrophic circulation contributes to the generation of KM. On the other hand, the loss of AE contributes almost entirely to the gain in KE, indicating negligible loss due to transient-eddy pressure work.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".