Atmospheric Energetics of Three Contrasting West African Monsoon Seasons as Simulated by a Regional Climate Model
Bibliographic record
Abstract
The West African atmospheric energy budget is assessed for the first time across three contrasting monsoon seasons (dry, wet, and moderate) using the latest version of the Canadian Regional Climate Model (CRCM6/GEM5). The model is driven by ERA5 reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF). A formalism appropriate for regional climate energetics is employed to quantify the primary physical processes occurring during the West African Monsoon, with the aim of highlighting those that exhibit significant inter-seasonal variability. The atmospheric energy path shows that the time-mean available enthalpy (AM) reservoir, reflecting high surface temperatures and a lapse rate characteristic of a dry atmosphere, dominates other energy reservoirs. AM is converted into the time-mean kinetic energy (KM) and the time-variability available enthalpy (AE) reservoirs, which are converted into a time-variability kinetic energy reservoir (KE) through barotropic and baroclinic processes. AE is the lowest energy reservoir, confirming smaller temperature variations in the tropics compared to higher latitudes. Kinetic energy reservoirs KM and KE have the same order of magnitude, suggesting that mean flow is as important as eddy activities during the season. The atmospheric energy cycle computed for three contrasting rainy seasons shows that time-variability energy reservoirs (AE and KE) and main terms acting upon them, are proportional to the rainfall activity, being higher (lower) during rainy (dry) years. It also reveals that, while CA (conversion from AM to AE) and the generation term GE feed wave’s development, the frictional term DE counteracts the generation of KE to dampen the creation of transient eddies. These findings suggest that the atmospheric energetic formalism could be applied on West African seasonal forecasts and future climate simulations to implement adaptation strategies.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".