Atmospheric water species budget in mesoscale simulations of lee cyclones over the Mackenzie River Basin
Bibliographic record
Abstract
A moisture budget over the Mackenzie River Basin (MRB) was computed using a highresolutionmesoscale model with explicit microphysics for 3 lee cyclogenesis events. A uniquefeature of the calculation is that all the budget terms are calculated from the model and noresidual terms are required. It was found that during the initial formative period of the leecyclones, a large influx of moisture occurs at the western boundary. However, as the cyclonemoves further east, a significant amount of moisture is withdrawn through the eastern andsouthern boundaries of the basin. Surface evaporation was found to be relatively large duringthe local day time and plays a vital rôle in initiating convection in the presence of frontal liftingsouth of 60°N within the basin. In 2 of the 3 cases, the total water in the basin increases overthe history of the simulation as a result of substantial lateral flux convergence of total watercontent even though the total precipitation in these two events was nearly 1.4× the surfaceevaporation. For the 3rd cyclone, the total water in the basin decreases substantially becauseof precipitation and large outward moisture flux at the boundary. The dominant microphysicalprocesses governing the transformation of various water species were condensation, deposition, autoconversion and accretion of cloud water by rain, accretion of cloud water by ice, meltingof ice to rain water and evaporation of cloud and rain water. In the net horizontal flux convergenceof water species, the largest was water vapor, followed by ice and cloud water. The netflux convergence of rainwater into the basin was small and the effect of the graupel processesis negligible.
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.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".