Verification of mesoscale modeling for the severe rainfall event over southern Ontario in May 2000
Bibliographic record
Abstract
A coupled atmospheric‐hydrological model (CAHM) with a high‐resolution, self‐nesting and one‐way coupling capability is employed to simulate the severe rainfall event that lead to a flood in May 2000 over southern Ontario. Three verification approaches are carried out to evaluate the atmospheric mesoscale model performance. The results show that the 48‐h accumulated peak precipitation simulated by a mesoscale model successfully captures the observed peak rainfall recorded over a spatially dense rain gauge network in southern Ontario. Furthermore, the quantitative evaluation of the model predicted precipitation demonstrates that there is a systematic improvement in terms of the accuracies and skills when the model resolution is increased. In addition, an independent verification by comparing the CAHM simulated streamflow with the observed hourly streamflow shows the excellent agreement between the simulations and the observations in terms of magnitudes and timing of peak streamflows, indicating that precipitation is well simulated by the atmospheric mesoscale model.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".