Simulation of Satellite Passive Microwave Observations in Rainy Atmospheres at Meteorological Service of Canada
Bibliographic record
Abstract
In the present study, a research version of the Meteorological Service of Canada (MSC) Global Environmental Multi-Scale (GEM) mesoglobal weather forecast model is evaluated by comparing simulated SSM/I brightness temperatures (Tbs) with observed ones. Several comparisons based on two-15-day periods, one in winter and one in summer, have been done. Results are compared to those obtained by [F. Chevallier, P. Bauer, Mon. Wea. Rev., vol.131, p.1240-55 (2003)] for a study conducted on the European Centre for Medium-Range Weather Forecast (ECMWF) model. The overall performance of the GEM model is similar to that of the ECMWF model. The model appears to simulate with realism the large-scale rainy systems but with frequent mislocations. Moreover, the model has a tendency to produce intense small-scale precipitating areas that are not observed. The frequency of cloud and rain occurrences is overestimated by the model. The model has the best skill at simulating the 22 GHz Tbs indicating that the simulated water vapour is realistic in cloudy areas. Finally these results are encouraging enough to continue investigation on the assimilation of brightness temperatures in cloudy and rainy skies at MSC
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".