Localization Test of the Beijing Shanghai Guangzhou Civil Aviation Numerical Forecast System over Guangdong Area
Bibliographic record
Abstract
In order to optimize the forecasting performance of the WRF based Beijing Shanghai Guangzhou civil aviation numerical forecast system in Guangzhou area,tested three different combinations of physics parameterizatio scheme and data assimilation scheme,conduct numerical simulation to a heavy rainfall event over Guangdong are during October 13-14,2011.The results show that,different combination physics parameterization scheme and data assimilation scheme have greateffect to the precipitation field.The result of using the scheme provided by city university of Hong Kong isbetter than using the scheme provided by Vancouver,Canada(both AWS data are not assimilated).Both using the Hong Kong's scheme,the method of not assimilating AWS data has better result than assimilating AWS data.But for the circulation field,the relative humidity field,the water vapor flux field and the CAP index field,they are less sensitive to different combinations than the precipitation field.Besides,analyze continuou 15 days forecast resultsof the system,the results show that,whether for the precipitation field or the situation field using the Hong Kong's scheme with AWS data are not assimilated gets higher score than the other two combinations,so this scheme is suggested.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".