An Observing System Simulation Experiment for the Impact of MTG Candidate Infrared Sounding Mission on Regional Forecasts: System Development and Preliminary Results
Bibliographic record
Abstract
An Observing System Simulation Experiment (OSSE) was designed and developed to assess the potential benefit of the Infrared Sounding on the Meteosat Third Generation (MTG-IRS) geostationary meteorological satellite system to regional forecasts. In the proposed OSSE framework, two different models, namely, the MM5 and WRF models, were used in a nature run and data assimilation experiments, respectively, to reduce the identical twin problem. The 5-day nature run, which included three convective storms that occurred during the period from 11 to 16 June 2002 over US Great Plains, was generated using MM5 with a 4 km. The simulated “conventional” observations and MTG-IRS retrieved temperature and humidity profiles, produced from the nature run, were then assimilated into the WRF model. Calibration experiments showed that assimilating real or simulated “conventional” observations yielded similar error statistics in analyses and forecasts, indicating that the developed OSSE system worked well. On average, the MTG-IRS retrieved profiles had positive impact on the analyses and forecasts. The analyses reduced the errors not only in the temperature and the humidity fields but in the horizontal wind fields as well. The forecast skills of these variables were improved up to 12 hours. The 18 h precipitation forecast accuracy was also increased.
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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 | 0.001 | 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) | 0.000 | 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".