MODEL INTER-COMPARISON FOR RESEARCH AND OPERATIONAL USE: A CASE STUDY IN THE ALPINE REGION
Bibliographic record
Abstract
AbstracJ: In the framework of an integrated modeling approach at regional and local scale, some models have been implemented and run in our institution: the SISL-MSM by us, the MESO-NH by the Laboratoire de Aerologie and Meteo- france, the ETA Model by NCEP, the MC2 model by CMC-Environment Canada and the WRF model (by many agencies). Boundary condifions are provided by our ESM (European Spectral Model) which is nested in oul GSS (Global SimulationSystem), a global model and an ensemble prediction system.A case study of a summer thunderstorm in the south-alpine region is presented, with simulation made by different models and grid mesh sizes in the same area.Observational data have been compared to the model simulations, The comparison shows the differences among the models and simulation designs in the complex topography of the Alps, the characteristics of the atmosphere behaviour in mountain regions and the importance of non-hydrostatic effects to correctly reproduce the overall physics and dynamics at the mesoscale . Keyw orils -Nume rical simulation, mode I inte r-comparis on, thunderstorm l.INTRODUCTIONMany projects of model inter-comparison are currently operational throughout the world, depending on aims, space and lime scales, domains.However, in the last years, only a few projects concerned the comparison of meteorological atmospheric models at the mesoscale.For example, in the Map project comparisons have been performed to evaluate precipitation zrmounts, thermodynamics, orography-generated gravity waves and their turbulent break down, interaction of large-scale dynamics on locally-driven fluxes and so on.From the operational point of view, the availability of different numerical weather prediction models (NWPM) may help the forecasters to better infer the weather from NWPM results.In our institution, forecasters operate every day in an area where the complexity of the domain plays a major role and this motivates the request to compare results of different models with the aim to operationally use them to improve the forecast itself.Usually there is also a strong orientation toward direct model inter-comparison, which requires a common simulation protocol and specific validation procedures.This is (and, more extensively, will be) done in our project, but an important
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".