dphase_cmcgeml: regional GEM model driving (low resolution) forecast run by CMC for the MAP D-PHASE project
Bibliographic record
Abstract
Project: D-PHASE, Demonstration of Probabilistic Hydrological and Atmospheric Simulation of flood Events in the Alpine region - The Mesoscale Alpine Programme (MAP, the first WWRP Research and Development Project (RDP)) is an international research initiative devoted to the study of atmospheric and hydrological processes over mountainous terrain. It aims towards expanding our knowledge of weather and climate over complex topography, and thereby to improve current forecasting capabilities. A large-scale field phase in the Alpine region took place from 7 September to 15 November 1999. D-PHASE (Demonstration of Probabilistic Hydrological and Atmospheric Simulation of flood Events in the Alpine region) is a WWRP Forecast Demonstration Project (FDP) and aims at demonstrating some of the many achievements of MAP, in particular the ability of forecasting heavy precipitation and related flooding events in the Alpine region. The MAP FDP will address the entire forecasting chain ranging from limited-area ensemble forecasting, high-resolution atmospheric modelling(km-scale), hydrological modelling, and nowcasting to decision making by the end users, i.e., it is foreseen to set up an end-to-end forecasting system. The demonstration period of MAP D-PHASE will be 1 June to 30 November 2007. See also official homepage: http://www.map.meteoswiss.ch/map-doc/dphase/dphase_info.htm Please be aware of the common COPS/GOP/D-PHASE data policy, which you please find at http://cops.wdc-climate.de/ Summary: The Canadian Meterological Centre (CMC) is running the Global Environmental Multiscale (GEM) model in limited-area mode for the duration of the MAP D-PHASE project (1 June - 31 November 2007). The model is run once-daily directly from operational GEM meso-global forecast data (grid spacing of 33 km). A pair of domains are used for the project with horizontal grid spacings of 15 km and 2.5 km. This outer (low resolution or driving) grid is initialized daily at 0000 UTC and covers all of Europe, out to the British Isles, the North Sea, and Nortern Africa. The timestep for this forecast is 300 sec and outputs are available hourly. No regional analysis or data assimilation cycle is undertaken during this project. All observational data will therefore be ingested only indrectly in the regional setup through the outer grid initialization and hourly boundary updates from the meso-global model. The GEM model is a semi-implicit, semi-Lagrangian, two time-level, non-hydrostatic model that runs in a wide variety of configurations. An updated version (v3.3.0) of the GEM model is being used for the MAP D-PHASE project in preparation for the Vancouver 2010 Olympic Games project. This version takes advantage of recent developments designed to enhance the quality of guidance over regions of steeply-sloping orography, including the addition of a 6-category bulk microphysics scheme and time-varying orography over the initialization period. For more information on -the GEM model dynamics: see Cote et al (1998) [Mon. Wea. Rev.]. -the model physics package: contact Recherche en Prevision Numerique for the related technical document by Mailhot. -the model's microphysics scheme: see Milbrandt and Yau (2007) [Mon. Wea. Rev.]. Grid description: DDOM: xfirst: 2.0 yfirst: 43.0 xsize: 201.0 ysize: 101.0 xinc: 0.08 yinc: 0.07 xnpole: 0.0 ynpole: 0.0
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.017 |
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".