Linking global circulation model synoptics and precipitation for western North America
Bibliographic record
Abstract
Abstract Synoptic downscaling from global circulation models (GCMs) has been widely used to develop local and regional‐scale future precipitation scenarios under global warming. This paper presents an analysis of the linkages between the Canadian Centre for Climate Modelling and Analysis first version of the Canadian Global Coupled Model (CCCma CGCM1) 2000 model output and local/regional precipitation time series. The GCM 500 hPa geopotential heights were visually classified for synoptic patterns using a geographical information system. The pattern frequencies were statistically compared with historical data from Changnon et al. (1993. Monthly Weather Review 121: 633–647) for the winter period 1961–85. The CGCM1 synoptic frequencies compare favourably with the historical data, and they represent a substantial improvement over the 1992 Canadian Climate Centre Global Circulation Model synoptic climatology output. The CGCM1 output was used to forecast future winter precipitation scenarios for five geographically diverse climate stations in western North America. Copyright © 2002 Royal Meteorological Society.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.002 | 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".