Variable resolution general circulation models: Stretched‐grid model intercomparison project (SGMIP)
Bibliographic record
Abstract
Variable resolution general circulation models (GCMs) using a global stretched grid with enhanced uniform resolution over the region(s) of interest have proven to be an established approach to regional climate modeling providing an efficient regional downscaling to mesoscales. This approach has been used since the early to mid‐1990s by climate modeling groups from France, the United States, Canada, and Australia, among others, along with or as an alternative to the current widely used nested‐grid approach. Stretched‐grid GCMs are used for continuous/autonomous climate simulations, as are usual GCMs, with the only difference being that variable resolution grids are used instead of more traditional uniform grids. The important advantages of variable resolution stretched‐grid GCMs are that they do not require any lateral boundary conditions/forcing and are free of the associated undesirable computational problems; as a result, they provide self‐consistent interactions between global and regional scales of motion and their associated phenomena as in uniform grid GCMs. The international stretched‐grid model intercomparison project, phase 1 (SGMIP‐1), using variable resolution GCMs developed at major centers/groups in Australia, Canada, France, and the United States, was initiated in 2001 and successfully conducted in 2002–2005. The results of the 12‐year (1987–1998) climate simulations for a major part of North America are available at the SGMIP Web site: http://essic.umd.edu/∼foxrab/sgmip.html. The SGMIP‐1 multimodel ensemble results for the region compare well with reanalysis and observations in terms of spatial and temporal diagnostics. Regional biases for time‐averaged model products are mostly limited to about half (or less) of typical reanalysis errors, i.e., within the uncertainties of the available reanalyses, while a high quality of global circulation is preserved. SGMIP products are available to national and international programs such as the World Meteorological Organization/World Climate Research Program/Working Group on Numerical Experimentation (WMO/WCRP/WGNE).
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".