Using the Regional Ocean Modeling System (ROMS) to improve the ocean circulation from a GCM 20th century simulation
Bibliographic record
Abstract
Global coupled climate models are generally capable of reproducing the observed trends in the globally averaged atmospheric temperature. However, the global models do not perform as well on regional scales. Here, we present results from a 20-year, high-resolution ocean model experiment for the Atlantic and Arctic Oceans. The atmospheric forcing is taken from the final 20 years of a twentieth-century control run with a coupled atmosphere–ocean general circulation model. The ocean model results from the regional ocean model are validated using observations of hydrography from repeat cruises in the Barents Sea. Validation is performed for average quantities and for probability distributions in space and time. The validation results reveal that, though the regional model is forced by a coupled global model that has a noticeable sea ice bias in the Barents Sea, the hydrography and its variability are reproduced with an encouraging quality. We attribute this improvement to the realistic transport of warm, salty waters into the Barents Sea in the regional model. These lateral fluxes in the ocean are severely underestimated by the global model. The added value with the regional model that we have documented here lends hope to advance the quality of oceanic climate change impact studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".