Improvements in LICOM2. Part II: Arctic Circulation
Bibliographic record
Abstract
Abstract A known issue of the National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/Institute of Atmospheric Physics Climate Ocean Model, version 2 (LICOM2, the standard version) is the use of an artificial island in the Arctic Ocean. The computational instability in the polar region seriously influences the model performance in terms of the Arctic circulation. The above-mentioned instability was originally attributed to the converging zonal grids in the polar region. However, this study finds that better computational stability could be achieved in an improved version of LICOM2 (i.e., LICOM2_imp) after four improvements on implementations of the vertical mixing, mesoscale eddy parameterization, and bottom drag schemes. LICOM2_imp is then able to reduce the aforesaid artificial island to a point (i.e., the North Pole). Two experiments of 650-yr integration by LICOM2_imp are carried out using different bathymetries: Exp IMPV0 with the artificial island (88°–90°N) and IMPV1 with only the single pole. The focus of this paper is on the Arctic circulation. Exp IMPV1 gives a more reasonable distribution of salinity and temperature in the Arctic Ocean, a more accurate location of the center of the Beaufort Gyre, and a better net volume flux of the transpolar drift. With more realistic bathymetry in the Arctic Ocean, the biases of net volume fluxes across the Fram Strait, Barents Sea Opening, and Barents Sea Exit are reduced from 1.71 to 1.56, from 0.23 to 0.10, and from 0.71 to 0.45 Sv (1 Sv ≡ 106 m3 s−1), respectively, closer to the observations. The large biases of the net volume fluxes at the Fram Strait in both experiments may be attributed to the closed Nares Strait and other straits/channels in the Canadian Arctic Archipelago.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 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 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".