Decadal variability in high northern latitudes as simulated by an intermediate-complexity climate model
Bibliographic record
Abstract
Abstract A 2500 year integration has been performed with a global coupled atmospheric-sea-ice-ocean model of intermediate complexity with the main objective of studying the climate variability in polar regions on decadal time-scales and longer. The atmospheric component is the ECBILT model, a spectral T21 three-level quasi-geostrophic model that includes a representation of horizontal and vertical heat transfers as well as of the hydrological cycle. ECBILT is coupled to the CLIO model, which consists of a primitive-equation free-surface ocean general circulation model and a dynamic-thermodynamic sea-ice model. Comparison of model results with observations shows that the ECBILT-CLIO model is able to reproduce reasonably well the climate of the high northern latitudes. The dominant mode of coupled variability between the atmospheric circulation and sea-ice cover in the simulation consists of an annular mode for geopotential height at 800 hPa and of a dipole between the Barents and Labrador Seas for the sea-ice concentration which are similar to observed patterns of variability. In addition, the simulation displays strong decadal variability in the sea-ice volume, with a significant peak at about 18 years. Positive volume anomalies are caused by (1) a decrease in ice export through Fram Strait associated with more anticyclonic winds at high latitudes, (2) modifications in the freezing/melting rates in the Arctic due to lower air temperature and higher surface albedo, and (3) a weaker heat flux at the ice base in the Barents and Kara seas caused by a lower inflow of warm Atlantic water. Opposite anomalies occur during the volume-decrease phase of the oscillation.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".