Multiple Equilibria and Abrupt Transitions in Arctic Summer Sea Ice Extent
Bibliographic record
Abstract
An application of bifurcation theory to the stability of Arctic sea ice cover is described. After reviewing past such efforts, a simple mathematical representation is developed of processes identified as contributing essentially to abrupt decreases in 21st century Arctic summer sea ice extent in climate model simulations of the Community Climate System Model, version 3 (CCSM3). The resulting nonlinear equations admit abrupt sea ice transitions resembling those in CCSM3 and also plausibly represent further gross aspects of simulated Arctic sea ice evolution such as the accelerating decline in summer ice extent in the late 20th and early 21st centuries. Equilibrium solutions to these equations feature multiple equilibria in a physically relevant parameter regime. This enables abrupt changes to be triggered by infinitesimal changes in forcing in the vicinity of the bifurcation or, alternatively, by finite perturbations some distance from the bifurcation, although numerical experiments suggest that abrupt transitions in CCSM3 may arise mainly from the increasing sensitivity of sea ice to fluctuations in ocean heat transport as ice thickness and extent diminish. A caveat is that behavior following a complete seasonal loss of ice cover is sensitive to aspects of the parameterization of ocean shortwave absorption. The objective is to illuminate the essential processes and not to embellish them or mix them up with others which are less important. The many simplifications also make it possible to see how the various processes interact, but also make it difficult to assess the quantitative validity of the argument. If the ideas have value, it will be because they serve to develop intuition. Thorndike [1992] 1.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".