Canada Basin hydrography in the CESM-LE and observations: implications for vertical ocean heat transport in a transitioning sea ice cover
Bibliographic record
Abstract
In recent years, there has been a significant sea ice retreat in the Pacific sector of the Arctic. One possible cause is the increase in ocean heat flux amplified by the ice-albedo feedback. This paper looks at vertical ocean heat transport from waters of Pacific origin and solar heat into the mixed layer and their impact on the sea ice mass balance in the Community Earth System Model - Large Ensemble (CESM-LE). To this end, we focus on two specific periods with observational hydrographic data from the Arctic Ice Dynamics Joint Experiment (1975-76) and Ice-Tethered Profiler (2004-2018). A comparison between simulated and observed salinity and potential temperature profiles highlights two key model biases in all ensemble members: an absence of Pacific Waters in the water column and a deepening of the winter mixed layer in opposition to observations that show a reduction in depth of the mixed layer and a stronger increase in stratification. Results from a one-dimensional vertical heat budget show that remnant solar heat trapped beneath the halocline is mostly ventilated to the surface by mixing before the following melt season, while vertical advection associated with Ekman pumping, even in early fall when the winds are strong and the pack-ice weak, only has a small effect on the vertical heat transport. Furthermore, we estimate from the 1D heat budget a reduction of 1.4 m winter ice growth over three years (the residence time of ice in the Beaufort Gyre) associated with the missing Pacific Waters.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".