Modeling Wind-Driven Circulation and Landfast Ice-Edge Processes during Polynya Events in Northern Baffin Bay
Bibliographic record
Abstract
Abstract A high-resolution sea ice–ocean numerical model of the North Water polynya has been developed to study the wind-driven circulation during polynya events. An idealized three-layer stratified ocean is used to initialize the model to characterize the baroclinic response to realistic wind and ice conditions. The model general circulation pattern is mainly forced by an along-channel sea level gradient between the Arctic Ocean and Baffin Bay, which determines the magnitude of the southward Baffin Current, and by an across-channel sea level gradient in Baffin Bay, which drives the northward West Greenland Current (WGC). These two currents are found to be anticorrelated to each other in the Smith Sound area. During strong northerly wind events, occurring quite frequently in the winter–spring period in the polynya, nutrient-rich Baffin Bay waters transported by the WGC are forced toward the Greenland shelf, coinciding with upwelling events along the Greenland coast. Whenever an ice bridge is present (i.e., the polynya exists and is substantially open), upwelling also occurs at the landfast ice edge. In such cases, the total upwelling area is increased by an amount that depends on the form of the ice bridge but could easily double during certain years. The baroclinic circulation associated with the upwelling response includes the formation of a cyclonic eddy attached to the ice edge that is generated during strong northerly wind events. Primary production estimations reveal that upwelling during polynya events plays a significant role in the early spring phytoplankton bloom, suggesting that the disappearance of the polynya as a result of climate change may have profound implications for the entire ecosystem.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".