Atmospheric vorticity sets the basin-scale circulation in Hudson Bay
Bibliographic record
Abstract
Hudson Bay of northern Canada receives upward of 700 km3 of river discharge annually. Cyclonic water circulation in Hudson Bay transports this massive volume of riverine water along the coast toward Hudson Strait and into the Labrador Sea. However, synoptic, seasonal and interannual variability of the freshwater transport in Hudson Bay remains unclear. Using yearlong observations of current velocity profiles, collected from oceanographic moorings deployed in western Hudson Bay from September 2016 to September/October 2017, we examined the role of atmospheric forcing on circulation and freshwater transport in the Bay. Our analysis reveals that the along-shore southeastward current through western Hudson Bay was amplified through the entire water column in response to winds generated by cyclones passing over Hudson Bay toward Baffin Bay and/or the Labrador Sea. An atmospheric vorticity index was used to describe the atmospheric forcing and found to correlate with sea surface height and along-shore currents. We showed that a surface Ekman on-shore transport increases sea surface heights along the coast, producing a cross-slope pressure gradient that drives an along-shore southeastward flow, in the same direction as the wind. Expanding our observations to the bay-wide scale, we confirmed this process of wind-driven water dynamics with (1) satellite altimetry measurements and (2) ocean model simulations. Ultimately, we find that cyclonic wind forcing amplifies cyclonic water circulation in Hudson Bay facilitating the along-shore freshwater transport to Hudson Strait. During periods of positive atmospheric vorticity, this forcing can reduce the residence time of riverine water in Hudson Bay.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".