Atmospherically forced sea-level variability in western Hudson Bay, Canada
Bibliographic record
Abstract
Abstract. In recent years, significant trends toward earlier breakup and later freeze-up of sea ice in Hudson Bay have led to a considerable increase in shipping activity through the Port of Churchill, which is located in western Hudson Bay and is the only deep-water ocean port in the province of Manitoba. Therefore, understanding sea-level variability at the port is an urgent issue crucial for safe navigation and coastal infrastructure. Using tidal gauge data from the port along with an atmospheric reanalysis and Churchill River discharge, we assess environmental factors impacting synoptic to seasonal variability of sea level at Churchill. An atmospheric vorticity index used to describe the wind forcing was found to correlate with sea level at Churchill. Statistical analyses show that, in contrast to earlier studies, local discharge from the Churchill River can only explain up to 5 % of the sea-level variability. The cyclonic wind forcing contributes from 22 % during the ice-covered winter–spring season to 30 % during the ice-free summer–fall season due to cyclone-induced storm surges generated along the coast. Multiple regression analysis revealed that wind forcing and local river discharge combined can explain up to 32 % of the sea-level variability at Churchill. Our analysis further revealed that the seasonal cycle of sea level at Churchill appears to be impacted by the seasonal cycle in atmospheric circulation rather than by the seasonal cycle in local discharge from the Churchill River, particularly post-construction of the Churchill River diversion in 1977. Sea level at Churchill shows positive anomalies for September–November compared to June–August. This seasonal difference was also revealed for the entire Hudson Bay coast using satellite-derived sea-level altimetry. This anomaly was associated with enhanced cyclonic atmospheric circulation during fall, reaching a maximum in November, which forced storm surges along the coast. Complete sea-ice cover during winter impedes momentum transfer from wind stress to the water column, reducing the impact of wind forcing on sea-level variability. Expanding our observations to the bay-wide scale, we confirmed the process of wind-driven sea-level variability with (i) tidal-gauge data from eastern Hudson Bay and (ii) satellite altimetry measurements. Ultimately, we find that cyclonic winds generate sea-level rise along the western and eastern coasts of Hudson Bay at the synoptic and seasonal timescales, suggesting an amplification of the bay-wide cyclonic geostrophic circulation in fall (October–November), when cyclonic vorticity is enhanced, and Hudson Bay is ice-free.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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 teacher head, 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".