Climate change and sea ice: Shipping accessibility on the marine transportation corridor through Hudson Bay and Hudson Strait (1980–2014)
Bibliographic record
Abstract
Shipping traffic has been increasing in Hudson Strait and Hudson Bay and the shipping route through these waters to the Port of Churchill may soon become a federally-designated transportation corridor. A dataset on passive microwave-based sea ice concentration was used to characterize the timing of the ice on the shipping corridor to the Port between 1980 and 2014. Efforts were made to produce results in a readily accessible format for stakeholders of the shipping industry; for example, open water was defined using a sea ice concentration threshold of ≤ 15% and results are presented in terms of real dates instead of anomalies. Between 1980 and 2014, the average breakup date on the corridor was July 4, the average freeze-up date was November 25, and the average length of the open water season was 145 days. However, each of these three variables exhibited significant long-term trends and spatial variability over the 34-year time period. Regression analysis revealed significant linear trends towards earlier breakup (–0.66 days year–1), later freeze-up (+0.52 days year–1), and a longer open water season (+1.14 days year–1) along the shipping corridor between 1980 and 2014. Moreover, the section of the corridor passing through Hudson Strait displayed significantly stronger trends than the two sections in Hudson Bay (i.e., “Hudson Islands” and “Hudson Bay”). As a result, sea ice timing in the Hudson Strait section of the corridor has diverged from the timing in the Hudson Bay sections. For example, the 2010–2014 median length of the open water season was 177 days in Hudson Strait and 153 days in the Hudson Bay sections. Finally, significant linear relationships were observed amongst breakup, freeze-up, and the length of the open water season for all sections of the corridor; correlation analysis suggests that these relationships have greatest impact in Hudson Strait.
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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 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".