Effect of Hudson Bay closure on global and regional climate under different astronomical configurations
Bibliographic record
Abstract
During the Quaternary, the Hudson Bay switched between closed (covered by ice sheet) and open (ice sheet-free) conditions due to large variations of ice sheets. However, how the closure and opening of the Hudson Bay have affected the local and global climates is still under-investigated. Using the LOVECLIM1.3 model, we have investigated the effect of the Hudson Bay closure under glacial conditions with different astronomical configurations, greenhouse gases (GHG) concentrations and Northern Hemisphere (NH) ice volume. Our model results show that the closure of the Hudson Bay could lead to a strengthening of the Atlantic Meridional Overturning Circulation (AMOC) due to the increased evaporation minus precipitation over the Labrador Sea which leads to saltier water and stronger deep convection in the Labrador Sea. This in turn leads to a warming in the NH with notable warming in the Labrador Sea and northeast North Atlantic, a cooling in the Southern Hemisphere (SH) and a northward shift of the Inter-tropical Convergence Zone (ITCZ). In addition to the large-scale climate changes, the closure of Hudson Bay also leads to a strong cooling over the Hudson Bay region due to changes of surface properties and a cooling to the southeast of Greenland due to more wind-driven sea ice export from the Arctic. However, the effect of the Hudson Bay closure depends on background climate conditions, and it could weaken or slightly reinforce the effect of the ice sheets under different astronomical configurations.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".