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Record W7000662991

Global and regional effects of Hudson Bay closure during deglaciation periods

2023· article· en· W7000662991 on OpenAlexaboutno aff

Bibliographic record

VenueDIAL (Catholic University of Leuven) · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsBayDeglaciationNorthern HemisphereSouthern HemisphereClimate changeSea iceGlobal warming
DOInot available

Abstract

fetched live from OpenAlex

During the Quaternary, the Hudson Bay switched between closed (covered by ice sheet) and open (ice sheet-free) condition 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 poorly understood. Using the LOVECLIM1.3 model, here we investigate the global and regional effects of Hudson Bay closure at the beginning of each deglaciation period of the last 800 ka. Sensitivity experiments are performed at nine selected dates at the early stage of the deglaciation periods which are characterized by large Northern Hemisphere (NH) ice sheets, relatively low CO2 and different combinations of astronomical parameters. Two experiments are performed at each date, one with the Hudson Bay open and another with the Hudson Bay closed. Our model results show that the closure of the Hudson Bay could lead to a strengthening of the Atlantic Meridional Overturning Circulation (AMOC), which in turn leads to a warming in the Northern Hemisphere with notable warming in the Labrador Sea and northeast North Atlantic, a cooling in the Southern Hemisphere and a northward shift of the Inter-tropical Convergence Zone (ITCZ). In addition to the large-scale climate changes related to the modification of AMOC, the closure of Hudson Bay also has a great effect on regional climate. For example, there is a cooling over the Hudson Bay and over the southeast of Greenland. Our results also show that 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 for 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.205
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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