Investigation of the Impacts of Greenland Ice Sheet Melting on the along-Shelf Flow on Greenland Shelves and the Labrador Sea Deep Convection
Bibliographic record
Abstract
Gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) satellite measuring system show that Greenland is losing mass as water is lost to the ocean. Past work has suggested that the freshwater flux from Greenland, particularly along the southeastern coast, may be affecting the Labrador Sea deep convection, a major driver of the world deep ocean circulation. The main objectives of this thesis are to examine (1) the relationship between Greenland freshwater flux and the near-surface Labrador Sea salinity; (2) the response of the Greenland shelf water flow to the freshwater flux from the coast; and (3) to predict when the Labrador Sea deep convection will shut down because of the near-surface Labrador Sea freshening. Using the GRACE results and analysis of Argo float hydrographic data showed that there is a strong correlation between the anomalous annual freshwater flux onto the southeastern Greenland shelf and the freshening of the Labrador Sea several months later. The corresponding regression coefficient is physically reasonable and the delay in freshening is what you would expect based on eddy propagation from the west Greenland coast to the site of Labrador Sea deep convection. Satellite altimeter data was used to estimate the interannual shelf water flow, but the flow trend was too small to be determined. Calculations of the heat flux during winter in the Labrador Sea region of deep convection showed that if the freshening continues at the present rate, in about 31 years the cooling heat flux in water will not be able to overcome the freshwater near-surface buoyancy and deep convection will cease.
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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 | 0.000 | 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 | 0.001 | 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) | 0.000 | 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".