Characteristics and causes of Irminger Water variability in the subpolar North Atlantic between 1993 and 2022
Bibliographic record
Abstract
Irminger Water (IW) originates in the subtropical North Atlantic and is transported northeastward with the North Atlantic Current. It is located in the Irminger Sea and the boundary current system (BCS) off Greenland and Labrador. As the warmest and most saline water mass in this region, it impacts glacial melt and convection in the Irminger and Labrador Seas. This thesis focuses on analyzing temporal and spatial variability of IW using the ARMOR3D data set from 1993 to 2022. It adds to analyzing IW in an ocean reanalysis and different model simulations. Utilizing data from ship surveys to the west of Greenland (at eastern AR7W), a local validation of ARMOR3D is performed. Eastern AR7W exhibits IW hydrography and volume transport variability. Seasonal variability results from colder and fresher waters formed during winter convection in the Irminger and Labrador Seas. On multi-year time scales, subpolar gyre changes tied to the North Atlantic Oscillation lead IW volume transports at eastern AR7W by up to three years. The commonly used static IW definitions generate a physically unrealistic boundary between IW and colder, fresher ambient waters. This thesis introduces a new method using non-static thresholds considering large-scale changes in the subpolar North Atlantic. This method infers hydrographic variability in an Irminger Sea subregion into the BCS. Results indicate that the static method overestimates IW volume transports by 1.3\,Sv in saline years and underestimates it 0.9\,Sv in fresh years. Another method, based on local water column hydrography, examines warm, saline water variability in regions where IW is mixed with ambient waters. This thesis provides a new understanding of the characteristics and causes behind IW's spatial and temporal variability. The newly developed methods offer IW variability using a more physical and process-oriented approach of temporally varying hydrographic thresholds.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".