ON THE DRIVING SOURCES AND VARIABILITY OF NORTH ATLANTIC DEEP WATER
Bibliographic record
Abstract
The rising concentration of anthropogenic heat-trapping gasses has resulted in an energy imbalance in the Earth's climate system. As a consequence of it, an enhanced hydrological cycle and the continuous decline of the ice sheets are expected to increase the freshwater input into the Arctic and Sub-Arctic basins. The input of cold and fresh waters limits vertical mixing processes in the upper ocean, and there is currently a rising concern on how these future changes might impact open ocean deep convection regions. To understand the implications of the global warming related changes on the basins and the waters formed within, it is imperative to have a better understanding of the processes involved in deep water formation. By using a numerical model with horizontal resolutions of 1/4 and 1/12, I investigated the sensitivity and variability of two components of the North Atlantic Deep Water under climate change like and present-day scenarios. I found that: (I) increased Greenland melt and precipitation impact denser Labrador Sea Water (LSW) replenishment; (II) potential decreases in Labrador Sea winter heat loss due to global warming may be a bigger threat to LSW formation than freshwater increase; (III) strong light-to-dense Atlantic Water (AW) transformation driven by heat loss occurs in the boundary currents of the Nordic Seas, with densities reaching that of the overflow waters; (IV) AW entering the Nordic Seas is transformed into overflow waters in the shelf system of the basin within 6 years; (V) along the north Icelandic shelfbreak the transformation is faster with export of the transformed waters occurring in the North Icelandic Jet (NIJ) within 1 year; (VI) a new overturning loop is proposed in this thesis with the North Icelandic Irminger Current (NIIC) being the upper limb and the NIJ the lower limb. Contrary to what has been thought, I found that the transformation of the NIIC waters occurs on and along the west/northwest portion of the Icelandic shelf.
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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 | 0.000 | 0.000 |
| 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".