Drivers of seasonal hydrography in Disko Bay, Greenland
Bibliographic record
Abstract
Abstract. This study investigates the seasonal dynamics of Disko Bay (Qeqertarsuup Tunua) in west Greenland. On the eastern side, the bay's hydrography is influenced by ice-ocean interactions and exchange with Ilulissat Icefjord (Kangiata Sullua), while on the western side, the bay exchanges waters with Baffin Bay. Since the mid-1990s, this region has experienced ocean warming, sea-ice decline, and the retreat of Greenland's fastest-flowing marine-terminating glacier. Although West Greenland Irminger Water (WGIW) is known to be a significant heat source behind these changes, the timing and pathways of its entry into Disko Bay remain poorly understood. We present a two-year (2022–2024) observational record of Disko Bay hydrography, providing new insights into the seasonal evolution and spatial structure of Polar Water (PW) and WGIW. Each spring, dense WGIW crosses the topographic barrier between Baffin Bay and Disko Bay, filling the Disko Bay basin and producing the highest observed temperature and density at depth. The PW–WGIW boundary shoals to depths shallow enough for WGIW to renew the Ilulissat Icefjord basin. In autumn/winter 2022, an additional episodic renewal coincided with strong upwelling-favourable winds along the west Greenland shelf. While WGIW renewal dominates winter and spring seasonality (a period also marked by sea-ice presence), summer and autumn hydrography are shaped by PW. With the onset of the melt season, a fresh stratified layer forms in the upper 50 m and progressively thickens and extends downward, continuing to freshen and cool through autumn. Beneath this layer, denser PW warms steadily along isopycnals, with spatial analyses indicating an advective pathway transporting this warming signal along the bay's periphery.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".