A full year of extreme sea-ice and atmosphere conditions in the Eurasian Arctic: the OCEAN environment during MOSAiC
Bibliographic record
Abstract
The Arctic Ocean, although remote to most of us, is linked to lower latitudes by way of climate, physics, biology and biogeochemistry. Strongly coupled to the rapidly changing Arctic atmosphere and sea-ice, the ocean is subject to amplification of change amid global trends in climate. The relatively fresh and cold upper mixed-layer in the Arctic basin exhibits a strong seasonal cycle, yet the deeper warm water of Atlantic origin largely stays isolated from the ice. Further, changes in heat, salt and momentum due to exchange with ice and atmosphere cannot penetrate to great depth due to a strong halocline. Nevertheless, we observed changes in the upper water column stratification and mixing, due to storms and freeze-induced brine release during the year-long MOSAiC experiment. This was further expressed by significant variability in (sub)mesoscale processes, including eddies and frontal adjustment. We will present results from ocean observations during the MOSAiC drift using a variety of manually-operated devices and autonomous platforms within several 10s of kilometres from the drifting icebreaker Polarstern. Preliminary analyses of our data highlight a pronounced seasonal cycle in mixed-layer depth and upper ocean stratification characteristics connected to brine release, turbulent events triggered by storms, and geographic background variability. We will further detail the observed full-depth water mass distribution and attempt to untangle temporal and spatial variability. Finally, we will give an overview of Team-OCEAN analyses and interdisciplinary projects.
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 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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".