Arctic Ocean freshwater composition, pathways and transformations from a passive tracer simulation
Bibliographic record
Abstract
Freshwater (FW) induced transformations in the upper Arctic Ocean were studied using a coupled regional sea ice-ocean model driven by winds and thermodynamic forcing from a reanalysis of data during the period 1948–2011, focusing on the mean state during 1968–2011. Using passive tracers to mark a number of FW sources and sinks, their mean composition, pathways and export were examined. The distribution of the simulated FW height reproduced the known features of the Arctic Ocean and volume-integrated FW content matched climatological estimates reasonably well. Input from Eurasian rivers and extraction by sea-ice formation dominate the composition of the Arctic FW content whilst Pacific water increases in importance in the Canadian Basin. Though pathways generally agreed with previous studies the locus of the Eurasian runoff shelf-basin transport centred at the Alpha-Mendeleyev ridge, shifting the Pacific–Atlantic front eastwards. A strong coupling between tracers representing Eurasian runoff and sea-ice formation showed how water modified on the shelf spreads across the Arctic and mainly exits through the Fram Strait. Transformation to salinity dependent coordinates showed how Atlantic water is modified by both low-salinity shelf and Pacific waters in an estuary-like overturning producing water masses of intermediate salinity that are exported to the Nordic Seas. A total halocline renewal rate of 1.0 Sv, including both shelf-basin exchange and cross-isohaline flux, was estimated from the transports: both components were of equal magnitude. The model's halocline shelf-basin exchange is dominated by runoff and sea-ice processes at the western shelves (the Barents and Kara seas) and Pacific water at the eastern shelves (the Laptev, East Siberian and Chukchi seas).
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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 | 0.000 | 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".