Changes in Freshwater Distribution and Pathways in the Arctic Ocean Since 2007 in the Mercator Ocean Global Operational System
Bibliographic record
Abstract
Abstract Low‐salinity waters in the upper Arctic Ocean, referred to as “freshwaters”, are cold and play a major role in isolating the sea ice cover from the heat stored in the salty Atlantic Waters (AW) underneath. We examined changes in Arctic freshwater distribution and circulation since 2007 using the 1/12° global Mercator Ocean operational model. We first evaluated model simulations over the upper water column in the Arctic Ocean, using nearly 20,000 independent in situ temperature‐salinity profiles over the 2007–2020 period. Simulated hydrographic properties and water mass distributions were in good agreement with observations. Comparison with long‐term mooring data in the Bering Strait and Beaufort Gyre highlighted the model's capabilities for reproducing the interannual evolution of Pacific Water properties. Taking advantage of the good performance of the model, we examined the interannual evolution of the freshwater distribution and circulation over 2007–2020. The Beaufort Gyre is the major freshwater reservoir across the full Arctic Ocean. After 2012 the gyre extended northward and increased the freshwater content in the Makarov Basin, near the North Pole. Coincidentally, the freshwater content decreased along the East Siberian slope, along with the AW shoaling, and the Transpolar Drift moved from the Lomonosov Ridge to align with the Mendeleev Ridge. We found that these changes in freshwater distribution were followed in 2015 by a marked change in the export of freshwater from the Arctic Ocean with a reduction in Fram Strait (−30%) and an increase in the western Canadian Archipelago (+16%).
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 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 | 0.005 | 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".