An Observational Estimate of Volume and Freshwater Flux Leaving the Arctic Ocean through Nares Strait
Bibliographic record
Abstract
Abstract The Arctic Ocean is an important link in the global hydrological cycle, storing freshwater and releasing it to the North Atlantic Ocean in a variable fashion as pack ice and freshened seawater. An unknown fraction of this return flow passes through Nares Strait between northern Canada and Greenland. Surveys of ocean current and salinity in Nares Strait were completed in the summer of 2003. High-resolution data acquired by ship-based acoustic Doppler current profiler and via hydrographic casts revealed subtidal volume and freshwater fluxes of 0.8 ± 0.3 Sv and –25 ± 12 mSv (Sv = 103 mSv = 106 m3 s−1), respectively. The observations resolved the dominant spatial scale of variability, the internal Rossby radius of deformation (LD ∼9 km), and revealed a complex, yet coherent along-channel flow with a Rossby number of about 0.13, close to geostrophic balance. Approximately one-third of the total volume flux was associated with across-channel slope of the sea surface and two-thirds (68%) with across-channel slope of isopycnal surfaces. During the period of observation, sustained wind from the southwest weakened the average down-channel flow at the surface. The speed of tidal currents exceeded subtidal components by a factor of 2. Tidal signals were resolved and removed from the observations here using two independent methods resolving horizontal and vertical variability of tidal properties, respectively. Tidal current predictions from a barotropic model agreed well with depth-averaged observations in both amplitude and phase. However, because estimates of freshwater flux require accurate surface currents (and salinity), a least squares fitting procedure using velocity data was judged more reliable, since it permits quantification of vertical tidal current variations.
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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 | 0.001 | 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) | 0.001 | 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".