Low-Level Jets, Orographic Effects, and Extreme Events in Nares Strait: A Model-Based Mesoscale Climatology
Bibliographic record
Abstract
Abstract A mesoscale atmospheric model, nested in operational global numerical weather prediction fields, is used to estimate low-level winds and surface wind stress through Nares Strait, between Ellesmere Island and Greenland, during 2 yr from August 2003 to July 2005. During most of the year, the model low-level winds are dominated by intense, southward along-strait flow, with monthly-mean southward 10-m winds reaching 10 m s−1 in winter. Summertime flow is weak and distributions of hourly along-strait winds during the 2-yr period are strongly bimodal. The strong southward low-level winds are associated with ageostrophic, orographically channeled flow down the pressure gradient from the Lincoln Sea to Baffin Bay and are highly correlated with the pressure difference along Nares Strait. The 2-yr means and leading EOFs of monthly-mean 10-m winds and wind stress place the strongest winds and stress in the southern parts of Smith Sound and of Kennedy Channel, at the openings to Baffin Bay and Kane Basin, at known sites of polynya formation, including the North Water polynya in Smith Sound, suggesting that the locally intensified winds may cause these persistent polynyas. An intense wind event observed in Nares Strait by a field camp, with surface winds exceeding 30 m s−1, generally follows the typical pattern of these low-level flows. Based on the model correlation of winds and pressure difference, a 51-yr time series of estimated winds in Nares Strait is reconstructed from historical surface pressure measurements at Thule, Greenland, and Alert, Canada. The pressure difference and reconstructed wind time series are correlated with the Arctic Oscillation at annual and longer periods, but not on monthly periods.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".