Structure and predictive skill of strong northeasterly wind events using a limited area numerical weather prediction model at Iqaluit, Canada
Bibliographic record
Abstract
Strong northeasterly wind events are infrequent over Baffin Island, but are potentially hazardous for aviation and the local community of Iqaluit (the capital of Nunavut, Canada). Three strong northeasterly wind events in this region are examined in this study, using the Canadian Global Environmental Multiscale-Limited Area Model (GEM-LAM) with a horizontal grid spacing of 2.5 km; in-situ observations; and reanalysis data. The skill of the GEM-LAM in simulating these events is examined. With the exception of one event, the GEM-LAM was successful at predicting the large-scale flow in terms of the circulation pattern, timing of the synoptic set-up and the low-level flow over the Hall Peninsula. The onset and cessation of strong winds and timing of major wind shifts was typically well handled by the model to within ~3 h, but with a tendency to underestimate the peak wind speed. The skill of the surface wind forecasts at Iqaluit is critically dependent on the predicted timing and location of the hydraulic jump and the grid point selected to represent Iqaluit. Examination of the observed and modelled data suggest that the strong northeasterly wind events have several features in common: (1) strong gradient-driven flow across the Hall Peninsula, (2) mean-state critical layer (or reverse shear) over the Hall Peninsula, (3) a low-level inversion, typically above the maximum barrier height immediately upstream of the Hall Peninsula, (4) subcritical flow, typically present upstream of the Hall Peninsula and (5) a hydraulic jump in the vicinity of Frobisher Bay. The modelled atmospheric conditions upwind of the Hall Peninsula immediately prior to the formation of the hydraulic jump (and acceleration of winds over the lee slope) are largely consistent with the prediction of propagating hydraulic jumps presented in the literature.
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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".