Simulation of an Arctic Ground Blizzard Using a Coupled Blowing Snow–Atmosphere Model
Bibliographic record
Abstract
A ground blizzard occurred from 16 to 18 November 1996 in the northern sectors of the Mackenzie River basin of Canada and the adjacent Beaufort Sea. This hazardous event, accompanied by a low-level jet with wind speeds approaching 20 m s 1 and extensive blowing snow near the surface (but clear sky aloft), is forced by a strong sea level pressure gradient that forms between a rapidly intensifying anticyclone over the Nunavut and Northwest Territories of Canada and an intense depression over the frozen Arctic Ocean. The event is first simulated at a horizontal grid size of 18 km using the uncoupled Canadian Mesoscale Compressible Community (MC2) model. This experiment is shown to capture the rapid anticyclogenesis event within 2 hPa of its central sea level pressure and the blizzard conditions near the Canadian Arctic coastline and the Beaufort Sea. Meteorological conditions observed at Trail Valley Creek (TVC), a small Arctic tundra watershed in which ground blizzard conditions were experienced during the event, are also accurately reproduced by the uncoupled simulation with the notable exception of the blowing snow process. Thus, the mesoscale model is then coupled to the ''PIEKTUK'' blowing snow model, and a second simulation is conducted. This additional experiment reveals the presence of extensive blowing snow associated with a strong low-level jet over TVC and the adjacent frozen Beaufort Sea. Over the 2-day event, blowing snow sublimation and transport combined to erode 1.6 mm snow water equivalent from the surface mass balance of TVC. The concurrent moistening and cooling of near-surface air due to blowing snow sublimation emerge during the blizzard but to a lesser extent than in an idealized modeling framework, as a consequence of entrainment and advective processes. Therefore, blowing snow sublimation rates are evaluated to be 1.8 times larger than in the stand-alone application of the PIEKTUK model to the same data.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".