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Record W7070624037

The role of blowing snow in the hydrometeorology of the Mackenzie River Basin /

2001· dissertation· en· W7070624037 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2001
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene expression and cancer classification
Canadian institutionsnot available
Fundersnot available
KeywordsSnowHydrometeorologySnowpackArcticSnowmeltMesoscale meteorologySublimation (psychology)Snow field
DOInot available

Abstract

fetched live from OpenAlex

Despite being ubiquitous in the Mackenzie River Basin (MRB) of Canada, the role of snow in its energy and water budgets are still open to much speculation. This thesis presents a multi-scale analysis of the contribution of blowing snow to the hydrometeorology of the MRB. A climatology of adverse wintertime weather events is first presented and demonstrates that blowing snow events are rare within the forested sections of the MRB but become more frequent in the northern parts of the basin covered by Arctic tundra. It is these areas which experience the largest impacts of blowing snow transport and sublimation due to large-scale processes. To further assess the mesoscale and microscale effects of blowing snow to the northern regions of the MRB, the development of a bulk blowing snow model is then described. The single- and double-moment versions of the PIEKTUK blowing snow model are shown to produce equivalent results as a previous spectral version of the numerical model while operating about 100 times faster. The application of the double-moment PIEKTUK model (PIEKTUK-D) to a Canadian Arctic tundra site near the northern tip of the MRB reveals that blowing snow sublimation depletes ≈3 mm snow water equivalent (swe) from the snowpack over a period of 210 days during the winter of 1996/1997 at Trail Valley Creek, Northwest Territories. Various assumptions on the state of the background thermodynamic profiles and their evolution during blowing snow, however, can yield significantly higher (>300%) rates of sublimation over the same period. PIEKTUK-D is then coupled to the Mesoscale Compressible Community (MC2) model for an interactive simulation of a ground blizzard at Trail Valley Creek. This coupled mesoscale simulation reveals that moistening and cooling of near-surface air associated with blowing snow sublimation is observed but mitigated in part by advective and entrainment processes. Combined, blowing snow sublimation and mass divergence are then shown to rem

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score0.811

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.232
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2001
Admission routes1
Has abstractyes

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