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Record W3185675772 · doi:10.82308/39644

A dynamic approach to the development of a precipitation climatology as applied to Montreal, Québec

2021· article· en· W3185675772 on OpenAlexaboutno aff
Kai Melamed‐Turkish

Bibliographic record

VenueeScholarship@McGill (McGill) · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsnot available
Fundersnot available
KeywordsPrecipitationClimatologyEnvironmental scienceMeteorologyAtmospheric sciencesGeographyGeology

Abstract

fetched live from OpenAlex

This study documents the frequency and intensity of precipitation in Montreal, Canada from 1979–2018 as it relates to the position of 500-hPa troughs, ridges, and inflection points. Upon identifying these features, the 500-hPa geopotential height wave is subdivided into four quadrants in order to isolate the contributions of the temperature and vorticity advection forcing terms in the quasigeostrophic (QG) omega equation. Precipitation is found to be significantly more intense in every season except summer in the quadrant where differential cyclonic vorticity advection (DCVA) and horizontal warm-air advection (WAA) are expected to promote unambiguous QG ascent. In the summer, the average precipitation is still most intense in this quadrant, but not significantly more intense than in the quadrant immediately downstream of the 500-hPa trough where ambiguous QG vertical motion is expected as DCVA and horizontal cold-air advection (CAA) compete. Precipitation in this quadrant is more intense than in the quadrants experiencing differential anticyclonic vorticity advection (DAVA) in every season with significantly higher intensities in spring and fall. Dynamic and thermodynamic properties are also analyzed. Among the conclusions, the quadrants experiencing DCVA exhibit significantly larger values of ascent compared to the two other quadrants and the quadrant with both DCVA and WAA features significantly higher values of equivalent potential temperature compared to the three other quadrants in every season. Odds ratios indicate a statistically significant association between heavy precipitation episodes and the DCVA-WAA quadrant periods. Heavy precipitation episodes in the DCVA-CAA quadrant tend to be associated with a negatively tilted 500-hPa geopotential height pattern in the winter and fall

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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 teacher head, not a consensus.

Study designOther design
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
Published2021
Admission routes1
Has abstractyes

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