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Record W2754463559 · doi:10.1002/2017gl074394

Local‐Scale Advection of Sensible and Latent Heat During Snowmelt

2017· article· en· W2754463559 on OpenAlexafffund
Phillip Harder, John W. Pomeroy, Warren Helgason

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsSnowmeltSensible heatLatent heatAdvectionEnvironmental scienceSnowHumidityAtmospheric sciencesClimatologyMeteorologyGeologyGeographyThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract The breakup of snow cover into patches during snowmelt leads to a dynamic, heterogeneous land surface composed of melting snow, and wet and dry soil and plant surfaces. Energy exchange with the atmosphere is therefore complicated by horizontal gradients in surface temperature and humidity as snow surface temperature and humidity are regulated by the phase change of melting snow unlike snow‐free areas. Airflow across these surface transitions results in local‐scale advection of energy that has been documented as sensible heat during snowmelt, while latent heat advection has received scant attention. Herein, results are presented from an experiment measuring near‐surface profiles of air temperature and humidity across snow‐free to snow‐covered transitions that demonstrates that latent heat advection can be the same order of magnitude as sensible heat advection and is therefore an important source of snowmelt energy. Latent heat advection is conditional on an upwind source of water vapor from a wetted snow‐free surface.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.040
GPT teacher head0.284
Teacher spread0.244 · 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

Citations45
Published2017
Admission routes2
Has abstractyes

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