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Record W2126084414 · doi:10.1002/2015gl063898

Effects of temperature and precipitation on snowpack variability in the Central Rocky Mountains as a function of elevation

2015· article· en· W2126084414 on OpenAlexafffund
Reinel Sospedra‐Alfonso, Joe R. Melton, William J. Merryfield

Bibliographic record

VenueGeophysical Research Letters · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of VictoriaEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSnowpackElevation (ballistics)SnowLapse ratePrecipitationEnvironmental scienceAtmospheric sciencesClimatologyRange (aeronautics)GeologyMeteorologyGeographyGeomorphology

Abstract

fetched live from OpenAlex

Abstract We employ a regression‐based methodology to study the impact of temperature and precipitation on snowpack variability as a function of elevation in the Central Rocky Mountains. Because of the broad horizontal coverage and thermal heterogeneity of the measurement sites employed, we introduce an elevation correction based on the sites' climatological temperature. For the elevation range investigated (1295–2256 m), and assuming an average atmospheric lapse rate of −6.5°C/km, we find a mostly linear relationship between effective elevation and correlation of temperature or precipitation with snow water equivalent and snowpack duration. We estimate a threshold elevation, 1560 ± 120 m, below (above) which temperature (precipitation) is the main driver of the snowpack. This threshold elevation is robust under a range of assumed atmospheric lapse rates. Locations below this elevation are likely to be affected by projected rising temperatures, with important effects on ecosystems and economic activities dependent on snow.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.168
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.027
GPT teacher head0.277
Teacher spread0.249 · 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.

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

Citations73
Published2015
Admission routes2
Has abstractyes

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