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Record W2102727418 · doi:10.1177/0959683609356583

Climatic and morphometric controls on the altitudinal range of glaciers, British Columbia, Canada

2010· article· en· W2102727418 on OpenAlexafffundabout
Erik Schiefer, Brian Menounos

Bibliographic record

VenueThe Holocene · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of the United Kingdom
KeywordsGlacierPrecipitationGlacier mass balanceAccumulation zoneClimatologyClimate changePhysical geographyGeologyGlacier morphologyCirque glacierTidewater glacier cycleGlacier ice accumulationLittle ice ageIce streamGeographyCryosphereOceanographyMeteorology

Abstract

fetched live from OpenAlex

To examine the relation between climate and glacier extent, we compared gridded, monthly temperature and precipitation data to the altitudinal range of glaciers in British Columbia, Canada. We related glacier relief to ablation season temperature (June—August), accumulation season precipitation (September— March), and morphometric variables that included slope, glacier order, and a shape index for 523 alpine glaciers that ranged from 5 to 15 km 2 in surface area. A 1°C increase in mean June—August temperature equates to a 109 to 182 m decrease in glacier relief, and a 1 mm increase in mean monthly September— March precipitation equates to a 0.78 to 2.20 m increase in glacier relief. The most important morphometric controls on this glacier—climate relation include average surface slope, glacier order (analogous to stream order), and the ratio of upper accumulation area to lower ablation area width, all of which are positively related to glacier relief. We note strong relations between glacier relief and climate in all mountain regions of British Columbia, with glaciers of the interior ranges being most sensitive to spatial climatic variability. We show how our approach can be used to estimate past climatic conditions based on historical ice extents, such as at the ‘Little Ice Age’ maximum, and to predict potential future equilibrium glacier extents in a changed climate regime, such as those predicted by general and regional circulation models.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 head0.013
GPT teacher head0.181
Teacher spread0.168 · 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 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

Citations3
Published2010
Admission routes3
Has abstractyes

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