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Record W1863393092 · doi:10.1002/grl.50191

Arctic climate warming and sea ice declines lead to increased storm surge activity

2013· article· en· W1863393092 on OpenAlexafffundabout
Jesse C. Vermaire, Michael F. J. Pisaric, Joshua R. Thienpont, Colin J. Courtney Mustaphi, Steven V. Kokelj, John P. Smol

Bibliographic record

VenueGeophysical Research Letters · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsQueen's UniversityBrock UniversityAboriginal Affairs Northern Dev CanadaCarleton University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaAboriginal Affairs and Northern Development CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsStorm surgeEnvironmental scienceClimate changeGlobal warmingArcticStormSurgeClimatologyCoastal floodSea iceLead (geology)Arctic ice packOceanographyGeologySea level riseGeographyMeteorology

Abstract

fetched live from OpenAlex

Abstract The combined effects of climate warming (i.e., increased storminess, reduced sea ice extent, and rising sea levels) make low‐lying Arctic coastal regions particularly susceptible to storm surges. The Mackenzie Delta, a biologically significant and resource‐rich region in northwestern Canada, is particularly vulnerable to flooding by storm surges. To properly manage the consequences of climate warming for Arctic residents, infrastructure, and ecosystems, a better understanding of the influence of climate change on storm surge activity is required. Here we use particle size analysis of lake sediment records to show that the occurrence and magnitude of storm surges in the outer Mackenzie Delta are significantly related to temperature and that the frequency and intensity of storm surges is increasing. Our results demonstrate the effects of changing climate on storm surge activity and provide a cautionary example of the threat of inundation to low‐lying Arctic coastal environments under future climate warming scenarios.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.029
GPT teacher head0.282
Teacher spread0.253 · 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

Citations101
Published2013
Admission routes3
Has abstractyes

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