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Record W3185797036 · doi:10.1080/11956860.2021.1949819

Numerical modelling of permafrost dynamics under climate change and evolving ground surface conditions: application to an instrumented permafrost mound at Umiujaq, Nunavik (Québec), Canada

2021· article· en· W3185797036 on OpenAlexafffundvenueabout
Julie Perreault, Richard Fortier, John Molson

Bibliographic record

VenueEcoscience · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversité LavalCenter for Northern Studies
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPermafrostThermokarstEnvironmental scienceClimate changeGlobal warmingAdvectionClimatologyAtmospheric sciencesHydrology (agriculture)GeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Numerical simulations were carried out based on a conceptual cryohydrogeological model of a permafrost mound near Umiujaq, Nunavik (Québec), Canada, to assess the impacts of climate warming and changes in surface conditions on permafrost degradation. The 2D model includes groundwater flow, advective-conductive heat transport, phase change and latent heat. Changes in surface conditions which are characteristic of the site were represented empirically in the model by applying spatially- and temporally-variable ground surface temperatures derived from linear regressions between monitored surface and air temperatures. After reaching a transient steady-state condition close to present-day conditions, the simulations were then extended to 2100 under hypothetical climate warming scenarios and using imposed changes in surface conditions consistent with observed on-site evolution. The simulations show that the development of a thermokarst pond and shrubification respectively induce ground warming of up to 0.5°C and 1.5°C, upward migration of the permafrost base by up to 2 and 4 m, and a decrease in the lateral permafrost extent of 1 and 7 m, relative to a reference case without changes in surface conditions. Feedback from permafrost degradation which drives changes in ground surface conditions should be included in future numerical modelling of permafrost dynamics.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
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
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.041
GPT teacher head0.242
Teacher spread0.201 · 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

Citations12
Published2021
Admission routes4
Has abstractyes

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