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Record W4388445142 · doi:10.5194/tc-17-4645-2023

Spatially heterogeneous effect of climate warming on the Arctic land ice

2023· article· en· W4388445142 on OpenAlexaboutno aff
Damien Maure, Christoph Kittel, Clara Lambin, Alison Delhasse, Xavier Fettweis

Bibliographic record

Venue˜The œcryosphere · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersHorizon 2020 Framework ProgrammeFonds Wetenschappelijk OnderzoekFonds De La Recherche Scientifique - FNRSFédération Wallonie-BruxellesEuropean Commission
KeywordsArcticArctic ice packCryosphereClimatologyGreenland ice sheetEnvironmental scienceArctic geoengineeringGlobal warmingIce sheetClimate changePhysical geographySea iceGeographyOceanographyGeologyAntarctic sea ice

Abstract

fetched live from OpenAlex

Abstract. Global warming has already substantially altered the Arctic cryosphere. Due to the Arctic warming amplification, the temperature is increasing more strongly, leading to pervasive changes in this area. Recent years were notably marked by melt records over the Greenland Ice Sheet, while other regions such as Svalbard seem to remain less influenced. This raises the question of the current state of the Greenland Ice Sheet and the various ice caps in the Arctic for which few studies are available. Here, we run the regional climate model (RCM) Modèle Atmosphérique Régional (MAR) at a resolution of 6 km over four different domains covering all Arctic land ice to produce a unified surface mass balance product from 1950 to the present day. We also compare our results to large-scale indices to better understand the heterogeneity of the evolutions across the Arctic and their links to recent climate change. We find a sharp decrease of surface mass balance (SMB) over the western Arctic (Canada and Greenland) in relationship with the atmospheric blocking situations that have become more frequent in summer, resulting in a 41 % increase of the melt rate since 1950. This increase is not seen over the Russian Arctic permanent ice areas, where melt rates have increased by only 3 % on average, illustrating a heterogeneity in the Arctic SMB response to global warming.

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 score0.053
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)0.0010.001

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 head0.016
GPT teacher head0.221
Teacher spread0.206 · 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
Published2023
Admission routes1
Has abstractyes

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