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Record W4416094367 · doi:10.5194/cp-22-825-2026

Growth and decay of the Iceland Ice Sheet through the last glacial cycle

2025· preprint· en· W4416094367 on OpenAlexafffund
A. Goffin, Lev Tarasov, Ívar Örn Benediktsson, Joseph M. Licciardi

Bibliographic record

VenueClimate of the past · 2025
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsIce sheetIce-sheet modelIce streamGlacial periodIce shelfArctic ice packSea iceGreenland ice sheetAntarctic sea ice

Abstract

fetched live from OpenAlex

Abstract. Constraining the dynamic evolution of past ice sheets is critical for unravelling their responses to external forcing and feedbacks over long timescales. This is particularly true in the context of marine ice sheet collapse, as this is one of the largest sources of uncertainty for future sea-level rise projections. The Iceland Ice Sheet (IIS) provides an empirically constrained case study for investigating such an instability, having retreated from a predominantly marine-based ice sheet to isolated mountain ice caps during the last deglaciation. However, previous reconstructions of the IIS have been limited by either sparse data or a restricted exploration of model parameter space, lacking a robust quantification of uncertainties. Here, we address this gap by performing a truncated history matching of the last glacial cycle of the IIS. We use the Glacial Systems Model (GSM) constrained by a curated set of geochronological data to generate an envelope of not-ruled-out-yet(NROY) ice sheet histories. Our results indicate that numerous asynchronous ice streams effectively drain ice from the interior to the margins, resulting in an extensive yet relatively thin ice sheet. During its local Last Glacial Maximum (23.6–20.9 ka), the IIS reaches the continental shelf edge in most sectors with a total volume of 0.41 to 0.76 metres equivalent sea level (m e.s.l.). In the most extreme NROY glaciation scenarios, our model reveals an ice bridge connecting the Iceland and Greenland ice over Denmark Strait. We find that accelerated ice discharge (at the grounding line) dominates mass loss during deglaciation. This acceleration is primarily driven by atmospheric warming through a cascade of mechanisms: surface meltwater induces hydrofracturing, leading to both ice shelf disintegration and tidewater calving, which in turn reduces buttressing and triggers rapid ice stream acceleration. The critical role of hydrofracturing in enabling model capture of deglacial data constraints is shown by explicit sensitivity experiments. This thereby supports inclusion of hydrofracturing for modelling of ongoing ice sheet response to climate change.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.491

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.017
GPT teacher head0.256
Teacher spread0.239 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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