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Record W2135206546 · doi:10.1002/2015jf003667

Modeling ice dynamic contributions to sea level rise from the Antarctic Peninsula

2015· article· en· W2135206546 on OpenAlexaff
Clemens Schannwell, Nicholas E. Barrand, Valentina Radić

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of British Columbia
FundersUniversity of BirminghamNatural Environment Research CouncilSight Research UK
KeywordsIce shelfAntarctic ice sheetFuture sea levelIce sheetGeologyAntarctic sea iceClimatologyCryospherePeninsulaOceanographySea iceIce streamGeography

Abstract

fetched live from OpenAlex

Abstract The future ice dynamical contribution to sea level rise (SLR) from 199 ice shelf nourishing drainage basins of the Antarctic Peninsula Ice Sheet is simulated, using the British Antarctic Survey Antarctic Peninsula Ice Sheet Model. Simulations of the grounded ice sheet include response to ice shelf collapse, estimated by tracking thermal ice shelf viability limits in 14 Intergovernmental Panel on Climate Change global climate models ensemble temperature projections. Grounding line retreat in response to ice shelf collapse is parameterized with a new multivariate linear regression model utilizing a range of glaciological and geometric predictor variables. Multimodel means project SLR up to 9.4 mm sea level equivalent (SLE) by 2200, and up to 19 mm SLE by 2300. Rates of SLR from individual drainage basins throughout the peninsula are similar to 2100, yet diverge between 2100 and 2300 due to individual basin characteristics. Major contributors to SLR are the outlet glaciers feeding southern George VI Ice Shelf, accounting for >75% of total SLR in some model runs. Ice sheet thinning induced by ice‐shelf removal is large (up to ∼500 m), especially in Palmer Land in the southern Antarctic Peninsula, and may propagate as far as 135 km inland. These results emphasize the importance of the ice dynamical contribution to future sea level of the APIS on decadal to centennial timescales.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.117
GPT teacher head0.354
Teacher spread0.238 · 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 designSimulation or modeling
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

Citations4
Published2015
Admission routes1
Has abstractyes

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