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Record W4415656409 · doi:10.1038/s41467-025-64438-3

Antarctic meltwater alters future projections of climate and sea level

2025· article· en· W4415656409 on OpenAlexaff
Shaina Sadai, Ambarish V. Karmalkar, David Pollard, Yue Dong, Erica M. Lucas, Natalya Gomez, Robert M. DeConto, Alan Condron

Bibliographic record

VenueNature Communications · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsMcGill University
FundersNational Science Foundation
KeywordsMeltwaterAntarctic ice sheetFuture sea levelIce sheetSea iceSea levelCryosphereClimate modelIce-albedo feedback

Abstract

fetched live from OpenAlex

Imperfect understanding of ice sheet-climate interactions poses challenges for projecting the impacts of ice sheet mass loss on future climate and sea level. Here we couple a dynamic Antarctic ice sheet model and global climate model to simulate ice sheet-climate interactions. In our single-model, single-member modeling framework, we find sea level and climate projections are significantly modified from uncoupled simulations neglecting Antarctic meltwater under RCP8.5 and RCP4.5. Antarctic meltwater yields surface air temperatures up to 1.5 °C higher in parts of the Northern Hemisphere, while broadly dampening temperature rise in the Southern Hemisphere. Due to radiative feedback changes, both emissions scenarios have global mean surface temperature warming ~0.3 °C lower in the coupled scenario than the control by 2100, with a maximum anomaly of ~1 °C at 2200 under RCP8.5. This slows Antarctica's contribution to global mean sea level rise. Total Antarctic sea level contributions under RCP8.5 (2100: ~0.3 m, 2200: >3 m) include substantial contributions from East Antarctica, though not under RCP4.5 (2100: ~0.1 m, 2200: >1 m). Regionally, projected sea level is up to 0.9 m higher in the Pacific than the global mean Antarctic contribution under RCP8.5 at 2200.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.279
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueNature Communications→Same topicCryospheric studies and observations→French-language works237,207→