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Record W2625444578 · doi:10.1017/jog.2019.22

GlacierMIP – A model intercomparison of global-scale glacier mass-balance models and projections

2019· article· en· W2625444578 on OpenAlexaff
Regine Hock, Rianne Giesen, Yukiko Hirabayashi, Matthias Huss, Valentina Radić, Aimée B. A. Slangen

Bibliographic record

VenueJournal of Glaciology · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of British Columbia
FundersNuclear Safety and Security CommissionNederlandse Organisatie voor Wetenschappelijk OnderzoekBundesministerium für Bildung und ForschungEuropean CommissionNational Aeronautics and Space AdministrationCommonwealth Scientific and Industrial Research OrganisationNational Science Foundation
KeywordsGlacier mass balanceScale (ratio)GlacierEnvironmental scienceClimatologyBalance (ability)GeologyPhysical geographyGeographyCartography

Abstract

fetched live from OpenAlex

ABSTRACT Global-scale 21st-century glacier mass change projections from six published global glacier models are systematically compared as part of the Glacier Model Intercomparison Project. In total 214 projections of annual glacier mass and area forced by 25 General Circulation Models (GCMs) and four Representative Concentration Pathways (RCP) emission scenarios and aggregated into 19 glacier regions are considered. Global mass loss of all glaciers (outside the Antarctic and Greenland ice sheets) by 2100 relative to 2015 averaged over all model runs varies from 18 ± 7% (RCP2.6) to 36 ± 11% (RCP8.5) corresponding to 94 ± 25 and 200 ± 44 mm sea-level equivalent (SLE), respectively. Regional relative mass changes by 2100 correlate linearly with relative area changes. For RCP8.5 three models project global rates of mass loss (multi-GCM means) of >3 mm SLE per year towards the end of the century. Projections vary considerably between regions, and also among the glacier models. Global glacier mass changes per degree global air temperature rise tend to increase with more pronounced warming indicating that mass-balance sensitivities to temperature change are not constant. Differences in glacier mass projections among the models are attributed to differences in model physics, calibration and downscaling procedures, initial ice volumes and varying ensembles of forcing GCMs.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.293

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)0.0000.000

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 head0.024
GPT teacher head0.255
Teacher spread0.231 · 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

Citations17
Published2019
Admission routes1
Has abstractyes

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