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Record W2790818753 · doi:10.5194/tc-13-325-2019

Global glacier volume projections under high-end climate change scenarios

2019· article· en· W2790818753 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venue˜The œcryosphere · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersNatural Environment Research CouncilEuropean CommissionSight Research UK
KeywordsCoupled model intercomparison projectGlacierClimatologyEnvironmental scienceGlacier mass balanceClimate changeGlobal warmingPrecipitationClimate modelRepresentative Concentration PathwaysPopulationAlbedo (alchemy)Elevation (ballistics)Atmospheric sciencesGeologyMeteorologyPhysical geographyGeography

Abstract

fetched live from OpenAlex

Abstract. The Paris agreement aims to hold global warming to well below 2 ∘C and to pursue efforts to limit it to 1.5 ∘C relative to the pre-industrial period. Recent estimates based on population growth and intended carbon emissions from participant countries suggest global warming may exceed this ambitious target. Here we present glacier volume projections for the end of this century, under a range of high-end climate change scenarios, defined as exceeding +2 ∘C global average warming relative to the pre-industrial period. Glacier volume is modelled by developing an elevation-dependent mass balance model for the Joint UK Land Environment Simulator (JULES). To do this, we modify JULES to include glaciated and unglaciated surfaces that can exist at multiple heights within a single grid box. Present-day mass balance is calibrated by tuning albedo, wind speed, precipitation, and temperature lapse rates to obtain the best agreement with observed mass balance profiles. JULES is forced with an ensemble of six Coupled Model Intercomparison Project Phase 5 (CMIP5) models, which were downscaled using the high-resolution HadGEM3-A atmosphere-only global climate model. The CMIP5 models use the RCP8.5 climate change scenario and were selected on the criteria of passing 2 ∘C global average warming during this century. The ensemble mean volume loss at the end of the century plus or minus 1 standard deviation is -64±5 % for all glaciers excluding those on the peripheral of the Antarctic ice sheet. The uncertainty in the multi-model mean is rather small and caused by the sensitivity of HadGEM3-A to the boundary conditions supplied by the CMIP5 models. The regions which lose more than 75 % of their initial volume by the end of the century are Alaska, western Canada and the US, Iceland, Scandinavia, the Russian Arctic, central Europe, Caucasus, high-mountain Asia, low latitudes, southern Andes, and New Zealand. The ensemble mean ice loss expressed in sea level equivalent contribution is 215.2±21.3 mm. The largest contributors to sea level rise are Alaska (44.6±1.1 mm), Arctic Canada north and south (34.9±3.0 mm), the Russian Arctic (33.3±4.8 mm), Greenland (20.1±4.4), high-mountain Asia (combined central Asia, South Asia east and west), (18.0±0.8 mm), southern Andes (14.4±0.1 mm), and Svalbard (17.0±4.6 mm). Including parametric uncertainty in the calibrated mass balance parameters gives an upper bound global volume loss of 281.1 mm of sea level equivalent by the end of the century. Such large ice losses will have inevitable consequences for sea level rise and for water supply in glacier-fed river systems.

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.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.004

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 head0.020
GPT teacher head0.222
Teacher spread0.201 · 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