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Record W4221056816 · doi:10.5194/egusphere-egu22-9837

Monitoring ice-calving at the Astrolabe glacier (Antarctica) with seismological and optical satellite

2022· preprint· en· W4221056816 on OpenAlexaff
Floriane Provost, Dimitri Zigone, Jean‐Philippe Malet, E. Le Meur, Clément Hibert

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSpan (engineering)GlacierLife spanEndocrinologyChemistryBiologyGeologyGeomorphology

Abstract

fetched live from OpenAlex

Better understanding the behaviour of tidewater outlet glaciers fringing marine ice sheets is of paramount importance to simulate Antarctica‘s future response to global warming. Addressing the processes underlying these glaciers dynamics (ice motion, crack propagation, basal melting, sea ice interaction, calving events, etc) is a mean of constraining their ice discharge to the sea and hence the ice sheet global mass balance. We here focus on the Astrolable glacier located in Terre Adélie (140°E, 67°S) near the Dumont d'Urville French research station. In January 2019, a large crack of around 3km length was observed in the western shore of the glacier potentially leading to a calving of ca. 28 km2.The fissure has progressively grown until November 2021 when an iceberg of 20km2 was eventually released. The location of the glacier outlet at the proximity of the Dumont D’Urville French research station is an asset to collect in-situ observations such as GNSS surveys and seismic monitoring. Satellite optical imagery also provides numerous acquisitions from the early nineties till the end of 2021 thanks to the Landsat and Sentinel-2 missions. We used two monitoring techniques: optical remote sensing and seismology to analyze changes in the activity of the glacier outlet. We computed the displacement of the ice surface with MPIC-OPT-ICE service available on the ESA Geohazards Exploitation Platform (GEP) and derived the velocity and strain rates from the archive of multispectral Sentinel-2 imagery from 2017 to the end of 2021. The images of the Landsat mission are used to map the limit of the ice front in order to retrieve the calving cycle of the Astrolabe. We observe that the ice front had significantly advanced toward the sea (4 km) since September 2016 and such an extension has not been observed in the previous years (since 2006) despite minor calving episodes. The joint analysis of the seismological data and the velocity and strain maps are discussed with the recent evolution of the glacier outlet. The strain maps show complex patterns of extension and compression areas. The number of calving events detected in the seismological dataset significantly increased during 2016-2021 in comparison with the period 2012-2016. Since the beginning of 2021, both datasets show an acceleration. The number of calving events increased exponentially from June 2021 until the rupture in November 2021 and the velocity of the ice surface accelerated from 1 m.day-1 to 4 m.day-1 in the part of the glacier that detached afterward. This calving event is the first one of this magnitude ever documented over the Astrolabe glacier.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

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

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 head0.034
GPT teacher head0.237
Teacher spread0.203 · 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 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
Published2022
Admission routes1
Has abstractyes

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