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Record W4220966791 · doi:10.5194/egusphere-egu22-11569

The influence of Earth’s hypsometry on global sea level through a glacial cycle and into the future

2022· preprint· en· W4220966791 on OpenAlexaff
Vivi Kathrine Pedersen, Natalya Gomez, Gustav Pallisgaard-Olesen, Julius Garbe, Andy Aschwanden, Ricarda Winkelmann, J. X. Mitrovica

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsMcGill University
Fundersnot available
KeywordsGlacial periodPost-glacial reboundGeologyBathymetryElevation (ballistics)OceanographyGeodesyGeomorphologyGeometryMathematics

Abstract

fetched live from OpenAlex

Earth’s topography and bathymetry is shaped by a complex interplay between solid-Earth processes that deform the Earth from within and the surface processes that modify the outer shape of the Earth. At the surface, an ultimate baselevel set by global sea level marks the defining transition from erosion to deposition. Over geological time scales, this baselevel has resulted in a distinct hypsometric distribution (distribution of surface area with elevation), with the highest concentration of surface area focused in a narrow elevation range near present-day sea level. This particular feature in Earth’s hypsometry makes the global land fraction very sensitive to changes in sea level. Indeed, a sea-level change will result in a significant change in the land fraction as dictated by the hypsometric distribution, thereby modulating the very same sea-level change. However, it remains unexplored exactly how sea-level changes have modified the global land fraction over past glacial cycles and into the future. Here we analyse how Earth’s hypsometry has changed over the last glacial cycle as large ice sheets waxed and waned particularly in Scandinavia and North America. These changes in global ice volume resulted in a significant global excursion in sea level, modulated regionally by solid-Earth deformation, gravitational effects, and effects from Earth’s rotation. These changes modified Earth’s hypsometry, and therefore the global land fraction at any given time. Consequently, we can map out how Earth’s hypsometry has influenced global mean sea level (GMSL) over time. To examine this relationship between Earth’s hypsometry and sea level further, we look to the deep future, to a scenario where both the Greenland Ice Sheet and the Antarctic Ice Sheets will melt away completely over multi-millennial timescales. This scenario is not meant to represent a realistic future scenario per se, but it allows us to define the hypsometric GMSL correction needed for any GMSL that the Earth has experienced recently or will experience in the future.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.030
GPT teacher head0.258
Teacher spread0.228 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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