Three-dimensional velocity variations due to ice mass changes in Greenland – Insights from a compressible glacial isostatic adjustment model
Bibliographic record
Abstract
The lithospheric thickness beneath and around Greenland varies from a few tens of kilometres in offshore regions to several tens of kilometres (up to 200 – 250 km) in land areas. But, due to different datasets and techniques applied in geophysical studies, there are large differences between the different geophysical lithosphere models. As an example, lithosphere models from seismological datasets show generally larger values (above 100 km), while models using gravity or thermal datasets tend to be thinner (values mostly below 100 km). To model the deformation associated with the melting of the Greenland Ice Sheet a detailed lithosphere model is required. Nevertheless, seismologically obtained lithosphere models are the ones usually applied in these so-called glacial isostatic adjustment (GIA) models. Besides, GIA models can be used to provide additional constraints on the lithospheric thickness. Results from most 3D GIA models are compared to observed vertical velocities only, while horizontal velocities are known to be sensitive to the lateral variations of the Earth (e.g., lithospheric thickness). But, horizontal velocities from incompressible GIA models, which are commonly used, are not suitable due to the neglect of material parameter changes related to the dilatation. Compressible GIA models in turn can provide more accurate estimates of the horizontal and vertical viscoelastic deformations induced by ice-mass changes. Here, we use a variety of lithospheric thickness models, obtained from gravity, thermal, and seismological datasets, in a three-dimensional compressible GIA Earth model. The GIA model will be constructed using the finite-element software ABAQUS (Huang et al., under review in GJI) and applying recent ice history models Huy3 and GLAC-GR2a for Greenland in combination with the Little Ice Age deglaciation model by Kjeldsen et al. (2015). We will compare various lithosphere models, including their impact on the modelled 3D velocity field, and compare these against independent GNSS (Global Navigation Satellite System) observations. References: Huang, P., Steffen, R., Steffen, H., Klemann, V., van der Wal, W., Reusen, J., Wu, P., Tanaka, Y., Martinec, Z., Thomas, M. (under review in GJI): A finite element approach to modelling Glacial Isostatic Adjustment on three-dimensional compressible earth models. Geophysical Journal International. Under review. Kjeldsen, K., Korsgaard, N., Bjørk, A. et al. (2015): Spatial and temporal distribution of mass loss from the Greenland Ice Sheet since AD 1900. Nature 528, 396–400, https://doi.org/10.1038/nature16183.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".