Lithosphere thickness and mantle viscosity estimated from joint inversion of GPS and GRACE-derived radial deformation and gravity rates in North America
Bibliographic record
Abstract
The Global Positioning System (GPS) and the Gravity Recovery and Climate Experiment (GRACE) have been used to respectively determine the Earth's surface deformation and gravity changes associated with glacial isostatic adjustment, which is caused by ongoing stress release of the viscoelastic mantle after removal of the Late Pleistocene ice sheets. Here we present a joint inversion analysis of GPS-derived radial (vertical) deformation and GRACE-derived gravity rates in North America to examine whether the ice sheets (ICE-3G and ICE-5G) and earth models can fit the satellite based observations. The results of joint inversion give an effective lithosphere thickness of 150 km (110–180 km under a statistical confidence level of 80 per cent), an upper-mantle viscosity of 3.7 (2.0–5.0; 90 per cent confidence level) × 1020 Pa s, and a lower-mantle viscosity of 1.9 (1.3–2.6; 90 per cent confidence level) × 1021 Pa s. More sophisticated models such as introducing a transition zone of 400–670 km are not fully resolved with current data sets because there is no significant improvement in fitting observations. Tests of modifying ICE-5G show that a reduction of ice thickness by ∼20 per cent in the area west of Hudson Bay and an increase by ∼40 per cent in the southeast (Quebec region) are required to fit both observed vertical deformation and gravity changes. An additional test from inversion analysis of GRACE-derived geoid rates confirms possible signal loss in the GRACE-derived gravity rates, which could be due to noise reduction methods used in data processing stages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".