Continuous GPS measurements of postglacial adjustment in Fennoscandia: 2. Modeling results
Bibliographic record
Abstract
Data collected under the auspices of the BIFROST GPS project yield a geographically dense suite of estimates of present‐day, three‐dimensional (3‐D) crustal deformation rates in Fennoscandia [ Johansson et al. , 2002 ]. A preliminary forward analysis of these estimates [ Milne et al. , 2001 ] has indicated that models of ongoing glacial isostatic adjustment (GIA) in response to the final deglaciation event of the current ice age are able to provide an excellent fit to the observed 3‐D velocity field. In this study we revisit our previous GIA analysis by considering a more extensive suite of forward calculations and by performing the first formal joint inversion of the BIFROST rate estimates. To establish insight into the physics of the GIA response in the region, we begin by decomposing a forward prediction into the three contributions associated with the ice, ocean, and rotational forcings. From this analysis we demonstrate that recent advances in postglacial sea level theory, in particular the inclusion of rotational effects and improvements in the treatment of the ocean load in the vicinity of an evolving continental margin, involve peak signals that are larger than the observational uncertainties in the BIFROST network. The forward analysis is completed by presenting predictions for a pair of Fennoscandian ice histories and an extensive suite of viscoelastic Earth models. The former indicates that the BIFROST data set provides a powerful discriminant of such histories. The latter yields bounds on the (assumed constant) upper and lower mantle viscosity (ν UM , ν LM ); specifically, we derive a 95% confidence interval of 5 × 10 20 ≤ ν UM ≤ 10 21 Pa s and 5 × 10 21 ≤ ν LM ≤ 5 × 10 22 Pa s, with some preference for (elastic) lithospheric thickness in excess of 100 km. The main goal of the (Bayesian) inverse analysis is to estimate the radial resolving power of the BIFROST GPS data as a function of depth in the mantle. Assuming a reasonably accurate ice history, we demonstrate that this resolving power varies from ∼200 km near the base of the upper mantle to ∼700 km in the top portion of the lower mantle. We conclude that the BIFROST data are able to resolve structure on radial length scale significantly smaller than a single upper mantle layer. However, these data provide little constraint on viscosity in the bottom half of the mantle. Finally, elements of both the forward and inverse analyses indicate that radial and horizontal velocity estimates provide distinct constraints on mantle viscosity.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".