The robustness of geodetically derived 1-D Antarctic viscosity models in the presence of complex 3-D viscoelastic Earth structure
Bibliographic record
Abstract
SUMMARY Earth structure beneath the Antarctic exerts an important control on the evolution of the ice sheet. A range of geological and geophysical data sets indicate that this structure is complex, with the western sector characterized by a lithosphere of thickness ∼50–100 km and viscosities within the upper mantle that vary by 2–3 orders of magnitude. Recent analyses of uplift rates estimated using Global Navigation Satellite System (GNSS) observations have inferred 1-D viscosity profiles below West Antarctica discretized into a small set of layers within the upper mantle using forward modelling of glacial isostatic adjustment (GIA). It remains unclear, however, what these 1-D viscosity models represent in an area with complex 3-D mantle structure, and over what geographic length-scale they are applicable. Here, we explore this issue by repeating the same modelling procedure but applied to synthetic uplift rates computed using a realistic model of 3-D viscoelastic Earth structure inferred from seismic tomographic imaging of the region, a finite volume treatment of GIA that captures this complexity, and a loading history of Antarctic ice mass changes inferred over the period 1992–2017. We find differences of up to an order of magnitude between the best-fitting 1-D inferences and regionally averaged depth profiles through the 3-D viscosity field used to generate the synthetics. Additional calculations suggest that this level of disagreement is not systematically improved if one increases the number of observation sites adopted in the analysis. Moreover, the 1-D models inferred from such a procedure are non-unique, that is a broad range of viscosity profiles fit the synthetic uplift rates equally well as a consequence, in part, of correlations between the viscosity values within each layer. While the uplift rate at each GNSS site is sensitive to a unique subspace of the complex, 3-D viscosity field, additional analyses based on rates from subsets of proximal sites showed no consistent improvement in the level of bias in the 1-D inference. We also conclude that the broad, regional-scale uplift field generated with the 3-D model is poorly represented by a prediction based on the best-fitting 1-D Earth model. Future work analysing GNSS data should be extended to include horizontal rates and move towards inversions for 3-D structure that reflect the intrinsic 3-D resolving power of the data.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".