Geodetic Evidence for Weak Mantle Beneath the Sumatran Backarc and Its Influence on Regional Sea-Level
Bibliographic record
Abstract
Postseismic deformation in the far field following large earthquakes is increasingly recognised as a key factor contributing to regional land height and relative sea-level (RSL) changes. The Sumatran subduction zone provides a unique setting to study this deformation owing to the availability of far-field (600 – 1000 km from the trench) and long-term (>20 years) Global Navigation Satellite System (GNSS) observations. In this study, we model the GNSS-constrained postseismic deformation of multiple great (Mw ≥ 8.0) regional earthquakes using a layered and self-gravitating spherical Earth model. Our results reveal a weak asthenosphere beneath the continental lithosphere in explaining the far-field GNSS observations. We estimated an asthenosphere Maxwell viscosity as low as 𝜂m = 1.5 – 3e18 Pa s. Even assuming the presence of a weaker lithosphere-asthenosphere boundary layer (𝜂m = 1.3 – 2.8e17 Pa s) of 5-10 km thickness, the asthenospheric Maxwell viscosity remains less than 1e19 Pa s. Using these mantle viscosities, we estimated horizontal and vertical postseismic viscoelastic surface deformation over a broader region beyond where GNSS observations are available. We show that a weak backarc asthenosphere leads to relatively large, fast, and extensive postseismic deformation, a conclusion that likely applies to many other subduction zones. The great Sumatran megathrust earthquakes, namely the 2004 Sumatra-Andaman, 2005 Nias-Simeulue, and 2007 Bengkulu events, caused continuous far-field postseismic land subsidence over two decades. The 2012 Mw 8.6 and Mw 8.2 Wharton Basin strike-slip earthquake sequences in the Indian Ocean produced postseismic uplift in the far field, slowing down but not offsetting the ongoing subsidence caused by the great megathrust earthquakes. Our results highlight a critical concern for Southeast Asia’s coastal population, as the regional VLM and RSL rise due to large earthquakes compounds the impacts of climate-driven sea-level changes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".