A Geodynamically Consistent Approach to Residual Topography and Geoid Anomalies on the Convecting Mantle: Importance of Global Crustal Models
Bibliographic record
Abstract
While the isostatic compensation of crustal thickness and density heterogeneity provides the dominant contribution to Earth’s observed topography, there nonetheless remains a substantial difference (the ‘residual topography’) between these two felds. This difference is a consequence of dynamic processes occurring within the mantle, most notably due to time-dependent vertical surface stresses driven by mantle convection. Mantle convection dynamics also produce differences between the observed geoid and the isostatic geoid generated by crustal heterogeneity: the ‘residual geoid’. The joint consideration of both residual geoid and topography anomalies provides unique and fundamental global constraints on the amplitude and spatial distribution of density anomalies in the convecting mantle.Despite the crucial role of isostasy in determining residual geoid and residual topography, accurate constraints depend heavily on the quality of the isostasy calculations. The classical theory of isostasy relies on a 1 -order treatment of hydrostatic equilibrium, which is not suffciently accurate for the calculation of isostatic geoid anomalies on a compressible, self-gravitating mantle. Consequently, we present a geodynamically consistent approach that is based on the surface loading response (via dynamic kernels) calculated with a viscous flow model that incorporates a fully compressible mantle and core (given by the PREM reference model) with self-gravitation.Another critical issue that remains outstanding is the accuracy inherent in global crustal heterogeneity models. Here we show that the differences between the residual geoid and topography felds predicted using CRUST1.0 (Laske et al. 2012) and the most recent ECM1 (Mooney et al. 2023) crustal heterogeneity models are substantial. We discuss the importance and implications of these differences in the context of determining the most accurate constraints on density anomalies in the convecting mantle.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".