ITRF2014, Earth Figure Changes, and Geocenter Velocity: Implications for GIA and Recent Ice Melting
Bibliographic record
Abstract
Abstract Using a selection of Global Navigation Satellite System vertical velocities from the latest solution of the International Terrestrial Reference Frame (ITRF) ITRF2014, we calculate the degree‐1 and degree‐2 spherical harmonics coefficients (SHC) of the solid Earth figure changes at different dates, with realistic errors that take into account the inhomogeneity of the network. We find that the SHC are globally close to zero except the zonal coefficients, which show values notably larger than those derived from different glacial isostatic adjustment (GIA) models and which have tended to increase during the time span of observations. We show that these differences are most probably due to global recent ice melting (RIM). Assuming elastic RIM deformation, we then investigate the Earth's geocenter velocity and the geoid oblateness time evolution (J2‐rate) derived from our SHC estimations. The obtained geocenter velocity reaches 0.9 ± 0.5 mm/year in 2013 with a z‐component of 0.8 ± 0.4 mm/year, which is slightly larger than previous estimations. We compare our J2‐rate estimations with observations. Our estimations show a similar acceleration in J2 after 2000. However, our estimates are notably larger than the observations. This indicates either that the J2‐rate due to GIA processes is lower than expected (as proposed by Nakada et al., 2015, 2016) or that the deformation induced by RIM is not purely elastic, or both. Finally, we show that viscous relaxation or phase transitions in the mantle transition zone may only partly explain this discrepancy. This raises the question of the accuracy of current mass estimations of RIM and GIA models.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 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".