Climate-Driven Deformation of the Solid Earth from GRACE and GPS
Bibliographic record
Abstract
GRACE data indicate large seasonal variations in gravity that are assumed to be related to climate-driven fluxes of space water. Seasonal redistribution of surface mass should deform the Earth, and our calculations using GRACE data suggest vertical deformations of approx. 13 mm in the region of greatest flux, the Amazon River Basin. To test the GRACE gravity-hydrology connection, we analyzed GPS data acquired from sites in this region. After accounting for degree 1 variations not observable with GRACE, we find that annual deformation measured with GPS correlates highly with predictions calculated from GRACE measurements. These results confirm the variations in surface water sensed by GRACE, which are significantly larger than those predicted by some hydrology models. The results also demonstrate that GRACE can be an important tool for monitoring deformation of the Earth, and suggest that combined analysis of GRACE and GPS may be a useful approach for estimation of geocenter variations.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".