The New Concept of GRACE Gradiometry and the Unravelling of the Mystery of Stripes
Bibliographic record
Abstract
For nearly two decades, the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) missions have been widely used to quantify mass transfers within the Earth. \nWe perform analysis on the on-board measurements, and we find an interesting correlation between space weather dynamics and disturbances of the on-board measurements. An innovative idea for bringing the two GRACE spacecraft into a differential mode is introduced to fully capture the impact of charged particles on the instrumentation. The idea of differential mode is advanced to a method named gradiometer mode that leads to the estimation of gravitational gradients using GRACE Level 1B measurements. GRACE gradiometer mode is shown to be able to capture geophysical signals at multiscale resolution between [8, 128] spherical harmonics. \nBoth GRACE and GRACE-FO suffer from a disturbing artifact, commonly known as longitudinal stripes, whose origin is yet to be determined. The presence of stripes in GRACE gravity models conceals geophysical signals and degrades the capability of the mission to quantify smaller scale mass transfers (< 200 km). In an effort to discover the origin of stripes, we scrutinize the missions instrumentation, twin-spacecraft configuration and orbital characteristics, to conclude that the GRACE spatial sampling pattern is responsible for the stripe artifacts. \nGRACE sampling characteristics are quantified and used to prove that the stripes are sub-Nyquist (pseudo-moir) artifacts. We show that the stripes are the result of oversampling the low frequency geoid along the east-west (latitudinal) direction. The low-frequency geoid modulates the total sampled gravitational signal with a frequency near (m/n)fs, where fs is the sampling frequency of the GRACE ground track bundles along the parallels, and m and n are mutually prime integers, with 2mn. GRACE effective latitudinal sampling frequency is shown to be s=1.14 degrees. We generate synthetic stripes using moir theory and by means of rigorous spectral analysis, it is shown that their spectral and spatial characteristics are very similar to the observed ones.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".