Influence of GIA Uncertainty on Climate Model Evaluation With GRACE/GRACE‐FO Satellite Gravimetry Data
Bibliographic record
Abstract
Abstract Global coupled climate models are in continuous need for evaluation against independent observations to reveal systematic model deficits and uncertainties. Changes in terrestrial water storage (TWS) as measured by satellite gravimetry missions GRACE and GRACE‐FO provide valuable information on wetting and drying trends over the continents. Challenges arising from a comparison of observed and modelled water storage trends are related to gravity observations including non‐water related variations such as, for example, glacial isostatic adjustment (GIA). Therefore, correcting secular changes in the Earth's gravity field caused by ongoing GIA is important for the monitoring of long‐term changes in terrestrial water from GRACE in particular in former ice‐covered regions. By utilizing a new ensemble of 56 individual realizations of GIA signals based on perturbations of mantle viscosities and ice history, we find that many of those alternative GIA corrections change the direction of GRACE‐derived water storage trends, for example, from gaining mass into drying conditions, in particular in Eastern Canada. The change in the sign of the TWS trends subsequently impacts the conclusions drawn from using GRACE as observational basis for the evaluation of climate models as it influences the dis‐/agreement between observed and modelled wetting/drying trends. A modified GIA correction, a combined GRACE/GRACE‐FO data record extending over two decades, and a new generation of climate model experiments leads to substantially larger continental areas where wetting/drying trends currently observed by satellite missions coincide with long‐term predictions obtained from climate model experiments.
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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 | 0.005 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".