Snow Accumulation Variability Over the West Antarctic Ice Sheet Since 1900: A Comparison of Ice Core Records With ERA‐20C Reanalysis
Bibliographic record
Abstract
Abstract This study uses a set of 37 firn core records over the West Antarctic Ice Sheet (WAIS) to test the performance of the twentieth century from the European Centre for Medium‐Range Weather Forecasts (ERA‐20C) reanalysis for snow accumulation and quantify temporal variability in snow accumulation since 1900. The firn cores are allocated to four geographical areas demarcated by drainage divides (i.e., Antarctic Peninsula (AP), western WAIS, central WAIS, and eastern WAIS) to calculate stacked records of regional snow accumulation. Our results show that the interannual variability in ERA‐20C precipitation minus evaporation (P − E) agrees well with the corresponding ice core snow accumulation composites in each of the four geographical regions, suggesting its skill for simulating snow accumulation changes before the modern satellite era (pre‐1979). Snow accumulation experiences significantly positive trends for the AP and eastern WAIS, a negative trend for the western WAIS, and no significant trend for the central WAIS from 1900 to 2010. The contrasting trends are associated with changes in the large‐scale moisture transport driven by a deepening of the low‐pressure systems and anomalies of sea ice in the Amundsen Sea Low region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".