Local artifacts in ice core methane records caused by layered bubble trapping and in situ production: a multi-site investigation
Bibliographic record
Abstract
Abstract. Advances in trace gas analysis allow localised, non-atmospheric features to be resolved in ice cores, superimposed on the coherent atmospheric signal. These high-frequency signals could not have survived the low-pass filter effect that gas diffusion in the firn exerts on the atmospheric history and therefore do not result from changes in the atmospheric composition at the ice sheet surface. Using continuous methane (CH4) records obtained from five polar ice cores, we characterise these non-atmospheric signals and explore their origin. Isolated samples, enriched in CH4 in the Tunu13 (Greenland) record are linked to the presence of melt layers. Melting can enrich the methane concentration due to a solubility effect, but we find that an additional in situ process is required to generate the full magnitude of these anomalies. Furthermore, in all the ice cores studied there is evidence of reproducible, decimetre-scale CH4 variability. Through a series of tests, we demonstrate that this is an artifact of layered bubble trapping in a heterogeneous-density firn column; we use the term “trapping signal” for this phenomenon. The peak-to-peak amplitude of the trapping signal is typically 5 ppb, but may exceed 40 ppb. Signal magnitude increases with atmospheric CH4 growth rate and seasonal density contrast, and decreases with accumulation rate. Significant annual periodicity is present in the CH4 variability of two Greenland ice cores, suggesting that layered gas trapping at these sites is controlled by regular, seasonal variations in the physical properties of the firn. Future analytical campaigns should anticipate high-frequency artifacts at high-melt ice core sites or during time periods with high atmospheric CH4 growth rate in order to avoid misinterpretation of such features as past changes in atmospheric composition.
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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 | 0.000 |
| 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 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".