Influence of the solar cycle and stratospheric intrusions to the tritium variation of continental ice layers (Colle Gnifetti, European Alps and EGRIP camp, Greenland)
Bibliographic record
Abstract
Examining continental ice layers accumulated before the nuclear era, when the artificial tritium component can be excluded, enables us to better understand the natural variation of cosmogenic tritium (3H). The extremely sensitive 3He-ingrowth method of 3H analysis allows us to determine low level tritium activities with high accuracy. Here we provide a detailed tritium profile of two shallow ice cores drilled in the European Alps and Greenland.A sensitive tritium profile of the top 33.7 m of the ice accumulation at Colle Gnifetti (Swiss-Italian Alps) is provided. The tritium concentrations of annual ice layers before 1953 vary between 0.050 and 0.145 TU with uncertainties of 0.0019 to 0.0048 TU. The tritium values reconstructed for the time of accumulation are varying between 4 and 10 TU. The long-term pattern of tritium in the ice (mainly before 1940) is in anti-correlation with the sunspot numbers. As the ice is not contaminated with artificial tritium, this change can be strongly attributed to the 11-year cycle of solar magnetic activity. This confirms the existing link between the Solar cycle and the cosmogenic tritium of precipitation [1].On the contrary, in Greenland at the EGRIP camp, the signal of the solar cycle is hardly visible. The natural level of tritium at around 20 TU is disturbed by large spikes (>400 TU). These spikes seem to be randomly distributed in time. There are annual layers which are unaffected. The reason of the high tritium concentration might be the stratospheric moisture input as shown by Fourré et al. (2018) [2]. Stratospheric moisture can be also identified by its 17O-excess pattern. Here we provide the correlation of tritium and 17O, as a hint of the origin of excess tritium. On the other hand, the evaluation of the first results shows that the strength of the stratospheric intrusions qualified by tritium amount seems to be weakening over the last 100 years.[1] Palcsu, L., Morgenstern, U., Sültenfuss, J., Koltai, G., László, E., Temovski, M., Major, Z., Nagy, J.T., Papp, L., Varlam, C., Faurescu, I., Túri, M., Rinyu, L., Czuppon, G., Bottyán, E., Jull, A.J.T. Modulation of Cosmogenic Tritium in Meteoric Precipitation by the 11-year Cycle of Solar Magnetic Field Activity, Scientific Reports 8 (2018) 12813.[2] Fourré, E., Landais, A., Cauquoin, A., Jean-Baptiste, P., Lipenkov, V., Petit J.-R. Tritium Records to Trace Stratospheric Moisture Inputs in Antarctica. Journal of Geophysical Research: Atmospheres 123 (2018), 3009-3018.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".