Factors controlling stable isotope composition of precipitation in arid conditions: an observation network in the Tianshan Mountains, central Asia
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Bibliographic record
Abstract
Approximately one-third of the Earth's arid areas are distributed across central Asia. The stable isotope composition of precipitation in this region is affected by its aridity, therefore subject to high evaporation and low precipitation amount. To investigate the factors controlling stable water isotopes in precipitation in arid central Asia, an observation network was established around the Tianshan Mountains in 2012. Based on the 1052 event-based precipitation samples collected at 23 stations during 2012–2013, the spatial distribution and seasonal variation of δD and δ18O in precipitation were investigated. The values of δD and δ 18O are relatively more enriched in the rainfall dominant summer months (from April to October) and depleted in the drier winter months (from November to March) with low D-excess due to subcloud evaporation observed at many of the driest low elevation stations. The local meteoric water line (LMWL) was calculated to be δD=7.36δ 18O – 0.50 (r 2=0.97, p<0.01) based on the event-based samples, and δD=7.60δ 18O+2.66 (r 2=0.98, p<0.01) based on the monthly precipitation-weighted values. In winter, the data indicate an isotopic rain shadow effect whereby rainout leads to depletion of precipitation in the most arid region to the south of the Tianshan Mountains. The values of δ 18O significantly correlate with air temperature for each station, and the best-fit equation is established as δ 18O=0.78T – 16.01 (r 2=0.73, p<0.01). Using daily air temperature and precipitation derived from a 0.5° (latitude)×0.5° (longitude) gridded data set, an isoscape of δ 18O in precipitation was produced based on this observed temperature effect.
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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 it