Moisture origin and stable isotope characteristics of precipitation in southeast Siberia
Bibliographic record
Abstract
Abstract The paper presents oxygen and hydrogen isotopes of 284 precipitation event samples systematically collected in Irkutsk, in the Baikal region (southeast Siberia), between June 2011 and April 2017. This is the first high‐resolution dataset of stable isotopes of precipitation from this poorly studied region of continental Asia, which has a high potential for isotope‐based palaeoclimate research. The dataset revealed distinct seasonal variations: relatively high δ 18 O (up to −4‰) and δD (up to −40‰) values characterize summer air masses, and lighter isotope composition (−41‰ for δ 18 O and −322‰ for δD) is characteristic of winter precipitation. Our results show that air temperature mainly affects the isotope composition of precipitation, and no significant correlations were obtained for precipitation amount and relative humidity. A new temperature dependence was established for weighted mean monthly precipitation: +0.50‰/°C ( r 2 = 0.83; p <.01; n = 55) for δ 18 O and +3.8‰/°C ( r 2 = 0.83, p < 0.01; n = 55) for δD. Secondary fractionation processes (e.g., contribution of recycled moisture) were identified mainly in summer from low d excess. Backward trajectories assessed with the Hybrid Single‐Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicate that precipitation with the lowest mean δ 18 O and δD values reaches Irkutsk in winter related to moisture transport from the Arctic. Precipitation originating from the west/southwest with the heaviest mean isotope composition reaches Irkutsk in summer, thus representing moisture transport across Eurasia. Generally, moisture transport from the west, that is, the Atlantic Ocean predominates throughout the year. A comparison of our new isotope dataset with simulation results using the European Centre/Hamburg version 5 (ECHAM5)‐wiso climate model reveals a good agreement of variations in δ 18 O ( r 2 = 0.87; p <.01; n = 55) and air temperature ( r 2 = 0.99; p <.01; n = 71). However, the ECHAM5‐wiso model fails to capture observed variations in d excess ( r 2 = 0.14; p < 0.01; n = 55). This disagreement can be partly explained by a model deficit of capturing regional hydrological processes associated with secondary moisture supply in summer.
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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) | 0.001 | 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".