The influence of below-cloud secondary effects on the stable isotope composition of hydrogen and oxygen in precipitation at Calgary, Alberta, Canada
Bibliographic record
Abstract
Stable isotope compositions of hydrogen (δ2H) and oxygen (δ18O) for short-term precipitation samples (n = 436) collected at Calgary, Alberta, Canada, between January 1997 and December 2001 were determined. Linear regression between δ2H and δ18O values of snow and large amount rain samples (≥4 mm) yielded correlation equations δ2H = 7.72 × δ18O + 5.02 and δ2H = 7.50 δ18O + 0.27, respectively. In contrast, correlation equations between δ2H and δ18O values for small amount rain samples (≤4 mm) resulted in progressively lower slope and intercept values with decreasing precipitation. Correlations of isotope data with parameters such as local temperature, relative humidity, and precipitation amount provided evidence that small amount rain samples undergo secondary evaporation accompanied by mass dependent isotope fractionation during their descent from the cloud base to the ground. Hence, the isotope compositions of precipitation at Calgary, and likely also at other locations in the North American Great Plains region, are influenced by below-cloud secondary effects. Since about one-third of the precipitation events in the 5-yr observation period were rain samples accumulating less than 4 mm, below-cloud secondary effects resulted in a slight decrease of slope and intercept values of the local meteoricwater line (δ2H=7.43 × δ18O-2.79) calculated using amount-weighted monthly average δ2H and δ18O values compared to equations based on isotope data for snow and large amount rain events only. The correlation equation (δ2H = 7.11 δ18O-11.60) calculated using δ2H and δ18O values of individual samples (non-amount weighted) yielded the lowest slope and intercept values caused by the significant influence of small amount rain samples.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".