The Impact of Climatic Conditions on Seasonal River Discharges in Siberia
Bibliographic record
Abstract
The influences of surface climate conditions and atmospheric circulation on seasonal river discharges of the Ob, Yenisei, and Lena River basins during 1936-95 have been examined and quantified. Climatic variables include seasonal basin-averaged surface air temperatures, precipitation, maximum snow accumulation depth, and starting and ending dates of the basins' continuous snow cover. Atmospheric circulation is represented by the Northern Hemisphere annular mode (NAM) index. The combinations of these climatic and atmospheric variables explain about 31% to 55% of the variance of the annual total discharges of these rivers. On average, climatic and atmospheric variables explain 35% to 69% variance of spring discharges, 34% to 47% variance of summer discharges, 21% to 50% variance of fall discharges, and 18% to 36% variance of winter discharges. This study reveals that the spring thermal condition is most significant for spring discharge and negatively affects summer discharge. Climatic conditions during the previous winter through fall influence fall discharges, while the atmospheric conditions of the previous summer and fall affect winter discharges. Also, winter snow accumulation influences summer and fall discharges of the Ob and Yenisei Rivers but affects winter and spring discharges of the Lena River, suggesting the importance of topography and permafrost conditions to river discharges over high-latitude regions.
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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) | 0.003 | 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".