The synoptic climate controls on hydrology in the upper reaches of the Peace River Basin. Part I: snow accumulation
Bibliographic record
Abstract
Abstract For most cold region rivers, winter snowpack accumulation is the main contributor to spring run‐off events. This study investigated the synoptic controls on snowpack variability in the upper reaches of the Peace River Basin. An examination of snowpack accumulation at Grande Prairie, Alberta, revealed considerable inter‐annual variability for the period 1963–1996. Moreover, a decadal‐scale shift was evident with the magnitude of the snowpack being significantly reduced after 1976. An eigenvector‐based map‐pattern classification procedure identified 16 patterns, of which 10 are classified as dry (non‐efficient precipitators) and 6 as wet (efficient precipitators). A frequency analysis demonstrated that variances in the occurrence of synoptic patterns were significantly related to variances in the magnitude of the snowpack at Grande Prairie on both an inter‐annual and inter‐decadal basis. Further analysis revealed that variances in the Pacific/North American (PNA) pattern influenced the local synoptic regime with wet (dry) types dominating under the negative (positive) PNA or zonal (meridional) flow. Although the Southern Oscillation Index (SOI) was found to have a significant impact on wet/dry‐type occurrence, it was revealed that El Niño events were associated with average synoptic conditions, while La Niña events were associated with a significant increase (decrease) in wet (dry) type frequency. A storm track analysis further identified that the occurrence of the wet and dry synoptic patterns influences the magnitude and position of surface lows in and around the Peace River Basin, and western Canada. Copyright © 2006 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".