Precipitation variability and its relationship to hydrologic variability in Alberta
Bibliographic record
Abstract
Abstract By applying wavelet‐based empirical orthogonal function (WEOF) analysis to gridded precipitation ( P ) and empirical orthogonal function (EOF) analysis to gridded air temperature ( T ), potential evapotranspiration (PET), net precipitation (P‐PET) and runoff ( Q ), this paper examines the spatial, temporal and frequency patterns of Alberta's climate variability. It was found that only WEOF‐based precipitation patterns, possibly modulated by El Nino Southern Oscillation (ENSO) and Pacific Decadal Oscillation(PDO), delineated Alberta into four major regions which geographically represent northern Alberta Boreal forests, southern Alberta grasslands and Aspen Parklands and the Rocky Mountains and Foothills. The leading mode of wavelet‐based precipitation variability WPC1 showed that between 1900 and 2000, a wet climate dominated northern Alberta with significant 4–8, 11 and 25‐year periodic cycles, while the second mode WPC2 showed that between 1960 and 2000, southern Alberta grasslands were characterized by decreasing precipitation, dominated by 11‐year cycles, and the last two modes WPC3 and WPC4 were characterized by 4–7 and 25‐year cycles and both delineated regions where moisture from the Pacific Ocean penetrated the Rocky Mountains, accounted for much of the sub‐alpine climate. These results show that WEOF is superior to EOF in delineating Alberta precipitation variability to sub‐regions that more closely agree with its eco‐climate regions. Further, it was found that while WPC2 could not explain runoff variations in southern Alberta, WPC1, WPC3 and WPC4 accounted for runoff variability in their respective sub‐regions. Copyright © 2009 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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".