Precipitation of southwestern Canada: Wavelet, scaling, multifractal analysis, and teleconnection to climate anomalies
Bibliographic record
Abstract
Using wavelets, statistically significant interannual and interdecadal oscillations that occurred haphazardly have been detected in southwestern (SW) Canadian seasonal precipitation anomalies. At interannual scales, station precipitation anomalies show unstable relations with large‐scale climate anomalies such as the El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Pacific/North America (PNA), East Pacific (EP) and West Pacific (WP) patterns, and the Central North Pacific (CNP) index. Not all significant precipitation activities could be matched by similar activities in one or more climate anomalies considered. Inconsistent wavelet coherence and phase difference between the leading principal components (PC) of regional precipitation anomalies and climate indices as well as weak Pearson's correlations between band‐passed precipitation PCs and climate indices for the 2–3 year and 3–8 year scales provide supporting evidence for unstable precipitation climate relationships at the interannual scale. On the other hand, interdecadal precipitation variability is mainly associated with low‐frequency variability in CNP, PDO and ENSO. Composite analysis of winter precipitation shows that ENSO, PDO, PNA and WP offer better separation of positive and negative precipitation anomalies than EP and CNP. However, the effect of ENSO is found to be stronger than the others. Precipitation power spectrum plots mostly reveal two linear decay regions of different slopes separated by a breakpoint located approximately at 20 to 30 days, while empirical probability plots reveal power law behavior and hyperbolic intermittency in these data, whose correlation dimensions (D2) are between 8 and 9. Different multifractal behaviors are observed among stations because the amount of different rainfall generating mechanisms vary from station to station, as reflected by the haphazard nature of oscillations detected in most precipitation data. Although the leading PCs of winter regional precipitation show modest correlations at zero‐ to three‐season lead times with ENSO and PDO indices, the high D2 values and absence of consistent interannual precipitation activities suggest that prediction of SW Canadian seasonal precipitation by teleconnection with climate indices is likely limited. Adding other predictor fields such as sea surface temperature and/or sea level pressure may be useful.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".