Understanding Extreme Precipitation Behaviour in British Columbia's Lower Mainland Using Historical and Proxy Data
Bibliographic record
Abstract
In British Columbia, Pineapple Express storms can lead to flooding, slope failures and negative impacts to water quality. Mitigating the impacts of extreme weather events in a changing climate requires an understanding of how local climate responds to regional-to-global climate forcing patterns. In this study, I use historical and proxy data to identify the distinguishing characteristics of Pineapple Express storms and to develop a tree ring oxygen isotope record (1960-1995) of local climate conditions in the Lower Mainland of British Columbia. I found that high magnitude Pineapple Express storms have significantly higher precipitation and streamflow than other storms types, which result in relatively high contributions of Pineapple Express storms to the annual water budget. As well, Pineapple Express precipitation is characterized by an enriched δ18O isotopic signature when compared to precipitation originating from the North Pacific Ocean. However, differences in source water do not appear to be driving the variability in tree ring δ18O ratios. Instead, tree ring isotopic values exhibit a regional climate pattern that is strongly driven by latitudinal temperature gradients and the Rayleigh distillation effect. Therefore, future warmer conditions may decrease the temperature gradient between the equator and the poles, which can be recorded in the tree ring isotope record. The results also suggest that warmer temperatures due to climate change could result in more active Pineapple Express storm seasons, with multiple PE storms happening over a short period of time. Concurrent storms significantly increase the risk to society because the resulting antecedent saturated soil conditions can trigger precipitation-induced natural hazards.
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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 | 0.004 |
| 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) | 0.002 | 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".