Trends and variability of the outdoor skating season in Canada during 1951-2005
Bibliographic record
Abstract
Climate change affects a range of human activities, including one of Canada's prime sources of entertainment: ice skating. Whether done recreationally or as hockey, its outdoor component is heavily dependent on weather and climate. Based on information obtained from public works officials from various Canadian cities, I have established a meteorological criterion for the initiation of an outdoor skating season (OSS) as the last day in a sequence of the first three consecutive fall/winter days with a maximum temperature below -5 °C. In addition, I derive a proxy of the OSS length, defined as the total number of days with a maximum temperature below -5 °C after the OSS start date and before the start of March. Using these filters, I have extracted the start dates and the lengths of the OSS for each year during the fifty-five year period 1951-2005 from a comprehensive daily temperature dataset (Vincent et al., 2002). For each station, I created time series of both the OSS start dates and OSS lengths, and calculated the magnitude, sign and statistical significance of the slopes of the best-fit lines to each time series. In order to establish a relationship of the OSS with large-scale climate patterns, I grouped stations into six climatic regions. Depending on location, I then tested each region for correlation with the Pacific North-American teleconnection pattern (PNA) or the North Atlantic Oscillation (NAO), using a composite analysis method. Lastly, I removed the signal due to these climate fluctuations from the OSS start date and length trends in order to determine how much of the variability was caused by these interannual climate oscillations. The results of the study indicate that most stations in British Columbia and southwest Alberta, as well as these in the southern Ontario/Québec region have witnessed a progressively later onset of the OSS over time. The Prairies, northwest Canada, and some Maritime locales show the opposite trend, although the magnitudes of the slopes are smaller. Significance tests on the regression lines show that most of these trends are not significant at the 95% level. However, OSS start dates in western Canada are very well correlated with PNA patterns by happening later on the average whenever PNA is positive and more warm air is channeled towards the west coast; the OSS start dates in eastern Canada show a similar connection with the NAO. The OSS lengths exhibit different trends: five of the six regions show a decrease in OSS length with the only region having experienced a lengthening of the OSS being the Maritimes. The statistical significance of the OSS length slopes is much higher than that of OSS start slopes, and the correlation with the PNA or NAO is similar in both cases. After carrying out the last procedure (removal of the PNA and NAO signals from the OSS start date and length series), I found an increase in the new slopes and their significance for more than half of my geographic regions' OSS start date and length trends.
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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 | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".