Changes in Daily and Extreme Temperature and Precipitation Indices for Canada over the Twentieth Century
Bibliographic record
Abstract
This study examines the trends and variations in several indices of daily and extreme temperature and precipitation in Canada for the periods 1950–2003 and 1900–2003 respectively. The indices are based on homogenized daily temperature and adjusted daily precipitation measurements which are special datasets that include adjustments for site relocation, changes in observing programs and corrections for known instrument changes or measurement program deficiencies. For 1950–2003, the analysis of the temperature indices indicates the occurrence of fewer cold nights, cold days and frost days, and conversely more warm nights, warm days and summer days across the country. The results are generally similar for 1900–2003 but they also include a decrease in the diurnal temperature range in southern Canada and a decrease in the standard deviation of the daily mean temperatures for many stations in western Canada. The analysis of the precipitation indices for 1950–2003 reveals more days with precipitation, a decrease in daily intensity and a decrease in the maximum number of consecutive dry days. The annual total snowfall significantly decreased in the south and increased in the north and north‐east during the second half of the twentieth century. The results are generally similar for 1900–2003. The national series for the century shows an increase in annual snowfall from 1900 to the 1970s followed by a considerable decrease until the 1980s which also corresponds to a pronounced downward trend in the frequency of frost days. No consistent changes were found in most of the indices of extreme precipitation for both periods.
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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 | 0.002 | 0.005 |
| 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".