Trends and periodicities in the Canadian Drought Code and their relationships with atmospheric circulation for the southern Canadian boreal forest
Bibliographic record
Abstract
Trends and periodicities in summer drought severity are investigated on a network of Canadian Drought Code (CDC) monthly average indices extending from central Quebec to western Manitoba and covering the instrumental period 19131998. The relationship and coherency between CDC indices and oceanatmosphere circulation patterns are also examined. Trend analyses indicate that drought severity is unchanged in eastern and central Canada. Composite analyses indicate that for most of the corridor, severe drought seasons occur with a combination of positive 500-hPa geopotential height anomalies centered over the Gulf of Alaska and over the Baffin Bay. Additional severe drought seasons develop across the corridor in the presence of positive height anomalies located over or upstream of the affected regions. According to spectral analyses, the North Atlantic and the North Pacific circulation patterns modulate the drought variability at the decadal scale. Our results lead us to conclude that climate warming and the increases in the amount and frequency of precipitation in eastern Canada during the last century had no significant impact on summer drought severity. It is unlikely that linear climate change contributed to the change in the boreal forest dynamics observed over the past 150 years.
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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 | 0.003 |
| 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".