Potential changes in climate indices in Alberta under projected global warming of 1.5–5 °C
Bibliographic record
Abstract
Alberta province, Canada The global average surface temperature has continuously warmed at an unprecedentedly rapid rate since the mid-20th century. Employing CMIP6 (Coupled Model Intercomparison Project Phase 6) climate projections, this study suggested a comprehensive framework with state-of-the-art techniques and evaluated potential changes in climate indices under the GMT changes of + 1.5 °C, + 2 °C, + 3 °C, + 4 °C, and + 5 °C in Alberta, Canada. Main finding of this study is that a significant warming trend in annual mean temperature was projected from all of the selected CMIP6 climate projections in Alberta while there was no distinct trend in annual precipitation. Under the GMT changes from + 1.5 °C to + 5 °C, extreme cold temperature indices were warming at a larger rate in response to the GMT warming. In particular, the warming rate of the annual coldest minimum temperature in Alberta was 2.5 times faster than GMT warming. In addition, a potential decrease in summer precipitation was projected under the GMT warming, leading to a drier and warmer summer in the central and southern parts of Alberta. Furthermore, more extreme drought conditions were projected in Alberta under the GMT warming, indicating that the extreme drought conditions are likely to become more common in Alberta along with the GMT warming.
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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 | 0.001 |
| 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".