Constrained Estimates of Externally Forced Past and Future Warming for Canada
Bibliographic record
Abstract
Abstract The Arctic has experienced the most rapid warming on Earth in recent decades. This affects Canada's landmass, which extends well into the Arctic. Nevertheless, limited spatial and temporal observational coverage, combined with large climate model uncertainties, pose challenges to understanding both past and future climate changes in these regions relative to preindustrial conditions. This is particularly challenging in a place like Canada that has insufficient historical data to determine preindustrial reference conditions. Emergent constraints can overcome this limitation by using historical observations for the modern post‐industrial era to constrain estimates of both preindustrial reference levels and future warming. Here we apply a carefully tested Bayesian observational constraint method to simultaneously assess the externally forced historical and future warming in Canada. Testing indicates that the approach reduces bias and uncertainty in historical and future warming estimates, increasing confidence that it may also serve as a basis for developing a broader understanding of climate change in other high‐latitude regions. We estimate that external forcing from human activity, has warmed Canada by 2.2 [1.3, 3.1]°C between the 1850–1900 pre‐industrial period and the recent 2015–2024 decade. Applying these same observational constraints to future climate conditions indicates that Canada will warm to 5.1 [3.2, 7.0]°C above pre‐industrial levels by the end‐of‐century under an intermediate emissions scenario SSP 2‐4.5, and to 6.7 [4.6, 8.9]°C under a high‐emissions scenario SSP 3‐7.0, with the largest warming projected for Northern Canada, followed by Quebec.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".