Human-induced changes in extreme cold surges across the Northern Hemisphere
Bibliographic record
Abstract
Extreme cold surges, very large temperature drops over a short period of time, have serious impacts on human health, energy supply and ecosystems. While changes in temperature variability and cold extremes in a warming climate are well understood, changes in extreme cold surges and their driving mechanisms are not. Here we show that extreme cold surges have robustly weakened in middle-to-high latitude continents during autumn and winter but have remained almost unchanged in lower latitudes. By diagnosing near-surface thermodynamic budget, we find that this change is mainly induced by anthropogenic forcing. Greenhouse gas forcing decreases the meridional temperature gradient and associated variability in middle-to-high latitudes but has minimal impact in lower latitudes. This leads to similar spatial pattern of changes in nonlinear horizontal temperature advection that dominantly drives the extreme cold surges. Influenced by the same mechanism, extreme cold surges during winter across middle-to-high latitudes will continue to weaken in the future, with an 8%-13% reduction in their strength by the end of the century under the SSP 3-7.0 scenario.
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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 | 0.000 |
| 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) | 0.002 | 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".