The Response of Extratropical Cyclone Propagation in the Northern Hemisphere to Global Warming
Bibliographic record
Abstract
Abstract Extratropical cyclones (ETCs) are a common source of natural hazards, from heavy rain to high winds, and the direction and speed of ETC propagation influence where impacts occur and for how long. Eighteen models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) are used to examine the response of Northern Hemisphere ETC propagation to global warming. In winter, simulations show that ETCs become slower over North America and the Arctic but faster over the Pacific Ocean and part of Europe. In summer, storm propagation becomes slightly slower throughout much of the midlatitudes (30°–60°N). Trends in both seasons relate closely to the impact of global warming on upper-level (250 hPa) winds and the 850–250-hPa thickness gradient. Wherever local thickness gradients weaken in the future, ETCs travel more slowly; conversely, wherever they strengthen, ETCs travel more quickly. In contrast to past work, we find that winter storm propagation becomes more zonal over the Pacific and Atlantic Oceans, which may link to decreased atmospheric blocking and less-sinuous flow at 500 hPa. The importance of model projections of the 850–250-hPa thickness gradient for meridionality of ETC propagation remains uncertain for these regions. However, for North America, models that project stronger thickness gradients also project less-sinuous flow and more-zonal ETC propagation. Overall, this work highlights strong regional variation in how the speed and direction of ETC propagation, and the upper-level circulation patterns that govern them, respond to continued warming. Significance Statement Extratropical storms are common sources of natural hazards like heavy rain and high winds. In our analysis of projections from 18 climate models, we find that winter storms tend to move more slowly over midlatitude North America and the Arctic as the world warms but move faster over the North Pacific Ocean and part of Europe. Slight slowing of summer storms is projected throughout much of the midlatitudes. When storms move slower, their attendant hazards (like heavy precipitation) last longer for the areas they impact. Further, Atlantic winter storms travel more west to east instead of southwest to northeast, so they impact Iceland less often and the British Isles more often. Changes become more dramatic with each additional degree of global 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".