Scenario changes in the climatology of winter midlatitude cyclone activity over eastern North America and the Northwest Atlantic
Bibliographic record
Abstract
The present study explores how midlatitude winter cyclone activity can be modified under warming‐induced conditions due to enhanced greenhouse gas concentrations. We performed simulations with the Canadian Regional Climate Model (CRCM version 3.5) implemented on a domain that covers the Northwest Atlantic and eastern North America. These simulations are driven by control conditions (1975–1994) and high‐CO2 scenario conditions (2040–2059) suggested by the Canadian Climate Centre model, CGCM2 (Second Generation Coupled Global Climate Model), following the IPCC IS92a scenario. Comparisons between model simulations for the control period (1975–1994) and North America Regional analysis (NARR) suggest that both CGCM2 and CRCM reliably reproduce the overall NARR patterns of sea level pressure, tropospheric baroclinicity and Atlantic storm tracks. However, compared to CGCM2 results, CRCM offers an improvement in simulations of the most intense cyclones. Although both models underestimate the track density of intense cyclones, the CGCM2 underestimates are larger than those of CRCM. Under the high‐CO2 climate change scenario, the CRCM and CGCM2 model simulations show similar changes in sea level pressure, surface temperature, and total track density of midlatitude winter cyclones. Although we can see the northwest shift of the dominant Atlantic storm track, it is not statistically significant. Moreover, simulations from both models show a decrease in the total cyclone track density along the Canadian east coast; the decrease is more robust in CRCM simulations than in CGCM2 results. For intense cyclones, CRCM simulations show a slight decrease in the track density, while no such change is found in CGCM2 simulations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".