Seasonal weather regimes in the North Atlantic region: towards new seasonality?
Bibliographic record
Abstract
European climate variability is shaped by atmospheric dynamics and local physical processes over the North Atlantic region. Both have strong seasonal features. So, a better understanding of their future seasonality is essential to anticipate changes in weather conditions for human and natural systems. We revisit the notion of seasons over the North Atlantic region through the concept of seasonal weather regimes (SWRs), by classifying daily fields of geopotential height at 500 hPa (Z500) without a priori separation of seasons. We use data from the ERA-Interim reanalysis, and from 12 climate models of the fifth phase of the Coupled Model Intercomparison Project. The spatial and temporal variability of SWR structures is investigated, as well as associated patterns of surface air temperatures. Although the climate models have biases, they reproduce structures and evolutions of SWRs similar to the reanalysis over 1979-2017: decreasing frequency of winter conditions, which start later and end earlier, and increasing frequency of summer conditions starting earlier and ending later in the year. These changes are stronger over 1979-2100 than over 1979-2017. By the end of the 21st century, the typical past winter conditions (e.g. 1979-2017) have almost disappeared and correspond to future extreme cold conditions. A new cluster related to summer that was almost absent in 1979-2017 (corresponding to past extreme warm conditions in the past) becomes dominant. To understand whether these changes are linked to uniform Z500 increase or changes in Z500 spatial patterns, we detrend the data (but impose a stationary seasonality) by removing the trend in the seasonal Z500 regional average to define detrended seasonal weather regimes (d-SWRs). The temporal properties of d-SWRs appear almost constant, whereas spatial patterns show evolution. Our results indicate that the evolutions of the SWR temporal features are caused by the regional Z500 trend and that changing spatial patterns in d-SWRs account for the heterogeneity of this trend. Previous research has shown that this large-scale Z500 trend is linked to human influence, suggesting that it drives the changes in seasonality that we find.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".