Coherent Interannual Variations of Springtime Surface Temperature and Temperature Extremes Between Central‐Northern Europe and Northeast Asia
Bibliographic record
Abstract
Abstract This study reveals a strong coherent interannual variation in spring surface air temperature (SAT) and temperature extremes between central‐northern Europe (45–70°N, 0–30°E) and Northeast Asia (40–70°N, 110–140°E). The regional mean spring SAT over the two regions is highly correlated, with a correlation of 0.6 during 1950–2017. Arctic Oscillation (AO) and an atmospheric teleconnection, termed the North Atlantic‐Eurasian (NAE) pattern, both play important roles in connecting SAT anomalies over the two regions. Anticyclonic anomalies are seen over central‐northern Europe and Northeast Asia during positive phases of the spring AO and NAE teleconnections. The associated southerly and westerly wind anomalies to the northwestern side of the anomalous anticyclones lead to surface warming over the two regions via anomalous wind‐induced heat advection from lower latitudes. In addition, a decrease in cloud cover and an accompanying increase in surface downward shortwave radiation also contribute to the coherent SAT warming over central‐northern Europe and Northeast Asia. We suggest that synoptic‐scale eddies forcings are crucial to the maintenance of the spring NAE teleconnection. Atmospheric model experiments indicate that the North Atlantic sea surface temperature anomalies also partly contribute to the maintenance of the NAE‐related atmospheric anomalies over the North Atlantic and European regions. The observed coherent spring SAT variations over central‐northern Europe and Northeast Asia and their associations with the AO and midlatitude atmospheric teleconnections can be reproduced in the long historical simulation of a coupled model. This study has implication for the understanding of concurrent occurrence of extreme temperature events over different regions of Eurasia.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".