The Diverse Impacts of El Niño on Northeastern Canada and Greenland Surface Air Temperatures
Bibliographic record
Abstract
Abstract El Niño is known to affect Arctic temperature. However, the robustness of the observed relationship between El Niño and Arctic temperature remains debated. Here we reexamine the impacts of El Niño on the Arctic temperature in boreal winter [December–February (DJF)] using reanalysis datasets and atmospheric model experiments. This study shows that extreme El Niño events are accompanied by significant boreal winter cooling over northeastern Canada and Greenland (NECG), while moderate eastern Pacific (MEP) El Niño events are accompanied by significant boreal winter warming in this region. For central Pacific (CP) El Niño events, a cold signal appears in NECG, but with no statistical significance. During extreme El Niño winters, a positive Pacific–North America (PNA)-like pattern is seen in the Pacific, and anomalously negative 200-hPa geopotential height (Z200) strengthening occurs over NECG, which is a response to anomalous strong wave activity originating in the tropical Pacific. El Niño–induced circulation anomalies can further induce NECG cooling via cold temperature advection and decreased downward longwave radiation. In contrast, for the MEP El Niño, the subtropical jet extends zonally from the North Pacific to the North Atlantic, which is accompanied by increased baroclinicity anomalies and favors the propagation of synoptic eddies into the Atlantic, leading to a negative North Atlantic Oscillation (NAO)-like pattern. This in turn could further enhance the positive Z200 anomalies over NECG, resulting in anomalous warming in NECG through warm temperature advection and enhanced downward longwave radiation. A series of atmospheric model experiments simulates the observed circulation changes and associated warming over NECG. Significance Statement This work investigates the different impacts of the three El Niño types on regional Arctic wintertime temperature anomalies based on observations and model experiments. The impacts of El Niño events on northeastern Canada and Greenland temperatures during boreal winter show distinct differences between extreme El Niño and moderate EP El Niño events. These distinct differences can be attributed to the different atmospheric circulation patterns induced by different SST patterns, which can lead to warm (cold) temperature advection and enhanced (decreased) downward longwave radiation. These results highlight the different impacts of extreme and moderate EP El Niños on Arctic temperatures and provide an improved understanding of the impact of El Niños on the Arctic climate.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".