A Comparison of North American Surface Temperature and Temperature Extreme Anomalies in Association with Various Atmospheric Teleconnection Patterns
Why this work is in the frame
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Bibliographic record
Abstract
The atmospheric teleconnection pattern reflects large-scale variations in the atmospheric wave and jet stream, and has pronounced impacts on climate mean and extremes over various regions. This study compares those patterns that have significant circulation anomalies over the North Pacific–North American–North Atlantic sector, which directly influence surface temperature and temperature extremes over North America. We analyze the pattern associated anomalies of surface temperature and warm and cold extremes over North America, during the northern winter and summer seasons. In particular, we assess the robustness of the regional temperature and temperature extreme anomaly patterns by evaluating the field significance of these anomalies over North America, and quantify the percentages of North American temperature and temperature extreme variances explained by these patterns. The surface temperature anomalies in association with the Pacific–North American pattern (PNA), Tropical–Northern Hemisphere pattern (TNH), North Pacific pattern (NP), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), Western Pacific pattern (WP), circumglobal teleconnection (CGT), and Asian–Bering–North American (ABNA) patterns are similar to those reported in previous studies based on various datasets, indicating the robustness of the results. During winter, the temperature anomaly patterns considered are field significant at the 5% level over North America, except the WP-related one. These pattern associated anomalies explained about 5–15% of the total interannual temperature variance over North America, with relatively high percentages for the ABNA and PNA patterns, and low for the WP pattern. The pattern associated warm and cold extreme anomalies resemble the corresponding surface mean temperature anomaly patterns, with differences mainly in magnitude of the anomalies. Most of the anomalous extreme patterns are field significant at the 5% level, except the WP-related patterns. These extreme anomalies explain about 5–20% of the total interannual variance over North America. During summer, the pattern-related circulation and surface temperature anomalies are weaker than those in winter. Nevertheless, all of the pattern associated temperature anomalies are of field significance at the 5% level over North America, except the PNA-related one, and explain about 5–10% of the interannual variance. In addition, the temperature extreme anomalies, in association with the circulation patterns, are comparable in summer and winter. Over North America, the NP-, WP-, ABNA-, and CGT-associated anomalies of warm extremes are field significant at the 5% level and explain about 5–15% of the interannual variance. Most of the pattern associated cold extreme anomalies are field significant at the 5% level, except the PNA and NAO related anomalies, and also explain about 5–15% of the interannual variance over North America.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it