A new Asian/North American teleconnection linking clustered extreme precipitation from Indian to Canada
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Three consecutive precipitation extremes emerged in November 2021, including India-Sri Lanka flooding, East Asian blizzard, and Canadian floods. Why the catastrophic events occurred successively and whether they will become more frequent as global warming continues are unknown. Here we show they are organized by an intraseasonal Asian/North American (ANA) teleconnection consisting of two cross-Pacific wave trains fortified by dipolar diabatic heating anomalies (“wet India-dry Philippines”). The dipolar heating anomaly is shaped by multi-scale interaction between a quasi-stationary Madden-Julian Oscillation (MJO) episode and a rapidly developed La Niña over the tropical Asian monsoon region. Numerical experiments suggest that the off-equatorial heating dipole can generate the ANA pattern resembling observations, distinct from the equatorial MJO-induced teleconnection and the La Niña-induced Pacific/North American teleconnection. Philippine cooling stimulates the circum-Pacific wave train, while Indian heating produces the eastward-propagating subtropical wave train. These wave trains persistently steered cross-Pacific atmospheric rivers channeling warm-moisture-laden air to the extratropics. We suggest that the ANA teleconnection could be a new route by which multi-scale interaction between the La Niña and quasi-stationary MJO over the tropical Asian monsoon affects extratropical East Asia and North America. This work provides a unique perspective on understanding the origins of increasing collisions of extremes worldwide within a short time as the global climate warms.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it