Impact of the Madden–Julian Oscillation on Wintertime Precipitation in Canada
Bibliographic record
Abstract
Abstract Based on the adjusted daily total precipitation data at Canadian stations and the Climate Prediction Center Merged Analysis of Precipitation (CMAP) data during the most recent 30 Northern Hemisphere winters, the connection between the tropical convection of the Madden–Julian oscillation (MJO) and the intraseasonal variability of precipitation in Canada is investigated. The dominant convection patterns associated with the MJO are represented by the two leading modes of the empirical orthogonal function (EOF) analysis that is applied to the pentad outgoing longwave radiation (OLR) in the equatorial Indian Ocean and western Pacific. The first EOF mode is characterized by a single convection center near the Maritime Continent, whereas the second EOF has an east–west dipole structure with enhanced precipitation over the Indian Ocean and reduced convective activity over the tropical western Pacific. Lagged regression analysis reveals significant precipitation anomalies in Canada associated with the tropical convection of the MJO. Above-normal precipitation starts to occur in the west coast of Canada one pentad after a positive EOF2 phase. In the next two pentads, positive precipitation anomalies extend to a large area of south Canada. At the same time, the northeast region experiences reduced precipitation. For strong MJO events when the principal component of EOF2 exceeds its standard deviation, the precipitation anomaly in the west coast of Canada can reach about 20%–30% of its standard deviation of pentad-to-pentad variability. A linearized global primitive equation model is utilized to assess the cause of the intraseasonal variability in the Northern Hemisphere extratropics and its influence on North American weather associated with the tropical heating of the MJO.
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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 | 0.001 |
| 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 | 0.001 |
| 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 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".