The seasonal footprinting mechanism in large ensemble simulations of the second generation Canadian earth system model: uncertainty due to internal climate variability
Bibliographic record
Abstract
Abstract Previous studies indicated that the wintertime North Pacific Oscillation (NPO) could exert marked impacts on the following winter El Niño-Southern Oscillation (ENSO) via the seasonal footprinting mechanism (SFM). Here, we examine this winter NPO-ENSO relationship in a 50-member ensemble of historical simulations conducted with the Canadian Centre for Climate Modeling and Analysis second generation Canadian Earth System Model (CanESM2) over the period of 1950–2005. The observed NPO pattern, featured by a meridional dipole atmospheric anomaly over the North Pacific, can be well reproduced by all of the 50 ensemble members. The multi-member ensemble (MME) mean can well simulate the observed NPO-ENSO relationship, as well as the SFM process. However, there exists a large spread of the results among the 50 members due to internal climate variability. Internal climate variability influences the winter NPO-ENSO relationship through modulating the subtropical center of the NPO. Specifically, the ensemble members with high NPO-ENSO correlations tend to have strong atmospheric anomalies over the subtropical North Pacific in winter. The atmospheric circulation anomaly brings strong sea surface temperature and precipitation anomalies in the tropical central Pacific and westerly wind anomalies over the tropical western Pacific in the following spring. These anomalies sustain in the following seasons and eventually lead to ENSO events in the following winter.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".