Diagnosis of the Source and Evolution of Medium-Range Forecast Errors for Extratropical Cyclone Joachim
Bibliographic record
Abstract
Abstract Medium-range forecasts for Cyclone Joachim, an extratropical cyclone that impacted western Europe on 16 December 2011, consistently predicted a high-impact intense cyclone; however, these forecasts failed to verify. The potential source and propagation of forecast errors for this case are diagnosed from the 51-member European Centre for Medium-Range Forecasts Ensemble Prediction System initialized 5 days prior to the cyclone’s landfall. Ensemble members are subdivided into two groups: one that contained the eight members that had the most accurate forecast of Joachim and, the other, the eight members that predicted the most intense cyclone. Composite differences between these two subgroups indicate that the difference between these forecasts originate in tropopause-based subsynoptic waves along a deep trough in the eastern Pacific. These errors move eastward over a northern stream ridge centered on the west coast of North America and modulate the evolution of a trough that dives equatorward out of Canada and is associated with the development of Joachim. Forecast error calculations and relaxation experiments indicate that reducing forecast errors associated with these subsynoptic features leads to more accurate forecasts. These results present further evidence that subsynoptic errors, especially those originating in the warm sector of a cyclone, can be a significant source of downstream forecast errors.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 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".