Predictability of an Atmospheric Blocking Event that Occurred on 15 December 2005
Bibliographic record
Abstract
Abstract Atmospheric blocking occurred over the Rocky Mountains at 1200 UTC 15 December 2005. The operational medium-range ensemble forecasts of the Canadian Meteorological Center (CMC), the Japan Meteorological Agency (JMA), and the National Centers for Environmental Prediction (NCEP), as initialized at 1200 UTC 10 December 2005, showed remarkable differences regarding this event. All of the NCEP members failed to predict the correct location of the blocking, whereas almost all of the JMA members and most of the CMC members were successful in predicting the correct location. The present study investigated the factors that caused NCEP to incorrectly predict the blocking location, based on an ensemble-based sensitivity analysis and the JMA global spectral model (GSM) multianalysis ensemble forecasts with NCEP, regionally amplified NCEP, and globally amplified NCEP analyses. A sensitive area for the blocking formation was detected over the central North Pacific. In this area, the NCEP control analysis experienced problems in the handling of a cutoff cyclone, and the NCEP initial perturbations were ineffective in reducing uncertainties in the NCEP control analysis. The JMA GSM multianalysis ensemble forecasts revealed that regional amplification of initial perturbations over the sensitive area could lead to further improvements in forecasts over the blocking region without degradation of forecasts over the Northern Hemisphere (NH), whereas the global amplification of initial perturbations could lead to improved forecasts over the blocking region and degraded forecasts over the NH. This finding may suggest that excessive amplification of initial perturbations over nonsensitive areas is undesirable, and that case-dependent rescaling of initial perturbations may be of value compared with climatology-based rescaling, which is widely used in current operational ensemble prediction systems.
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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 | 0.000 | 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) | 0.013 | 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".