Quantifying the Relevance of Cyclones for Precipitation Extremes
Bibliographic record
Abstract
Owing to the huge potential impact of precipitation extremes on society, it is important to better understand the mechanisms causing these events, and their variations with respect to a changing climate. In this study, the importance of a particular category of weather systems, namely cyclones, for the occurrence of regional-scale precipitation extremes is quantified globally using the ECMWF Interim reanalysis (ERA-Interim) dataset. Such an event-based climatological approach complements previous case studies, which established the physical relationship between cyclones and heavy precipitation. A high percentage of precipitation extremes is found to be directly related to cyclones. Regional hot spots are identified where this percentage of cyclone-induced precipitation extremes exceeds 80% (e.g., in the Mediterranean region, Newfoundland, near Japan, and over the South China Sea). The results suggest that in these regions changes of heavy precipitation with global warming are specifically sensitive to variations in the dynamical forcing, for example, related to shifts of the storm tracks. Furthermore, properties of cyclones causing extreme precipitation are investigated. In the exit regions of the Northern Hemisphere storm tracks, these cyclones are on average slightly more intense than low pressure systems not associated with precipitation extremes, but no differences with respect to minimum core pressure are found in most other parts of the midlatitudes. The fundamental linkage between cyclones and precipitation extremes may thus provide guidance to forecasters involved in flood prediction, but it is unlikely that forecasting rules based on simple cyclone properties can be established.
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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 | 0.004 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".