Convective environments and hazards in Mediterranean cyclones
Bibliographic record
Abstract
In the Mediterranean region the presence of warm sea surface temperatures and of complex topography favour per se the development of deep convection. This study shows how the presence of Mediterranean cyclones (MEDCs) further enhances the frequency of thunderstorms and how the synoptic and mesoscale features around the cyclones’ low-pressure centres organise the distribution of convective environments. The results are based on ERA5 reanalysis environmental variables, hail and lightning probabilities (modeled from ERA5 predictors) and a lightning detection dataset called ATDNet. Furthermore, a recent classification of MEDCs into nine clusters based on upper-level dynamical structure (Givon et al., 2024) serves as a framework for assessing the relationship between cyclone type and convection.For each MEDC cluster, we characterise the frequency, intensity, spatial distribution and time evolution of convective environments and hazards. Convective activity typically develops to the northeast of the cyclone centre and within the warm sector, peaking before the cyclone reaches its minimum central pressure. Among the various cyclone types, small and deep systems occurring during autumn in the Northern Mediterranean exhibit the highest potential for the development of severe convection, followed by weaker cyclone systems propagating mainly in the Southern Mediterranean during transition seasons and summer. We further examine feature objects that correspond with different dynamical processes within the cyclones, finding that regions of warm conveyor belt ascent are more strongly associated with deep convection than cold frontal zones. The pattern holds across all cyclone clusters. These findings advance the understanding of mesoscale processes associated with MEDCs and offer useful insights for improving operational weather forecasting and risk communication regarding MEDC-related hazards.Givon, Y., Hess, O., Flaounas, E., Catto, J. L., Sprenger, M., and Raveh-Rubin, S.: Process-based classification of Mediterranean cyclones using potential vorticity, Weather Clim. Dynam., 5, 133–162, https://doi.org/10.5194/wcd-5-133-2024, 2024.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".