Lightning activity, rainfall and flash flooding – occasional or interrelated events? A case study in the island of Crete
Bibliographic record
Abstract
Abstract. The majority of cyclones passing over Crete in late autumn to early winter originate from southwest, west and northwest and are of varying size and intensity. A number of these cyclones cause flash floods. The present study reports the possible relationships between lighting activity and high precipitation related to flash flood events. In this study an attempt was made to correlate the lightning number and location, recorded by the ZEUS lightning detection system, with the rainfall characteristics for sixteen rain events (4 flood and 12 non-flood events) on the island of Crete, during the period 2008–2009. Spatiotemporal analysis of rain and rain rate with flash count was performed with respect to distance (radius) of flashes from raingauge location at various temporal scales, in order to examine the correlation of accumulated rainfall and lightning activity. The maximum attained statistical significant correlation was obtained within a circular area of an average radius of 15 km around the raingauge, and an average time lag of flash count prior precipitation accumulation of 15 min. The maximum correlation between the lightning and rainfall data is obtained for shorter time lags for the flood events (15 min) than the non-flood events (25 min), that could reflect the faster propagation of flood triggering storms due to high convective activity. Results show increased lightning activity occurring during flood triggering storms, by an average of four times higher. Furthermore, there is evidence that the number of flashes that occur during a precipitation event is related to precipitation depth when the latter is adequate to produce a flood event. Differences between flood and non-flood producing storms need to be further assessed by analyzing more independent parameters, including the synoptic conditions and dominant flash flood hydrological generating processes.
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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) | 0.000 | 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".