Subseasonal and Diurnal Variability in Lightning and Storm Activity over the Yangtze River Delta, China, during Mei-yu Season
Bibliographic record
Abstract
Abstract Using 5 years of operational Doppler radar, cloud-to-ground (CG) lightning observations, and National Centers for Environmental Prediction reanalysis data, this study examined the spatial and temporal characteristics of and correlations between summer storm and lightning activity over the Yangtze River Delta (YRD), with a focus on subseasonal variability and diurnal cycles. The spatiotemporal features of storm top, duration, maximum reflectivity, size, and cell-based vertical integrated liquid water were investigated using the Storm Cell Identification and Tracking algorithm. Our results revealed that there was high storm activity over the YRD, with weak diurnal variations during the mei-yu period. Specifically, storms were strongly associated with mei-yu fronts and exhibited a moderate size, duration, and intensity. On average, afternoon storms exhibited stronger reflectivity and higher storm tops than morning storms, as evidenced by the afternoon peak in CG lightning. The storm intensity strengthened in the post-mei-yu period, due to an increase in atmospheric instability; this was accompanied by a higher frequency of CG lighting. The diurnal cycles of storm frequency and CG lightning in the post-mei-yu period followed a unimodal pattern with an afternoon peak. This is attributable to increased thermodynamic instability in the afternoon, as little diurnal variation was observed for wind shear and moisture. An inverse correlation between lightning occurrence and mean peak current (MPC) for negative CG lightning was evident during the pre-mei-yu and mei-yu periods. The diurnal variation in MPC for negative CG lightning agreed well with that for storm intensity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".