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Evaluation of Lightning Prediction by an Electrification and Discharge Model in Long-Term Forecasting Experiments.
- Source :
- Advances in Meteorology; 2/24/2022, p1-13, 13p
- Publication Year :
- 2022
-
Abstract
- Over nearly three rainy seasons of lightning activity in North China, numerical prediction experiments were carried out using the Weather Research and Forecasting model coupled with electrification and discharge schemes (WRF-Electric). The numerical forecast results were evaluated using the neighborhood-based equitable threat score (ETS) and fraction skill score (FSS) verification methods based on nationwide observational lightning data. An algorithm was used to generate the coverage of the total flash (intracloud and cloud-to-ground flashes) by fitting the cloud-to-ground flash data. The numerical results showed that the region of lightning activity could be well predicted by the mesoscale WRF-Electric model, particularly during a 6–12-hour forecasting period. The average ETS score of the 6–12-hour forecasting period was 0.34 for a 20 km neighborhood radius. The predictive skill of the model varied not only monthly but also diurnally. The model showed better forecasting skills during the main rainy season (June–July–August) and at 14 : 00–20 : 00 local time. The predictability of the model was enhanced with increasing thunderstorm scale. On the other hand, the coverage of predicted lightning activity was relatively concentrated, and the lightning flash density was higher than the observations. The main discrepancies in the model prediction were related to the design of the discharge parameterization. Thus, in discharge parameterization, the initial threshold for lightning should be modified according to the model resolution, while the magnitude of the neutralization charge in a single discharge should be referenced to the observational results. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 16879309
- Database :
- Complementary Index
- Journal :
- Advances in Meteorology
- Publication Type :
- Academic Journal
- Accession number :
- 155429875
- Full Text :
- https://doi.org/10.1155/2022/4583030