Evaluation of Lightning Prediction by an Electrification and Discharge Model in Long-Term Forecasting Experiments

Liangtao Xu, Shuang Chen,Wen Yao

Advances in Meteorology(2022)

引用 1|浏览8
暂无评分
摘要
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.
更多
查看译文
关键词
lightning prediction,discharge model,electrification,long-term
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要