Lightning Distribution Characteristics And Research For Potential Forecast In Shandong Province

Lightning is a strong atmospheric discharge phenomenon accompanied with the energy release of thunderstorm.Lightning is the basic features of thunderstorm, so the activity of lightning can evolve the development of the thunderstorm in a certain extent. Shandong province is located in the eastern coastal areas of China, the lower reaches of the Yellow River, with the complex and varied terrain and frequently convective activities, which belongs to the area of multiple lightning.In this paper, the location data of flashes in Shandong province from2007to2011(June, July, August) was used, with the method of statistical analysis and EOF, and the analysis of the interannual variation,monthly variation and diurnal variation of lightning frequency and spatial variation characteristics of ground flash density were done.The negative CG lightning was accounted for more than Ninety-eight percent of the total lightning, positive CG lightning accounted for only about One point five percent. The total lightning frequency was increased month by month and reached to maximum in the August, and the change trend of negative lightning was consistent with the total lightning. It was showed that the wave of hourly variation for lightning had the obvious types with double peaks and double valleies. The peaks were respectively at03:00and17:00and the valley values were at10:00and23:00. The change of positive flashes lagged behind the total and negative lightning.In summer,the flash density was greater than0.4(km2.a) through the whole province, density greater than1.6(km2.a) mainly distributed in the central region (Binzhou, Zibo, Laiwu, Zaozhuang and Linyi)and the Northeast of Dongying and Jiaodong area (the big part of Yantai and Qingdao).Moreover,an obvious high value area also existed in Caoxian of Heze city. In the terms of time change of ground flash density,from08:00to14:00, flash density was relatively small,mostly with the0.8(km2.a),the high value area of lightning density greater than1.2(km2.a) were located in the Caoxian of Heze and the central area of Laiwu.From14:00to20:00, the lightning activities strengthened with the lightning frequency increased.The high value areas of ground flash abovel.6(km2.a) were mainly distributed in the Middle and East of Shandong. From20:00to02:00, With the decrease of convection activities, lightning mainly existed in the northwest and Southeast of Shandong area.From02:00to08:00, with the increase of the convective weather processes, the province had multiple regions with lightning density greater than1.6(km2.a).At the aspect of Spatial variation for lightning density spatial changes, there was the same change trend in Shandong province through the analysis of the first eigenvector of the spatial variation,the change in Lunan area, and parts of Yantai and Qingdao was relatively larger; with the analysis of the second eigenvector of lightning density spatial changes,it was found that it was different for secondary changes between the northwest、southwest of Shandong and Jiaodong Peninsula, southern mountain of Shandong.After the study for the lightning current amplitude, it was found that the frequency of negative lightning was in well agreement with the total lightning flash, and the amplitudes for most positive flashes were below65kA, the majority of negative lightning below45kA.The sounding data of Qingdao from2009to2011was used in this section. Then the data was processed by normalization method,50commonly used physical parameters were calculated. The thirty parameters of correlation coefficients greater than0.3with lightning were selected for the construction of forecasting equation. The nonlinear Logistic regression analysis and Bayes discriminant methods were adopted to build the forecast equation. Besides, the prediction results of the two models were compared and analyzed. It was researched that the error rata and foul alarm rate of Logistic regression model was smaller, and the prediction accuracy for the weak thunderstorm was better than that of Bayes prediction model. Finally, the probability of the thunderstorm on June29,2009, was reported using Logistic regression model and the fact was consistent with the frontal forecast.