The Lightning Detection Network of China Power Grid has been accumulating a large amount of lightning data. In order to study and obtain the lightning characteristics
we applied the statistics and mining analysis methods as well as the big data analysis methods in recent years to analyze 10 years of lightning data from 2005 to 2014. Analysis results show that the lightning amount in 10 years is about 128 million
and the positive ratio shows a general upward trend with an average value of 7.50%. Lightning activities in all areas are different where the amount in the South China and the cloud-ground flash density(GFD) in the East China are the highest
respectively
and the national average GFD is 1.33 flashes/(km2·a). The lightning current amplitude has a similar distribution regular in each year
and a
b of the fitting curve of cumulative probability is 31.33 k A
2.76
which is very close to the recommended values of IEEE and CIGRE. Moreover
we discussed the relationship between lightning and precipitation of Wuhan and Hangzhou and found that the lighting activities in the years from 2005 to 2008 have the generally same peak as the precipitation
and their monthly distribution shows a moderately strong correlation except for a few years. There are no significant correlations between the positive rate of lightning and the precipitation except for a few years. The correlations between the average lightning current amplitude and the precipitation of the tow cities have good consistence
and are both very weak except individual year in Hangzhou. On the basis of the lightning detection data
integrating the atmospheric electric field
satellite cloud image
and meteorologic radar data
we applied data mining technology to realize the lightning warning through forecasting the movement trend of lightning clusters. The specific examples show that the lead time of lightning warning is about 10 to 30 minutes
the average space error of warning target area is about 5 to 15 km
and the warning effective rate is up to 75% to 85%.