Comparison of the Performance of Different Lightning Jump Algorithms in Beijing

Tian Ye; Yao Wen; Yin Jiali; Qie Xiushu; Cao Haiwei; Li Jin; Yuan Shanfeng; Wang Dongfang

doi:10.11898/1001-7313.20210207

Vol.32, NO.2, 2021

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Article Navigation > Journal of Applied Meteorological Science > 2021 > 32(2): 217-232

Tian Ye, Yao Wen, Yin Jiali, et al. Comparison of the performance of different lightning jump algorithms in Beijing. J Appl Meteor Sci, 2021, 32(2): 217-232. DOI: 10.11898/1001-7313.20210207.

Citation:

Tian Ye, Yao Wen, Yin Jiali, et al. Comparison of the performance of different lightning jump algorithms in Beijing. J Appl Meteor Sci, 2021, 32(2): 217-232. DOI: 10.11898/1001-7313.20210207.

Tian Ye, Yao Wen, Yin Jiali, et al. Comparison of the performance of different lightning jump algorithms in Beijing. J Appl Meteor Sci, 2021, 32(2): 217-232. DOI: 10.11898/1001-7313.20210207.

Citation:

Tian Ye, Yao Wen, Yin Jiali, et al. Comparison of the performance of different lightning jump algorithms in Beijing. J Appl Meteor Sci, 2021, 32(2): 217-232. DOI: 10.11898/1001-7313.20210207.

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Comparison of the Performance of Different Lightning Jump Algorithms in Beijing

DOI: 10.11898/1001-7313.20210207

Tian Ye^{1), 2)},
Yao Wen^{3)
,
,},
Yin Jiali¹⁾,
Qie Xiushu⁴⁾,
Cao Haiwei¹⁾,
Li Jin¹⁾,
Yuan Shanfeng⁴⁾,
Wang Dongfang⁴⁾

1).
Beijing Meteorological Observation Center, Beijing 100089
2).
Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089
3).
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081
4).
Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

Received Date: 2020-09-29
Rev Recd Date: 2020-12-23
Publish Date: 2021-03-31

Abstract

Abstract

Based on S-band Doppler weather radar raw data, the total lightning location data of Beijing Lightning Network (BLNET) and hailfall reports from Beijing Meteorological Service, two lightning jump algorithms, Gatlin algorithm and σ algorithm, with different configurations are compared and analyzed for early warning performance of 177 hailfall events in Beijing from 2015 to 2018. The results show that, the early warnings of different multiples of σ algorithm are quite different, 2σ (in this situation, the current changing rate of total flash exceeds two times of the standard deviation of total flash rate in previous time) has the best performance in the σ algorithm. That is to say, 2σ algorithm has the highest probability of detection (POD) and critical success index (CSI), as well as the lowest false alarm rate (FAR), comparing with σ, 3σ and 4σ algorithms. The early warnings of Gatlin algorithm under different N (which is the amount of samples before current time used to calculate the mean and standard deviation) configurations have little difference, and the early warning efficiency is best when N=6, comparing with N=7, 8, 9 and 10. The POD, FAR and CSI of 2σ algorithm are 80.2%, 41.6%, and 51.1%, respectively. The corresponding results of the Gatlin algorithm with N=6 are 82.5%, 62.0%, and 35.2%, respectively. In addition, the applications of these two algorithms to a multi-cell thunderstorm process and a squall line process are analyzed in detail. The results also show that Gatlin algorithm with N=6 has a slightly higher POD than 2σ algorithm, but its FAR is much higher and its CSI is lower. Considering the evaluation of hail nowcast results by Gatlin algorithm and 2σ algorithm, 2σ lightning jump algorithm is more suitable for hail nowcasting in Beijing. And it is beneficial to improving the application of lightning data to hail nowcasting in Beijing
- lightning jump;
- hail;
- early warning;
- 2σ algorithm;
- strong convection

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References(38)

Figures and Tables

Fig. 1 Distribution map of BLNET stations

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Fig. 2 Comparison of early warning effects of different σ thresholds

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Fig. 3 Comparison of the early warning effects of Gatlin algorithm with different N of D

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图 4 2017年8月8日北京多单体对流系统的雷达组合反射率因子演变

(黑色六角形为降雹点)

Fig. 4 Radar composite reflectivity of a multi-cell convective system across Beijing on 8 Aug 2017

(the black six-pointed star indicates the hailfall position)

DownLoad: Full-Size Img PowerPoint

图 5 2017年8月8日北京多单体对流系统识别结果

(红色圈为产生降雹的单体，黑色六角形为降雹点)

Fig. 5 Identification results of strong convection cells on 8 Aug 2017

(the red polygon marks the hail-producing convection cell, the black six-pointed star indicates the hailfall position)

DownLoad: Full-Size Img PowerPoint

图 6 叠加前后3 min内总闪定位的2017年8月8日北京强对流单体识别结果

(红色圆点代表云闪, 红色×表示负地闪, 红色+表示正地闪;黑色六角形为降雹点，19：48图中插图为分裂单体与总闪定位结果叠加的放大图)

Fig. 6 Identified strong convection cells and the located total flashes in 3 min before and after the corresponding time

(the red dot indicates the intracloud flash, the red × indicates the negative cloud-to-ground flash and the red + indicates the positive cloud-to-ground flash, the black six-pointed star indicates the hailfall position, the illustration is an enlarged view of superposition of the split cell and the total flashes in the figure of 1948 BT)

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Fig. 7 The lightning flash rate of the hail-producing cell of the multi-cell system and total flash rates(the columns) and jump thresholds(the pink curves) derived by 2σ algorithm and Gatlin algorithm

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图 8 2015年8月7日北京飑线过程的雷达组合反射率因子

(黑色六角形为降雹点，数字代表降雹顺序)

Fig. 8 Radar composite reflectivity of a squall line across Beijing on 7 Aug 2015

(the black six-pointed star indicates the hailfall position, the number in each subgraph indicates the sequence of the hailfall events)

DownLoad: Full-Size Img PowerPoint

图 9 飑线过程强对流单体识别结果

(黑色六角形为降雹点，数字代表降雹顺序)

Fig. 9 Identification results of every strong convection cells during the squall line process

(the black six-pointed star indicates the hailfall position, the number indicates the sequence of the hailfall events)

DownLoad: Full-Size Img PowerPoint

Fig. 10 The lightning flash rate of the haill-producing cell of the squall line system and total flash rates(the columns) and jump thresholds(the pink curves) derived by 2σ algorithm and Gatlin algorithm

DownLoad: Full-Size Img PowerPoint

Table 1 The lightning jump information of 2σ algorithm for a squall line process in Beijing on 7 Aug 2015

跃增时刻	降雹时刻	与首次跃增时刻相比得到的预警提前时间/min
16:42，16:48	17:40—17:41	58
17:10，17:16，17:26，17:28，17:40	18:00—18:06	50
18:28	18:50—18:53	22
18:28，18:30，18:52	19:15—19:20	47
18:28，18:30，18:52	19:16—19:17	48
无	19:58—20:01	漏报

DownLoad: Download CSV

Table 2 The lightning jump information of Gatlin algorithm for a squall line process in Beijing on 7 Aug 2015

跃增时刻	降雹时刻	与首次跃增时刻相比得到的预警提前时间/min
16:42，16:48，16:54	17:40—17:41	58
17:00，17:06，17:10，17:16，17:26，17:28，17:34，17:40，17:42	18:00—18:06	60
18:28，18:30，18:32，18:52	18:50—18:53	22
18:56，19:16	19:15—19:20	19
18:56，19:16	19:16—19:17	20
19:28，19:36	19:58—20:01	30

DownLoad: Download CSV

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