基于闪电聚类方法的西北太平洋区域雷暴活动特征

周鑫; 张文娟; 张义军; 孙秀斌; 郑栋; 姚雯

doi:10.16032/j.issn.1004-4965.2021.047

基于闪电聚类方法的西北太平洋区域雷暴活动特征

doi: 10.16032/j.issn.1004-4965.2021.047

周鑫^{1, 2},
张文娟¹,
张义军^{3, 4, ,},
孙秀斌²,
郑栋¹,
姚雯¹

1.
中国气象科学研究院灾害天气国家重点实验室, 北京 100081
2.
成都信息工程大学电子工程学院, 四川成都 610225
3.
复旦大学大气与海洋科学系/大气科学研究院, 上海 200438
4.
复旦大学海洋气象灾害联合实验室, 上海 200438

基金项目:

国家重点研发计划项目 2019YFC1510103

中国气象科学研究院基本科研业务费重点项目 2020Z009

详细信息

通讯作者:
张义军, 男, 河北省人, 博士, 研究员, 主要从事大气电学研究。E-mail: zhangyijun@fudan.edu.cn

中图分类号: P446
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- 被引次数: 0
出版历程
- 收稿日期: 2020-11-24
- 修回日期: 2021-05-08
- 网络出版日期: 2021-09-27
- 刊出日期: 2021-06-01

CHARACTERISTICS OF THUNDERSTORM ACTIVITY IN THE NORTHWEST PACIFIC BASED ON LIGHTNING CLUSTERING METHOD

ZHOU Xin^{1, 2},
ZHANG Wenjuan¹,
ZHANG Yijun^{3, 4
, ,},
SUN Xiubin²,
ZHENG Dong¹,
YAO Wen¹

1.
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
2.
College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China
3.
Department of Atmospheric and Oceanic Sciences/Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
4.
Joint Laboratory of Marine Meteorological Disasters, Fudan University, Shanghai 200438, China

摘要

摘要: 利用2010—2018年全球闪电定位网(WWLLN)观测资料, 采用基于闪电密度的空间聚类算法(DBSCAN)建立了西北太平洋地区雷暴数据集, 研究了该区域雷暴的时空分布特征, 并进行海陆差异对比。研究结果表明, 在合理设定DBSCAN参数阈值的条件下, 基于WWLLN闪电聚类的雷暴与天气雷达观测在时空分布和过程演变上具有一致性。西北太平洋区域的日均雷暴数为3 869, 雷暴的闪电密集区平均面积为557.91km², 平均延展尺度为31.99 km, 平均闪电频次为33 str/(h·thu)。在空间分布上, 东南亚沿海地区与热带岛屿的雷暴活动最强, 南海的雷暴活动强于深海。距离海岸线越近的海域其雷暴面积越大。在季节分布上, 整个区域雷暴活动在夏季(6—8月)达到全年最强, 南海雷暴活动6月达到峰值, 而日本东部近海海域的雷暴活动则在冬季达到最强。我国内陆南方地区雷暴3月开始显著增多, 雷暴平均面积达到最大, 但雷暴平均闪电频次5月才达到峰值。在日变化方面, 陆地雷暴活动呈现典型的单峰型特征, 大部分雷暴发生在午后及傍晚。海洋雷暴日变化则较为平缓, 南海具有其独特的雷暴日变化特征。
- 雷暴 /
- 闪电 /
- WWLLN /
- DBSCAN /
- 西北太平洋
Abstract: Based on lightning data from the World Wide Lightning Location Network(WWLLN) from 2010 to 2018, and the algorithm of Density-Based Spatial Clustering of Application with Noise(DBSCAN), this study establishes a thunderstorm dataset of the Northwestern Pacific. The temporal and spatial distribution characteristics of thunderstorms in this region are studied, and the characteristics of thunderstorms over land and ocean are compared. The results show that when the parameter thresholds of the DBSCAN algorithm are reasonably performed, the temporal and spatial distribution and evolution of thunderstorms based on WWLLN lightning clusters are consistent with the observations of weather radars.The average daily number, the average area of lightning cluster, the average extension scale, and the average lightning frequency of thunderstorms in the Northwestern Pacific region are 3869, 557.91 km², 31.99 km, and 33 str/(h · thu), respectively. In terms of spatial distribution, thunderstorm activities are the most intense in the coastal areas of Southeast Asia and tropical islands. In addition, thunderstorm activities in the South China Sea are stronger than that in the deep ocean. The average area of offshore thunderstorms increases with the shortening of its distance from the coastline. As for seasonal variation, thunderstorm activities throughout the region reach their peak in summer(June to August) with the peak of that over the South China Sea in June, while thunderstorm activities off the coast of eastern Japan reach their peak in winter. In the southern part of China's inland areas, thunderstorm activities begin to increase significantly in March and the average area of thunderstorms reaches its maximum at that time; however, the average lightning frequency of thunderstorms reaches its peak in May. In terms of diurnal variation, the distribution of continental thunderstorm activities is typical unimodal, and most thunderstorms occur in the afternoon and evening. The diurnal variation of marine thunderstorms is relatively moderate, and a unique diurnal pattern can be found in the thunderstorm activities in the South China Sea.
- thunderstorm /
- lightning /
- WWLLN /
- DBSCAN /
- Northwestern Pacific

HTML全文

图 1 研究范围及四个重点关注区域（西太平洋PO，南海SCS，印度洋IO和我国内陆南方区域INL)

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图 2 2012年7月3日江苏南通一次雷暴过程基于WWLLN闪电的DBSCAN雷暴聚类结果（黑色多边形）与雷达回波的叠加

雷达观测时间(当地时间):a.15:02;b.19:02;c.23:02;d.次日05:02。黑色‘+'代表聚类雷暴闪电，红色‘.’代表非聚类雷暴闪电，将发生在雷达观测时间前后半小时内的闪电聚类为雷暴。

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图 3 雷暴特征参量概率分布

a.雷暴面积；b.雷暴延展尺度；c.雷暴闪电频次。

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图 4 雷暴特征参量的空间分布

a.雷暴数密度（thu/(100 km²·y)); b.雷暴平均面积（km²/thu）。

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图 5 年平均雷暴数（thu/(100 km²·y)）的季节变化

a.冬季（12—2月）；b.春季（3—5月）；c.夏季（6—8月）；d.秋季（9—11月）。

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图 6 四个区域雷暴特征参量的月变化

a.平均雷暴数(thu/(10⁶ km²)); b.雷暴平均面积（km²); c.雷暴平均闪电频次(str/(h·thu))。

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图 7 四个关注区域雷暴数（thu/(10⁷km²))的逐时日变化

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图 8 a.雷暴峰值出现时间的空间分布（LT); b.雷暴谷值出现时间的空间分布（LT); c.雷暴数峰值与谷值比率的空间分布。

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表 1 雷暴特征参量

特征参量	定义	单位
雷暴发生时间	聚类成该雷暴闪电的开始时间	年月日时
雷暴位置	聚类成该雷暴闪电的质心位置	经纬度
雷暴面积	聚类成该雷暴闪电的最小外接凸多边形的面积	km²
雷暴延展尺度	聚类成该雷暴闪电中相距最远的2个闪电之间的距离	km
雷暴闪电频次	单位时间内聚类成该雷暴中的闪电数	str/h

下载: 导出CSV

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