华南一次典型雷暴过程双偏振雷达参量与闪电活动关系研究

杜赛; 刘显通; 孙皓霆; 陈绍东; 陈绿文; 颜旭

doi:10.16032/j.issn.1004-4965.2021.038

华南一次典型雷暴过程双偏振雷达参量与闪电活动关系研究

doi: 10.16032/j.issn.1004-4965.2021.038

1.
中国气象局广州热带海洋气象研究所，广东广州 510641
2.
海珠区气象局，广东广州 510220

基金项目:

国家自然科学基金项目 41705020

广东省科技计划项目 2017B020244002

中国气象科学研究院基本科研业务费专项 2020Z010

广东省气象局科学技术项目 GRMC2019M09

详细信息

通讯作者:
刘显通, 男, 江西省人, 副研究员, 研究方向: 云降水物理与热带灾害性天气预报。E-mail: xtliu@gd121.cn

中图分类号: P445
计量
- 文章访问数: 240
- HTML全文浏览量: 37
- PDF下载量: 50
- 被引次数: 0
出版历程
- 收稿日期: 2020-12-30
- 修回日期: 2021-05-30
- 网络出版日期: 2021-09-27
- 刊出日期: 2021-06-01

RELATIONSHIP BETWEEN DUAL-POLARIZATION RADAR PARAMETERS AND LIGHTNING ACTIVITY DURING A TYPICAL THUNDERSTORM IN SOUTH CHINA

1.
Guangzhou Institute of Tropical and Marine Meteorology, CMA, Guangzhou 510641, China
2.
Meteorological Bureau of Haizhu District, Guangzhou 510220, China

摘要

摘要: 基于2017年5月8日华南地区一次典型飑线过程, 分析了此次过程中闪电活动和-35~0℃温度层内双偏振雷达参量的分布特征以及双偏振雷达参量与闪电活动之间的关系。结果表明: 此次飑线过程中, 双偏振雷达参量与闪电频次的趋势在时间变化上有较好的一致性, 且随着闪电活动的发生及雷暴过程的增强, 双偏振雷达参量中的冰水含量、雷达反射率因子、差分反射率、差分相移率等偏振参量都有不同程度的增加, 闪电频次高峰时间段对应各个参量最大值时间段。双偏振雷达各个参量最大值与闪电活动的线性拟合关系均优于多项式拟合关系。定性地发现了双偏振雷达参量与闪电活动的关系, 可为将来将双偏振雷达参量加入到闪电临近预警预报提供一定的参考依据。
- 双偏振雷达 /
- 雷达参量 /
- 飑线 /
- 闪电活动 /
- 闪电临近预警
Abstract: Based on a typical squall line process in South China on May 8, 2017, this paper analyzed the lightning activity and the distribution characteristics of dual-polarization radar parameters in the-35 ~ 0 ℃temperature layer as well as the relationship between the dual-polarization radar parameters and lightning activities during this process. The results show that during the squall line process, the dual-polarization radar parameters and the trend of lightning frequency have a good consistency in time variation. And with the occurrence of lightning activity and the enhancement of thunderstorm process, the polarization parameters of dual polarization radar such as ice water content, radar reflectivity factor, differential reflectivity, and differential phase shift rate all increase by varying degree. The peak time of lightning frequency corresponds to the peak time of each parameter. The linear fitting relationship between the maximum value of each parameter of dual-polarization radar and lightning activity is better than the polynomial fitting relationship. The present research finds the relationship between the parameters of dualpolarization radar and lightning activity, providing reference for the introduction of dual-polarization radar parameters to lightning nowcasting.
- dual-polarization radar /
- radar parameters /
- squall line /
- lightning activity /
- lightning nowcasting

HTML全文

图 1 研究范围(图中黑框部分)

蓝色三角形为广东省EN闪电定位系统，红色五角星为广州S波段双偏振雷达分布图。

下载: 全尺寸图片幻灯片

图 2 2017年5月8日00时清远探空站T-log p图

红色实线：大气层结温度，绿色实线：大气层结露点温度。

下载: 全尺寸图片幻灯片

图 3 2017年5月8日雷暴过程每6 min闪电频次分布(00:00—18:00)

下载: 全尺寸图片幻灯片

图 4 双偏振雷达各参数在-35~0 ℃温度层占比

下载: 全尺寸图片幻灯片

图 5 2017年5月8日雷暴过程双偏振雷达各参量最大值时间分布

下载: 全尺寸图片幻灯片

图 6 双偏振雷达各参量最大值与闪电活动(总闪频数、云闪频数、地闪频数)散点图

下载: 全尺寸图片幻灯片

图 7 在10:00时刻双偏振雷达组合反射率(a)、冰水含量(b)分别和闪电(总闪频次)叠加图及沿a中黑色实线剖面图(c)

下载: 全尺寸图片幻灯片

表 1 广州S波段双偏振天气雷达主要性能指标

序号	项目	参数	序号	项目	参数
1	天线形式天线直径	中心馈电，实面天线	12	接收机最小可测功率	≤-109 dBm(1.57 μs) ≤-114 dBm(4.5 μs)
2	天线直径	旋转抛物面，8.5 m	12	接收机最小可测功率	≤-109 dBm(1.57 μs) ≤-114 dBm(4.5 μs)
3	波速宽度	≤1°(3 dB)	13	接收机噪声系数	≤4 dB
4	天线增益	≥44 dB	14	接收机动态范围	≥85 dB
5	天线方向性	水平/垂直极化波速主轴方向差 < 0.1°	15	接收机距离分辨率	250 m/1 000 m
6	双通道隔离度	≥30 dB	16	雷达反射率因子	1 dB
7	发射机工作频率	2 885 MHz	17	径向速度V_r/谱宽S_w	1 m/s
8	发射机峰值功率	≥650 kW	18	差分反射率Z_DR	0.2 dB
9	发射机脉冲宽度	1.57 μs, 4.7 μs	19	差分传播相移Φ_DP	2°
10	发射机脉冲重复频率	322~1 304 Hz	20	差分传播相移率K_DP	0.2 °/km
11	发射机偏振方式	双线偏振/双发双收	21	相关系数CC	0.01

下载: 导出CSV

表 2 2017年5月8日清远探空资料分析

时间/UTC	CAPE/(J/kg)	CIN/(J/kg)	K	SI	LI	0 ℃层高度/m	-10 ℃层高度/m	-20 ℃层高度/m	-30 ℃层高度/m	-35 ℃层高度/m
00	94	-17.3	32.7	1.41	0.51	5 050	7 000	8 080	9 700	10 300

下载: 导出CSV

参考文献(37)

[1]	BUECHLER, DENNIS E, GOODMAN S J. Echo size and asymmetry: Impact on NEXRAD storm identification[J]. J Appl Meteor Climatol, 1990, 29(9): 962-969.
[2]	MICHIMOTO K. A study of radar echoes and their relation to lightning discharge of thunderclouds in the Hokuriku district Part Ⅰ: Observation and analysis of thunderclouds in summer and winter[J]. J Meteor Soc Japan, 1991, 69(3): 327-336.
[3]	HONDL K D, EILTS M D. Doppler radar signatures of developing thunderstorms and their potential to indicate the onset of cloud-toground lightning[J]. Mon Wea Rev, 1994, 122(8): 1 818-1 836.
[4]	VINCENT B R, CAREY L D, SCHNEIDER D, et al. Using WSR-88D reflectivity data for the prediction of cloud-to-ground lightning: A central North Carolina study[J]. Natl Wea Dig, 2004, 27(1): 35-44.
[5]	李南, 魏鸣, 姚叶青. 安徽闪电与雷达资料的相关分析以及机理初探[J]. 热带气象学报, 2006, 22(3): 265-272.
[6]	彭丽英, 万齐林, 王谦谦, 等. 广东中部地区雷电和CINRAD雷达回波的统计关系[J]. 热带气象学报, 2007, 23(2): 171-176.
[7]	WOLF P. Anticipating the initiation, cessation, and frequency of cloud-to-ground lightning, utilizing WSR-88D reflectivity data[J]. Electron J Oper Meteorol, 2007, 8(1): 1-19.
[8]	CLEMENTS N C, ORVILLE R E. The warning time for cloud-to-ground lightning in isolated, ordinary thunderstorms over Houston, Texas[D]. Texas A & amp; M University, 2010.
[9]	姚叶青, 袁松, 丁卫东, 等. 利用闪电定位和雷达资料进行雷电临近预报方法研究[J]. 热带气象学报, 2011, 27(6): 905-9l1.
[10]	GREMILLION M S, ORVILLE R E. Thunderstorm characteristics of cloud-to-ground lightning at the Kennedy Space Center, Florida: A study of lightning initiation signatures as indicated by the WSR-88D[J]. Wea Forecasting, 1999, 14(5): 640-649.
[11]	MARTINEZ M. The relationship between radar reflectivity and lightning activity at initial stages of convective storms[C]//American Meteorological Society, 82nd Annual Meeting, First Annual Student Conference, Orlando, Florida. 2002.
[12]	李芳, 黄兴友, 王振会, 等. 基于南京地区雷达资料的雷电识别指标初探[J]. 气象科学, 2010, 30(2): 202-207.
[13]	王飞, 张义军, 赵均壮, 等. 雷达资料在孤立单体雷电预警中的初步应用[J]. 应用气象学报, 2008, 19(2): 153-160.
[14]	REYNOLDS S E, BROOK M, GOURLEY M F. Thunderstorm charge separation[J]. J Atmos Sci, 1957, 14(5): 426-436.
[15]	TAKAHASHI T. Riming electrification as a charge generation mechanism in thunderstorms[J]. J Atmos Sci, 1978, 35(8): 1 536-1 548.
[16]	SAUNDERS C P R, KEITH W D, MITZEVA R P. The effect of liquid water on thunderstorm charging[J]. J Geophys Res Atmos, 1991, 96(D6): 11 007-11 017.
[17]	MANSELL E R, MACGORMAN D R, ZIEGLER C L, et al. Charge structure and lightning sensitivity in a simulated multicell thunderstorm[J]. J Geophys Res Atmos, 2005, 110: D12101, doi:10.1029/2004JD005287.
[18]	MACGORMAN D R, MACGORMAN R, RUST W D, et al. The electrical nature of storms[M]. Oxford: Oxford University Press on Demand, 1998.
[19]	MARSHALL T C, RUST W D. Electric field soundings through thunderstorms[J]. J Geophys Res Atmos, 1991, 96(D12): 22 297-22 306.
[20]	DEIERLING W, LATHAM J, PETERSEN W A, et al. On the relationship of thunderstorm ice hydrometeor characteristics and total lightning measurements[J]. Atmos Res, 2005, 76(1-4): 114-126.
[21]	CAREY L D, BAIN A L, MATTHEE R. Kinematic and microphysical control of lightning in multicell convection over Alabama during DC3[C]//5th International Conference on Lightning meteorology, 2014: 20-21.
[22]	MECIKALSKI R M, BAIN A L, CAREY L D. Radar and lightning observations of deep moist convection across northern Alabama during DC3: 21 May 2012[J]. Mon Wea Rev, 2015, 143(7): 2 774-2 794.
[23]	WOODARD C J, CAREY L D, PETERSEN W A, et al. Operational utility of dual-polarization variables in lightning initiation forecasting[J]. Electron J Oper Meteor, 2012, 13(1): 79-102.
[24]	PRESTON A D, FUELBERG H E. Improving lightning cessation guidance using polarimetric radar data[J]. Wea Forecasting, 2015, 30(2): 308-328.
[25]	WANG J, ZHOU S, YANG B, et al. Nowcasting cloud-to-ground lightning over Nanjing area using S-band dual-polarization Doppler radar[J]. Atmos Res, 2016, 178: 55-64.
[26]	MOSIER R M, SCHUMACHER C, ORVILLE R E. Radar nowcasting of cloud-to-ground lightning over Houston, Texas[J]. Wea Forecasting, 2011, 26(2): 199-212.
[27]	HAYASHI S, UMEHARA A, NAGUMO N, et al. The relationship between lightning flash rate and ice-related volume derived from dualpolarization radar[J]. Atmos Res, 2021, 248: https://doi.org/10.1016/j.atmosres.2020.105166.
[28]	杜爽, 王东海, 李国平, 等. 基于双频星载降水雷达GPM数据的华南地区降水垂直结构特征分析[J]. 热带气象学报, 2020, 36(1): 115-130.
[29]	易燕明, 杨兆礼, 万齐林, 等. 近50年广东省闪电、雷暴时空变化特征的研究[J]. 热带气象学报, 2006, 22(6): 539-546.
[30]	王义耕, 陈渭民, 刘洁. TRMM卫星观测到的华南地区的闪电时空分布特征[J]. 热带气象学报, 2009, 25(2): 227-233.
[31]	顾宇丹, 虞敏, 林文旻. 上海市两套闪电定位系统探测能力对比分析[J]. 气象与环境科学, 2018, 41(3): 126-131.
[32]	LIU C, HECKMAN S. The application of total lightning detection and cell tracking for severe weather prediction[C]//91st American Meteorological Society Annual Meeting, 2011: 1-10.
[33]	THOMPSON K B, BATEMAN M G, CAREY L D. A comparison of two ground-based lightning detection networks against the satellitebased Lightning Imaging Sensor(LIS)[J]. J Atmos Oceanic Technol, 2014, 31(10): 2 191-2 205.
[34]	郭凤霞, 黄兆楚, 王曼霏, 等. 广东一次雷暴过程的宏微观及电特征的数值模拟[J]. 热带气象学报, 2018, 34(5): 626-636.
[35]	张敏锋, 刘欣生, 张义军, 等. 广东地区雷电活动的气候分布特征[J]. 热带气象学报, 2000, 16(1): 46-53.
[36]	甘明骏, 郭凤霞, 黎奇, 等. 广东一次飑线过程中一个雷暴单体成熟阶段的电荷结构演变特征的数值模拟[J]. 热带气象学报, 2020, 36(4): 562-576.
[37]	KEIGHTON S J, BLUESTEIN H B, MACGORMAN D R. The evolution of a severe mesoscale convective system: Cloud-to-ground lightning location and storm structure[J]. Mon Wea Rev, 1991, 119(7): 1 533-1 556.