中国东南区域闪电活动特征及其与大气环境参数的关系

doi:10.3969/j.issn.0253-2778.2017.05.005

中国科学技术大学学报 ›› 2017, Vol. 47 ›› Issue (5): 403-412.DOI: 10.3969/j.issn.0253-2778.2017.05.005

中国东南区域闪电活动特征及其与大气环境参数的关系

王基鑫，祝宝友，马明，

1.中国科学技术大学地球与空间科学学院，中国科学院近地空间环境重点实验室，安徽合肥230026；
2.中国科学技术大学安徽蒙城地球物理国家野外科学观测研究站, 安徽合肥 230026

收稿日期:2016-04-12 修回日期:2016-04-29 出版日期:2017-05-31 发布日期:2017-05-31
通讯作者: 马明
作者简介:王基鑫，男，1990年生，硕士生. 研究方向：雷电气候学. E-mail：wangjix@mail.ustc.edu.cn
基金资助:
公益性行业（气象）科研专项（GYHY201306017），国家重点基础研究发展(973)计划（2014CB441404），中央高校基本科研业务费专项资金资助.

Characteristics of lightning activity and its relationship with the atmospheric environment parameters in Southeast China

WANG Jixin, ZHU Baoyou, MA Ming,

1. School of Earth and Space Sciences，University of Science and Technology of China，CAS Key Laboratory of Geospace Environment， Hefei 230026，China;
2. Mengcheng National Geophysical Observatory，University of Science and Technology of China，Hefei 230026,China

Received:2016-04-12 Revised:2016-04-29 Online:2017-05-31 Published:2017-05-31

摘要/Abstract

摘要： 利用近18年（1997～2013）的星载LIS/OTD（lightning imaging sensor and optical transient detector）闪电观测资料、NCEP/NCAR（National Center for Environmental Protection/National Center for Atmospheric Research）和ERA-Interim再分析资料，对北纬30°以南、东经100°以东的中国陆地地区（17.5～30°N, 100～122.5°E）的闪电活动特征及其与大气环境因素的关系进行了分析.结果表明：中国东南闪电高发区闪电活动季节性特征明显，春夏两季为闪电高发期，厄尔尼诺事件对其闪电活动的年际变化有较强的影响，在此期间冬春季闪电活动有明显的增强.东南闪电高发区闪电活动与地面温度、700～400 hPa平均相对湿度、850 hPa位温等热力学参数有明显正相关，与多种稳定度参数有强相关，显示出大气层结不稳定性越大，闪电活动越强.进一步通过多元逐步线性回归方法，建立了东南闪电高发区区域平均闪电密度与地面温度、CAPE（convective available potential energy）、BR（Bowen ratio）、LI（lifted index）、SI（Showalter index）的回归方程，有助于利用多种参数开展预报区域闪电活动.

关键词: 闪电活动特征, 热力学参数, 稳定度参数, 回归方程

Abstract: Based on space-borne lightning observation data from Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD), and reanalysis data of National Center for Environmental Protection/National Center for Atmospheric Research (NCEP/NCAR) and ERA-Interim in an 18-year period from 1997 to 2013, the lightning activity over southeastern China (17.5~30°N, 100~122.5°E) and its associations with atmospheric environmental factors were investigated. The results indicate that the lightning activities show strong seasonal variabilities with high frequency of lightning events in the spring and summer. On the inter-annual time scale, the El Nio-Southern Oscillation (ENSO ) has a significant impact on lightning variability. The El Nio events can significantly intensify the lightning activity in winter and spring. The high frequency of lightning events in southeastern China is associated with the increase of thermodynamic parameters, such as surface air temperature, 700~400 hPa averaged relative humidity and 850 hPa potential temperature. The atmospheric stability parameters are also closely related to lightning activity, and a larger unstable atmospheric layer is associated with a stronger lightning activity. Furthermore, multivariate step linear regression is applied to establish the relationship between predictor variables (e.g., surface air temperature, convective available potential energy, Bowen ratio, lifted index and Showalter index) and prediction (averaged lightning activity concentration). The multiple stepwise linear regression equation is beneficial for regional lightning activity forecast.

Key words: characteristics of lighting activity, thermodynamic parameter, stability parameter, regression equation

中图分类号:

P427.3

王基鑫，祝宝友，马明，. 中国东南区域闪电活动特征及其与大气环境参数的关系[J]. 中国科学技术大学学报, 2017, 47(5): 403-412.

WANG Jixin, ZHU Baoyou, MA Ming,. Characteristics of lightning activity and its relationship with the atmospheric environment parameters in Southeast China[J]. Journal of University of Science and Technology of China, 2017, 47(5): 403-412.

参考文献

［1］
MARKSON R, MUIR M. Solar wind control of the Earth's electric field[J]. Science, 1980, 208(4447): 979-990.
[2] WILLIAMS E R, HECKMAN S J. The local diurnal variation of cloud electrification and the global diurnal variation of negative charge on the Earth[J]. Journal of Geophysical Research: Atmospheres, 1993, 98(D3): 5221-5234.
[3] PRICE C. Evidence for a link between global lightning activity and upper tropospheric water vapour[J]. Nature, 2000, 406(6793): 290-293.
[4] BOND D W, STEIGER S, ZHANG R, et al. The importance of NOx production by lightning in the tropics[J]. Atmospheric Environment, 2002, 36(9): 1509-1519.
[5] 周筠珺, 郄秀书. 闪电产生NOx机制及中国内陆闪电产生NOx量的估算[J]. 高原气象, 2002, 21(5): 501-508.
[6] 郄秀书. 卫星观测到的全球闪电活动及其地域差异[J]. 地球物理学报, 2003, 46(6): 743-750.
[7] 郄秀书, TOUMI R, 周筠珺. 青藏高原中部地区闪电活动特征及其对对流最大不稳定能量的响应[J]. 科学通报, 2003, 48(1): 87-90.
[8] 郭凤霞, 鞠晓雨, 陈聪. 估算闪电产生氮氧化物量的研究回顾与进展[J]. 地球科学进展, 2013, 28(3): 305-317.
[9] 李照荣, 康凤琴, 马胜萍. 西北地区雷暴气候特征分析[J]. 灾害学, 2005, 20(2): 83-88.
[10] 冯建英, 陈佩璇, 梁东升. 西北地区雷暴的气候特征及其变化规律[J]. 甘肃科学学报, 2007, 19(3): 71-74.
[11] 易燕明, 杨兆礼, 万齐林, 等. 近50年广东省雷暴、闪电时空变化特征的研究[J]. 热带气象学报, 2006, 22(6): 539-546.
[12] 冯桂力, 胡先锋, 李采莲, 等. 青岛地区闪电活动气候特征[J]. 陕西气象, 2009 (B09): 1-4.
[13] 孙蟩. 北京城区与郊区雷暴气候特征及其变化对比分析[J]. 气候与环境研究, 2011, 16(5): 649-656.
[14] 邓德文, 周筠珺, 赵鹏国, 等. 中国典型区域雷电活动气候特征及其机制分析[J]. 气象科学, 2013 (1): 109-118.
[15] 郄秀书. 青藏高原闪电活动的时空分布特征[J]. 地球物理学报, 2004, 47(6): 997-1002.
[16] 马明, 陶善昌, 祝宝友, 等. 卫星观测的中国及周边地区闪电密度的气候分布[J]. 中国科学(D辑:地球科学), 2004, 34(4): 298-306.
[17] 袁铁, 郄秀书. 卫星观测到的我国闪电活动的时空分布特征[J]. 高原气象, 2004, 23(4): 488-494.
[18] TOUMI R, QIE X. Seasonal variation of lightning on the Tibetan Plateau: A spring anomaly？[J]. Geophysical Research Letters, 2004, 31(4): 235-250.
[19] 马明, 陶善昌, 祝宝友, 等. 全球闪电活动对气温变化的响应[J]. 科学通报, 2005, 50(15): 1643-1647.
[20] 张义军, 孟青. 青藏高原东部地区的大气电特征[J] . 高原气象, 1998, 17( 2) : 135- 141.
[21] 袁铁, 郄秀书. 青藏高原中部闪电活动与相关气象要素季节变化的相关分析[J]. 气象学报, 2005, 63(1): 123-127.
[22] 郑栋, 张义军, 吕伟涛, 等. 大气不稳定度参数与闪电活动的预报[J]. 高原气象, 2005, 24(2): 196-203.
[23] CHRISTIAN H, BLAKESLEE R, GOODMAN S, et al. The lightning imaging sensor[C]//NASA Conference Publication. NASA, 1999: 746-749.
[24] BOCCIPPIO D J, KOSHAK W J, BLAKESLEE R J. Performance assessment of the optical transient detector and lightning imaging sensor. Part I: Predicted diurnal variability[J]. Journal of Atmospheric and Oceanic Technology, 2002, 19(9): 1318-1332.
[25] CHRISTIAN H J, BLAKESLEE R J, BOCCIPPIO D J, et al. Global frequency and distribution of lightning as observed from space by the Optical Transient Detector[J]. Journal of Geophysical Research: Atmospheres, 2003, 108(D1): ACL 4-1-ACL 4-15.
[26] CECIL D J, BUECHLER D E, BLAKESLEE R J. Gridded lightning climatology from TRMM-LIS and OTD: Dataset description[J]. Atmospheric Research, 2014, 135: 404-414.
[27] KALNAY E, KANAMITSU M, KISTLER R, et al. The NCEP/NCAR 40-year reanalysis project[J]. Bulletin of the American Meteorological Society, 1996, 77(3): 437-471.
[28] DEE D P, UPPALA S M, SIMMONS A J, et al. The ERA-Interim reanalysis: Configuration and performance of the data assimilation system[J]. Quarterly Journal of the Royal Meteorological Society, 2011, 137(656): 553-597.
[29] BOLTON D. The computation of equivalent potential temperature[J]. Monthly Weather Review, 1980, 108(7): 1046-1053.
[30] 李任承, 顾光芹. 关于假相当位温的精确计算[J]. 气象, 1990, 16(3): 13-17.
[31] DUGAS W A, FRITSCHEN L J, GAY L W, et al. Bowen ratio, eddy correlation, and portable chamber measurements of sensible and latent heat flux over irrigated spring wheat[J]. Agricultural and Forest Meteorology, 1991, 56(1): 1-20.
[32] WARE R, ROCKEN C, SOLHEIM F, et al. GPS sounding of the atmosphere from low Earth orbit: Preliminary results[J]. Bulletin of the American Meteorological Society, 1996, 77(1): 19-40.
[33] GEORGE J J. Weather forecasting for aeronautics[M]. New York: Academic Press, 2014.
[34] ANDERSSON T, ANDERSSON M, JACOBSSON C, et al. Thermodynamic indices for forecasting thunderstorms in southern Sweden[J]. Meteorological Magazine, 1989, 118(1404): 141-146.
[35] GOODMAN S J. Predicting thunderstorm evolution using ground-based lightning detection networks[R]. NASA, 1990: 19910006347.
[36] BARLOW W. A new index for the prediction of deep convection[C]//17th Conference On Severe Local Storms. St. Louis, MO: American Meteorological Society, 1993: 129-132.
[37] VAN DELDEN A. The synoptic setting of thunderstorms in western Europe[J]. Atmospheric Research, 2001, 56(1): 89-110.
[38] STACKPOLE J D. Numerical analysis of atmospheric soundings[J]. Journal of Applied Meteorology, 1967, 6(3): 464-467.
[39] SHOWALTER A K. A stability index for thunderstorm forecasting[J]. Bulletin of the American Meteorological Society, 1953, 34(6): 250-252.
[40] 吕新刚, 周志强. 沙瓦特指数的数值计算方案比较研究[J]. 气象, 2015, 41(10): 1260-1267.
[41] 马明, 陶善昌, 祝宝友, 等. 1997/1998 El Nio期间中国南部闪电活动的异常特征[J]. 中国科学(D 辑: 地球科学), 2004, 34(9): 873-881.
[42] 封国林, 孙树鹏, 赵俊虎, 等. 基于2009年初长江中下游地区持续阴雨过程的 10-30 天延伸期稳定分量的提取及配置分析[J]. 中国科学：地球科学, 2013, 43(5): 836-847.

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中国东南区域闪电活动特征及其与大气环境参数的关系

Characteristics of lightning activity and its relationship with the atmospheric environment parameters in Southeast China

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