Characteristics of Lightning Activity in Super Typhoon Mangkhut (1822)
-
摘要: 为了进一步认识热带气旋（TC）全生命期中闪电的活动特征，本文利用全球闪电定位网（WWLLN）资料、中央气象台的TC路径数据、风云四号A星（FY-4A）的相当黑体温度（TBB）数据和ERA5再分析资料，研究了2018年登陆中国的最强台风“山竹”从生成到消亡全生命期中闪电活动的时空分布和随强度的变化特征，探讨了闪电活动与风圈半径及下垫面的关系。结果表明：（1）“山竹”中的闪电活动有明显的三圈结构，内核闪电密度最大，内雨带几乎没有闪电，外雨带闪电数量最多。内核闪电与外雨带闪电的主要发生时间不同，外雨带在远海也能产生大量闪电。（2）闪电活动的方位分布与TC强度、所处地理位置及环境密切相关，不同时期闪电方位分布不同。（3）闪电活动与风圈半径没有明确的关系，闪电活动多发于风圈半径较小的东南和西南方位。（4）TC快速增强期间及前后，内核闪电活动对TC强度增强具有一定的指示作用。此外，内核闪电活动与对流强度呈现较好的相关性。（5）岛屿和陆地的存在对于强对流的发展有着极重要的作用。气流遇到较高地形被迫抬升，形成闪电。TC西南方位距岛屿东南侧约300 km的海面，水汽、热量充足且人为气溶胶较多，有利于上升气流的发展，进而产生闪电。这些认识有助于闪电资料在TC中小尺度强对流监测和预警中的应用。
-
关键词:
- 超强台风 /
- 山竹 /
- 闪电 /
- 全球闪电定位网(WWLLN)
Abstract: To gain further insight into the characteristics of lightning activity during the whole life of a tropical cyclone (TC), World Wide Lightning Location Network (WWLLN) data, TC best-track data from the National Meteorological Center of China Meteorological Administration, black body temperature data from the Fengyun-4A satellite, and ERA5 reanalysis data are used to explore typhoon Mangkhut, the strongest typhoon that landed in China in 2018. The temporal and spatial distributions of lightning activity and its variation with intensity during the whole life of typhoon Mangkhut are studied, as well as the relationship between lightning activity and wind circle radius and the underlying surface. Results show (1) the three-circle structure of the lightning activity in Mangkhut: the highest density of lightning in the inner core, almost no lightning in the inner rainbands, and the largest amount of lightning in the outer rainbands. The inner core lightning has a different main occurrence time from the outer rainband lightning, which can also produce a large amount of lightning in the open sea. (2) The azimuthal distribution of lightning activity is closely related to TC intensity, geographical location, and environment and is different in different periods. (3) There is no clear relationship between lightning activity and wind circle radius. The lightning activity mostly occurs in the southeast and southwest, where the wind circle has a smaller radius. (4) During and around TC rapid intensification, the inner core lightning activity has a certain indicator effect on TC intensity intensification. Moreover, there is a good correlation between lightning activity and convective intensity in the inner core. (5) The existence of islands and land plays an important role in severe convection development. When the stream hits a higher terrain, it is forced to lift, forming lightning. The southwest direction of the TC is about 300km away from the southeast side of the island, and sufficient water vapor, heat, and more anthropogenic aerosols are observed, which are conducive to updraft development, thus generating lightning. These insights contribute to the application of lightning data in monitoring and early warning of mesoscale and small-scale severe convections in TCs.-
Key words:
- Super typhoon /
- Mangkhut /
- Lightning /
- World Wide Lightning Location Network (WWLLN)
-
图 1 全生命期（2018年9月7日12:00至9月17日09:00，协调世界时，下同）距热带气旋（TC）中心1000 km内累计闪击密度（填色，单位：10−2 km−2）的径向空间分布
Figure 1. Radial spatial distribution of cumulative stroke density (shaded, units: 10−2 km−2) within 1000 km from the TC (tropical cyclone) center during the whole life (from 1200 UTC 7 September to 0900 UTC 17 September 2018) of the TC
图 2 全生命期距中心1000 km内累计闪击密度的地理空间分布。路径每点代表每小时位置，上方箭头指向F-RI（第一次快速增强）和Re-RI（再次快速增强即第二次快速增强），下方箭头数字指向日期（例如17表示9月17日00:00）
Figure 2. Geospatial distribution of cumulative stroke density within 1000 km from the TC center during the whole life of the TC. Each point of the track represents the hourly position, the arrows above point to F-RI (First Rapid Intensification) and Re-RI (Re-RI means Second Rapid Intensification), and the arrows below point to the date (e.g. 17 means 0000 UTC 17 September)
图 3 不同强度等级时闪击活动的径向分布特征：（a）小时平均闪击密度[单位：(100 km)−2 h−1]；（b）小时平均闪击数；（c）同一强度等级时不同径向距离的闪击数占比。图中1、2用以区分同一强度等级先后顺序
Figure 3. Radial distribution characteristics of stroke activity at different intensity levels: (a) hourly average stroke density [units: (100 km)−2 h−1]; (b) hourly average stroke count; (c) proportion of stroke count in different radial distances at the same intensity level. Distinguishing the order of the same intensity grade by 1 and 2
图 4 全生命期TC闪击数、最大风速和中心气压随时间的逐小时变化：（a）内核；（b）内雨带；（c）外雨带。PH和GD分别代表菲律宾和广东省，箭头指向不同特殊时刻，下同
Figure 4. Hourly variations of stroke count, maximum wind speed, and central pressure during the whole life of the TC: (a) Inner core; (b) inner rainbands; (c) outer rainbands. PH and GD represent the Philippines and Guangdong Province respectively. The arrows point to different special moments, the same below
图 5 距TC中心不同距离上平均闪击密度随时间的变化（彩色折线为TC的中心气压，不同颜色代表TC的不同强度等级，参见图2图例，下同）
Figure 5. Variation of average stroke density with time at different distances from the TC center (the colored broken line is the central pressure of the TC, and different colors represent different intensity levels of the TC; same as the legend in Figure 2)
图 6 TC不同方位上平均闪击密度随时间的变化：（a）内核；（b）内雨带；（c）外雨带
Figure 6. Variation of average stroke density with time in different azimuths of the TC: (a) Inner core; (b) inner rainbands; (c) outer rainbands
图 7 不同强度等级闪击活动方位分布特征：（a）小时平均闪击密度[单位：(100 km)−2 h−1]；（b）小时平均闪击数；（c）同一强度等级时不同径向距离的闪击数占比。图中以1、2区分同一强度等级先后顺序
Figure 7. Azimuth distribution characteristics of stroke activity at different intensity levels: (a) hourly average stroke density (units: (100 km)−2 h−1); (b) hourly average stroke count; (c) proportion of stroke count in different radial distances at the same intensity level. Distinguishing the order of the same intensity grade by 1 and 2
图 8 TC不同方位风圈半径随时间的变化（生成至登陆广东省前）：（a）十二级风圈；（b）十级风圈；（c）七级风圈。灰色背景区分六个阶段
Figure 8. Variation of the wind circle radius in different azimuths with time (from generation to landing in Guangdong Province): (a) Wind circle rank 12; (b) wind circle rank 10; (c) wind circle rank 7. Six stages distinguished by gray background
图 9 C-RI期间及前后内核平均闪击密度随时间的变化
Figure 9. Variation of inner core average stroke density with time during and around C-RI
图 10 C-RI期间及前后最大风速变化（W）与内核累计闪击次数（L）的相关性。W和L后面数字代表小时数。（a）6小时最大风速变化与6、12和24小时内核累计闪击次数的相关性；（b）12小时最大风速变化与6、12和24小时内核累计闪击次数的相关性；（c）24小时最大风速变化与6、12和24小时内核累计闪击次数的相关性。r1至r9代表W6、W12和W24分别与L6、L12和L24的相关系数
Figure 10. Correlation between the change in maximum wind speed (W) and the cumulative number of inner core strokes (L) during and around C-RI. The numbers after W and L represent hours. (a) Correlation between the 6-hour change in maximum wind speed and the 6-, 12-, and 24-hour cumulative numbers of inner core stroke; (b) Correlation between the 12-hour change in maximum wind speed and the 6-, 12-, and 24-hour cumulative numbers of inner core stroke; (c) Correlation between the 24-hour change in maximum wind speed and the 6-, 12-, and 24-hour cumulative numbers of inner core stroke. r1–r9 represent the correlation coefficients of W6, W12, and W24 with L6, L12, and L24, respectively
图 11 内核的闪击数、TBB最低值、TBB低于205 K的面积占比和500 hPa涡度（相对）最高值随时间的变化（灰色背景区分五个阶段）
Figure 11. Variation of stroke number, minimum value of TBB, proportion of the area where TBB is lower than 205 K, and maximum value of 500 hPa vorticity (relative) with time in the inner core (five stages distinguished by gray background)
图 12 2018年9月（a、b）15日01:00、（c、d）12日16:00和（e、f）16日02:00三个特殊时刻的闪电活动、TBB（左列）和海拔（右列）的分布情况。粉色矩形框指示研究区域，风矢表示850 hPa风场，红色“+”代表闪击，黑圈（圆弧）由内到外分别代表距中心半径100 km、200 km和1000 km
Figure 12. Lightning activity at three special moments of (a, b) 0100 UTC 15, (c, d) 1600 UTC 12 and (e, f) 0200 UTC 16 September 2018: TBB (left column); altitude (right column). Pink rectangular boxes indicate the study area, wind arrow represents 850 hPa wind field, the red “+” symbol represents stroke, and the black circle (arc) represents 100 km, 200 km, and 1000 km from the center radius from inside to outside, respectively
-
[1] Abarca S F, Corbosiero K L, Galarneau Jr T J. 2010. An evaluation of the worldwide lightning location network (WWLLN) using the national lightning detection network (NLDN) as ground truth [J]. J. Geophys. Res., 115(D18): D18206. doi: 10.1029/2009jd013411 [2] Abarca S F, Corbosiero K L, Vollaro D. 2011. The world wide lightning location network and convective activity in tropical cyclones [J]. Mon. Wea. Rev., 139(1): 175−191. doi: 10.1175/2010MWR3383.1 [3] Black R A, Hallett J. 1999. Electrification of the Hurricane [J]. J. Atmos. Sci., 56(12): 2004−2028. doi: 10.1175/1520-0469(1999)056<2004:EOTH>2.0.CO;2 [4] 陈联寿, 丁一汇. 1979. 西太平洋台风概论 [M]. 北京: 科学出版社.Chen Lianshou, Ding Yihui. 1979. Introduction to Typhoon in the Western Pacific (in Chinese) [M]. Beijing: Science Press. [5] 陈联寿, 孟智勇. 2001. 我国热带气旋研究十年进展 [J]. 大气科学, 25(3): 420−432. doi: 10.3878/j.issn.1006-9895.2001.03.11Chen Lianshou, Meng Zhiyong. 2001. An overview on tropical cyclone research progress in China during the past ten years [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 25(3): 420−432. doi: 10.3878/j.issn.1006-9895.2001.03.11 [6] 陈淑琴, 李英, 范悦敏, 等. 2021. 台风“山竹”(2018)远距离暴雨的成因分析 [J]. 大气科学, 45(3): 573−587. doi: 10.3878/j.issn.1006-9895.2009.20126Chen Shuqin, Li Ying, Fan Yuemin, et al. 2021. Analysis of long-distance heavy rainfall caused by typhoon Mangosteen (2018) [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(3): 573−587. doi: 10.3878/j.issn.1006-9895.2009.20126 [7] DeMaria M, Sampson C R, Knaff J A, et al. 2014. Is tropical cyclone intensity guidance improving? [J]. Bull. Amer. Meteor. Soc., 95(3): 387−398. doi: 10.1175/BAMS-D-12-00240.1 [8] Emanuel K A. 1988. The maximum intensity of hurricanes [J]. J. Atmos. Sci., 45(7): 1143−1155. doi: 10.1175/1520-0469(1988)045<1143:tmioh>2.0.co;2 [9] Fierro A O, Leslie L, Mansell E, et al. 2007. A high-resolution simulation of microphysics and electrification in an idealized hurricane-like vortex [J]. Meteor. Atmos. Phys., 98(1): 13−33. doi: 10.1007/s00703-006-0237-0 [10] Fierro A O, Stevenson S N, Rabin R M. 2018. Evolution of GLM-observed total lightning in hurricane Maria (2017) during the period of maximum intensity [J]. Mon. Wea. Rev., 146(6): 1641−1666. doi: 10.1175/MWR-D-18-0066.1 [11] Griffin E M, Schuur T J, MacGorman D R, et al. 2014. An electrical and polarimetric analysis of the overland reintensification of tropical storm Erin (2007) [J]. Mon. Wea. Rev., 142(6): 2321−2344. doi: 10.1175/MWR-D-13-00360.1 [12] Guimond S R, Heymsfield G M, Turk F J. 2010. Multiscale observations of hurricane Dennis (2005): The effects of hot towers on rapid intensification [J]. J. Atmos. Sci., 67(3): 633−654. doi: 10.1175/2009JAS3119.1 [13] 郭凤霞, 刘冰, 白翎, 等. 2014. 中低层水平风速对闪电和降水影响的数值模拟 [J]. 高原气象, 33(4): 1135−1145. doi: 10.7522/j.issn.1000-0534.2013.00004Guo Fengxia, Liu Bing, Bai Ling, et al. 2014. Numerical simulation study on the effect of middle-and low-level horizontal wind speed on lightning and precipitation [J]. Plateau Meteorology (in Chinese), 33(4): 1135−1145. doi: 10.7522/j.issn.1000-0534.2013.00004 [14] He Y C, He J Y, Chen W C, et al. 2020. Insights from super typhoon Mangkhut (1822) for wind engineering practices [J]. J. Wind. Eng. Ind. Aerod., 203: 104238. doi: 10.1016/j.jweia.2020.104238 [15] Hutchins M L, Holzworth R H, Virts K S, et al. 2013. Radiated VLF energy differences of land and oceanic lightning [J]. Geophys. Res. Lett., 40(10): 2390−2394. doi: 10.1002/grl.50406 [16] Jacobson A R, Holzworth R, Harlin J, et al. 2006. Performance assessment of the world wide lightning location network (WWLLN), using the Los Alamos sferic array (LASA) as ground truth [J]. J. Atmos. Oceanic Technol., 23(8): 1082−1092. doi: 10.1175/JTECH1902.1 [17] 雷小途, 张义军, 马明. 2009. 西北太平洋热带气旋的闪电特征及其与强度关系的初步分析 [J]. 海洋学报, 31(4): 29−38. doi: 10.3321/j.issn:0253-4193.2009.04.004Lei Xiaotu, Zhang Yijun, Ma Ming. 2009. The preliminary analysis of the lightning characteristics and the relationship between lightning and intensity of tropical cyclone in Northwest Pacific [J]. Acta Oceanologica Sinica (in Chinese), 31(4): 29−38. doi: 10.3321/j.issn:0253-4193.2009.04.004 [18] 李瑞, 尹承美, 胡鹏, 等. 2020. 海气热通量和垂直风切变对强热带风暴“温比亚”(2018)影响研究[J]. 海洋湖沼通报, (3): 7–15Li Rui, Yin Chengmei, Hu Peng, et al. Effects of air-sea heat flux and environmental vertical wind shear on severe tropical storm Rumbia (2018) [J]. Transactions of Oceanology and Limnology (in Chinese), (3): 7–15. doi:10.13984/j.cnki.cn37-1141.2020.03.002 [19] 梁志超, 丁菊丽, 费建芳, 等. 2022. 气溶胶直接和间接效应对台风眼墙和外雨带的影响及其分离贡献 [J]. 中国科学: 地球科学, 52(1): 154–170.Liang Zhichao, Ding Juli, Fei Jianfang, et al. 2021. Direct/indirect effects of aerosols and their separate contributions to typhoon Lupit (2009): Eyewall versus peripheral rainbands [J]. Science China Earth Sciences, 64(12): 2113–2128, doi:10.1007/s11430-020-9816-7 [20] 刘俊, 谭涌波, 师正, 等. 2018. 气溶胶对雷暴云微物理过程和起电影响的数值模拟 [J]. 气候与环境研究, 23(6): 758−768. doi: 10.3878/j.issn.1006-9585.2018.18047Liu Jun, Tan Yongbo, Shi Zheng, et al. 2018. A numerical study of aerosol effects on microphysical process and electrification in thunderstorms [J]. Climatic and Environmental Research (in Chinese), 23(6): 758−768. doi: 10.3878/j.issn.1006-9585.2018.18047 [21] Lo H S, Lee Y K, Po B H K, et al. 2020. Impacts of typhoon Mangkhut in 2018 on the deposition of marine debris and microplastics on beaches in Hong Kong [J]. Sci. Total Environ., 716: 137172. doi: 10.1016/j.scitotenv.2020.137172 [22] Mansell E R, Ziegler C L. 2013. Aerosol effects on simulated storm electrification and precipitation in a two-moment bulk microphysics model [J]. J. Atmos. Sci., 70(7): 2032−2050. doi: 10.1175/JAS-D-12-0264.1 [23] Marks F D, Shay L K, PDT-5. 1998. Landfalling tropical cyclones: Forecast problems and associated research opportunities [J]. Bull. Amer. Meteor. Soc., 79(2): 305−323. doi: 10.1175/1520-0477(1998)079<0305:ltcfpa>2.0.co;2 [24] Molinari J, Moore P K, Idone V P, et al. 1994. Cloud-to-ground lightning in Hurricane Andrew [J]. J. Geophys. Res., 99(D8): 16665−16676. doi: 10.1029/94jd00722 [25] Molinari J, Moore P, Idone V. 1999. Convective structure of hurricanes as revealed by lightning locations [J]. Mon. Wea. Rev., 127(4): 520−534. doi: 10.1175/1520-0493(1999)127<0520:CSOHAR>2.0.CO;2 [26] 潘伦湘. 2012. 西北太平洋地区台风闪电活动特征及成因研究 [D]. 中国科学院研究生院博士学位论文.Pan Lunxiang. 2012. Characteristics and causes of typhoon lightning activity in the Northwest Pacific Ocean [D]. Ph. D. dissertation (in Chinese), Graduate University of Chinese Academy of Science. [27] 潘伦湘, 郄秀书. 2010. 0709号超强台风圣帕(Sepat)的闪电活动特征 [J]. 大气科学, 34(6): 1088−1098. doi: 10.3878/j.issn.1006-9895.2010.06.05Pan Lunxiang, Qie Xiushu. 2010. Lightning activity in super typhoon Sepat (0709) [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 34(6): 1088−1098. doi: 10.3878/j.issn.1006-9895.2010.06.05 [28] 潘伦湘, 郄秀书, 刘冬霞, 等. 2010. 西北太平洋地区强台风的闪电活动特征 [J]. 中国科学: 地球科学, 40(2): 252–260.Pan Lunxiang, Qie Xiushu, Liu Dongxia, et al. 2010. The lightning activities in super typhoons over the Northwest Pacific [J]. Science China Earth Sciences, 538): 1241–1248. doi:10.1360/zd2010-40-2-252 [29] Petersen W A, Cifelli R C, Rutledge S A, et al. 1999. Shipborne dual-Doppler operations during TOGA COARE: Integrated observations of storm kinematics and electrification [J]. Bull. Amer. Meteor. Soc., 80(1): 81−98. doi: 10.1175/1520-0477(1999)080<0081:SDDODT>2.0.CO;2 [30] Price C, Asfur M, Yair Y. 2009. Maximum hurricane intensity preceded by increase in lightning frequency [J]. Nat. Geosci., 2(5): 329−332. doi: 10.1038/ngeo477 [31] 邱振峰. 2020. 西北太平洋台风演变过程中的闪电活动特征研究 [D]. 南京信息工程大学硕士学位论文.Qiu Zhenfeng. 2020. Study on the characteristics of lightning activity during the evolution of typhoons in the Northwest Pacific [D]. M. S. thesis (in Chinese), Nanjing University of Information Science & Technology. doi:10.27248/d.cnki.gnjqc.2020.000201 [32] Reinhart B, Fuelberg H, Blakeslee R, et al. 2014. Understanding the relationships between lightning, cloud microphysics, and airborne radar-derived storm structure during Hurricane Karl (2010) [J]. Mon. Wea. Rev., 142(2): 590−605. doi: 10.1175/MWR-D-13-00008.1 [33] 师正, 谭涌波, 唐慧强, 等. 2015. 气溶胶对雷暴云起电以及闪电发生率影响的数值模拟 [J]. 大气科学, 39(5): 941−952. doi: 10.3878/j.issn.1006-9895.1412.14230Shi Zheng, Tan Yongbo, Tang Huiqiang, et al. 2015. A numerical study of aerosol effects on the electrification and flash rate of thunderstorms [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 39(5): 941−952. doi: 10.3878/j.issn.1006-9895.1412.14230 [34] Shi Z, Tan Y B, Liu Y P, et al. 2018. Effects of relative humidity on electrification and lightning discharges in thunderstorms [J]. Terr. Atmos. Oceanic Sci., 29(6): 695−708. doi: 10.3319/TAO.2018.09.06.01 [35] Stevenson S N, Corbosiero K L, Abarca S F. 2016. Lightning in eastern North Pacific tropical cyclones: A comparison to the North Atlantic [J]. Mon. Wea. Rev., 144(1): 225−239. doi: 10.1175/MWR-D-15-0276.1 [36] 孙萌宇, 郄秀书, 刘冬霞, 等. 2020. 北京地区闪电活动与气溶胶浓度的关系研究 [J]. 地球物理学报, 63(5): 1766−1774. doi: 10.6038/cjg2020N0095Sun Mengyu, Qie Xiushu, Liu Dongxia, et al. 2020. Analysis of potential effects of aerosol on lightning activity in Beijing metropolitan region [J]. Chinese J. Geophys. (in Chinese), 63(5): 1766−1774. doi: 10.6038/cjg2020N0095 [37] Takahashi T. 1978. Riming electrification as a charge generation mechanism in thunderstorms [J]. J. Atmos. Sci., 35(8): 1536−1548. doi: 10.1175/1520-0469(1978)035<1536:reaacg>2.0.co;2 [38] Virts K S, Wallace J M, Hutchins M L, et al. 2013. Highlights of a new ground-based, hourly global lightning climatology [J]. Bull. Amer. Meteor. Soc., 94(9): 1381−1391. doi: 10.1175/BAMS-D-12-00082.1 [39] Wadler J B, Rogers R F, Reasor P D. 2018. The relationship between spatial variations in the structure of convective bursts and tropical cyclone intensification as determined by airborne Doppler radar [J]. Mon. Wea. Rev., 146(3): 761−780. doi: 10.1175/MWR-D-17-0213.1 [40] Wang B, Zhou X. 2008. Climate variation and prediction of rapid intensification in tropical cyclones in the western North Pacific [J]. Meteor. Atmos. Phys., 99(1–2): 1–16. doi:10.1007/s00703-006-0238-z [41] 王芳, 郄秀书, 崔雪东. 2017. 西北太平洋地区热带气旋闪电活动的气候学特征及其与气旋强度变化的关系 [J]. 大气科学, 41(6): 1167−1176. doi: 10.3878/j.issn.1006-9895.1704.17102Wang Fang, Qie Xiushu, Cui Xuedong. 2017. Climatological characteristics of lightning activity within tropical cyclones and its relationship to cyclone intensity change over the Northwest Pacific [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 41(6): 1167−1176. doi: 10.3878/j.issn.1006-9895.1704.17102 [42] 王晓雅, 蒋卫国, 邓越, 等. 2019. “山竹”台风影响地区的小时降雨动态变化及危险性动态评估 [J]. 灾害学, 34(3): 202−208. doi: 10.3969/j.issn.1000-811X.2019.03.037Wang Xiaoya, Jiang Weiguo, Deng Yue, et al. 2019. Hourly rainfall dynamics and hazard dynamic assessment of Mangkhut typhoon-affected areas [J]. Journal of Catastrophology (in Chinese), 34(3): 202−208. doi: 10.3969/j.issn.1000-811X.2019.03.037 [43] Wang Y, Lee K H, Lin Y, et al. 2014. Distinct effects of anthropogenic aerosols on tropical cyclones [J]. Nat. Climate Change, 4(5): 368−373. doi: 10.1038/nclimate2144 [44] Wiens K C, Rutledge S A, Tessendorf S A. 2005. The 29 June 2000 supercell observed during STEPS. Part II: Lightning and charge structure [J]. J. Atmos. Sci., 62(12): 4151−4177. doi: 10.1175/JAS3615.1 [45] Williams E R. 1988. The electrification of thunderstorms [J]. Sci. Amer., 259(5): 88−99. doi: 10.1038/scientificamerican1188-88 [46] Williams E R, Sátori G. 2004. Lightning, thermodynamic and hydrological comparison of the two tropical continental chimneys [J]. J. Atmos. Sol-Terr. Phys., 66(13–14): 1213–1231. doi:10.1016/j.jastp.2004.05.015 [47] Yang J, Li L L, Zhao K F, et al. 2019. A comparative study of Typhoon Hato (2017) and Typhoon Mangkhut (2018)—Their impacts on coastal inundation in Macau [J]. J. Geophys. Res., 124(12): 9590−9619. doi: 10.1029/2019jc015249 [48] 杨美荣, 袁铁, 郄秀书, 等. 2011. 西北太平洋热带气旋的闪电活动、雷达反射率和冰散射信号特征分析 [J]. 气象学报, 69(2): 370−380. doi: 10.11676/qxxb2011.032Yang Meirong, Yuan Tie, Qie Xiushu, et al. 2011. An analysis of the characteristics of lightning activities, radar reflectivity and ice scattering for tropical cyclones over the western North Pacific [J]. Acta Meteor. Sinica (in Chinese), 69(2): 370−380. doi: 10.11676/qxxb2011.032 [49] 张文娟. 2013. 热带气旋闪电活动特征及其与气旋特性演变的关系研究 [D]. 中国气象科学研究院博士学位论文.Zhang Wenjuan. 2013. Characteristics of lightning activity in tropical cyclones and their relationship with the evolution of cyclone characteristics [D]. Ph. D. dissertation (in Chinese), Chinese Academy of Meteorological Sciences. [50] 杨云月, 许涛, 罗翠榆, 等. 2020. 典型厄尔尼诺期间台风降水δ18O变化分析: 以2018年22号台风“山竹”为例 [J]. 热带海洋学报, 39(4): 34−41. doi: 10.11978/2019081Yang Yunyue, Xu Tao, Luo Cuiyu. 2020. Analysis on the variation of typhoon precipitation δ18O during typical El Niño event: A case study of Typhoon Mangkhut (2018) [J]. Journal of Tropical Oceanography (in Chinese), 39(4): 34−41. doi: 10.11978/2019081 [51] Zhang W J, Zhang Y J, Zheng D, et al. 2012. Lightning distribution and eyewall outbreaks in tropical cyclones during landfall [J]. Mon. Wea. Rev., 140(11): 3573−3586. doi: 10.1175/MWR-D-11-00347.1 [52] Zhang W J, Hui W, Lyu W, et al. 2020a. FY-4A LMI observed lightning activity in super typhoon Mangkhut (2018) in comparison with WWLLN Data [J]. J. Meteor. Res., 34(2): 336−352. doi: 10.1007/s13351-020-9500-4 [53] Zhang W J, Zhang Y J, Zheng D, et al. 2020b. Quantifying the contribution of tropical cyclones to lightning activity over the Northwest Pacific [J]. Atmos. Res., 239: 104906. doi: 10.1016/j.atmosres.2020.104906 [54] 朱润鹏, 袁铁, 李万莉, 等. 2013. 基于卫星观测资料的全球闪电活动特征研究 [J]. 气候与环境研究, 18(5): 639−650. doi: 10.3878/j.issn.1006-9585.2012.12017Zhu Runpeng, Yuan Tie, Li Wanli, et al. 2013. Characteristics of global lightning activities based on satellite observations [J]. Climatic and Environmental Research (in Chinese), 18(5): 639−650. doi: 10.3878/j.issn.1006-9585.2012.12017 -
下载:
点击查看大图
计量
- 文章访问数: 262
- HTML全文浏览量: 27
- PDF下载量: 60
- 被引次数: 0
