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高原气象  2016, Vol. 35 Issue (6): 1498-1511    DOI: 10.7522/j.issn.1000-0534.2016.00070
论文     
中低层增温对强降水中涡旋形成的敏感性研究
陈贵川1, 吴钲2, 谌芸3, 李强1, 朱岩1
1. 重庆市气象台, 重庆 401147;
2. 重庆市气象科学研究所, 重庆 401147;
3. 国家气象中心, 北京 100081
Sensitivity Study of Middle-low Level Temperature Increase for Mesovortex Formation in a Heavy Rainfall Case
CHEN Guichuan1, WU Zheng2, CHEN Yun3, LI Qiang1, ZHU Yan1
1. Chongqing Meteorological Observatory, Chongqing 401147, China;
2. Chongqing Institute of Meteorology, Chongqing 401147, China;
3. National Meteorological Center, Beijing 100081, China
 全文: PDF(35652 KB)   HTML
摘要:

2012年7月21日22:00-23:00重庆盘龙出现了180.9 mm·h-1的极端强降水,这在西南低涡暴雨中比较罕见的。通过对雷达资料的分析,发现此次极端强降水过程中有近于中气旋强度的中涡旋形成和发展。为了研究中低层增温对强降水中涡旋形成的作用,利用中尺度数值模式WRF-ARW,结合雷达资料同化的ARPS-3DVAR方法和复杂云分析方案,并对中低层进行中心增温同化敏感性实验,对上述过程中出现的近于中气旋强度的强降水中涡旋进行了数值模拟。结果表明:全球预报系统GFS(Global Forecasting System)预报场同化雷达反射率因子和径向风资料之后,能较好地模拟出西南低涡东侧准线性对流系统(Qusi-Linear Convective System,QLCSs)、强降水落区、强降水中心、盘龙附近的β中尺度气旋式环流以及镶嵌在其中的γ中尺度涡旋(即中涡旋);850 hPa和700 hPa经过中心增温同化后能增强中涡旋的强度,当700 hPa中心增温2℃同化后能模拟出与盘龙附近相似的近于中气旋强度的中涡旋。同时,此次强降水中涡旋形成的机制为中低层异常高的温湿条件导致异常强的对流不稳定性,上升运动快速发展,中低层水汽通量辐合迅速增强,大量水汽凝结并急剧释放潜热,高温高湿气柱随上升运动迅速增长导致增温中心附近位势高度急剧下降,水平位势梯度加大,风速增大,中涡旋迅速发展增强到中气旋的强度。表明中低层垂直风切变偏弱的环境中中低层异常高的温湿条件是形成强上升运动,促进近于中气旋强度的中涡旋形成的重要条件。

关键词: 数值模拟中心增温同化西南低涡中涡旋中气旋    
Abstract:

An extreme precipitation event characterized by hourly rainfall of 180.9 mm·h-1 occurred near Panlong, Chongqing from 22:00 to 23:00 on July 21 2012, which was fairly rare among rainstorms caused by the southwest vortex. An analysis of Radar data reveals that during the process, a mesovortex that almost rivals a mesocyclone was observed to had been forming and evolving. To investigate the impact of low-level warming exerted on the formation of mesovortex, basing on WRF model, a set of numerical simulations that combined complex cloud analysis and ARPS-3DVAR method that incorporated radar assimilation, together with the sensitivity experiment of center temperature increment assimilation (CTIA) on low-level atmosphere, had been carried out to explore the relationship between mesovortex and aforementioned extreme precipitation. The results indicate that after the assimilation of reflectivity and radial velocity of radar, the GFS forecast performs well on the simulation of the qusi-linear convective system (QLCSs), the area and the center of heavy rainfall and the meso-β-scale cyclonic circulation in the eastern part of Southwest vortex near Panlong with a meso-γ-scale vortex embedded in. The intensity of meso-γ-scale vortex was increased due to CTIA done at both level of 850 hPa and 700 hPa. With 2 Celsius degree's incensement of CTIA at 700 hPa, the mesovortex which was comparable to a mesocyclone was successfully simulated. Meanwhile, the mechanism of the forming of mesovortex could be explained as follows:the abnormal warmness and humidity at low level lead to the abnormal intensification of convective instability, which further triggered the booming development of updraft. As vapor flux converges drastically, a large amount of vapor condenses, rapidly releasing latent heat. The geopotential height near the warming center dropped rapidly as warm and humid air column stretches due to the intensification of updraft. The horizontal gradient of geopotential height thus increase as well as the wind speed surges simultaneously. The mesovortex evolves into a typical mesocyclone swiftly. These indicate that in the background of weak vertical wind shear, the abnormal warmness and humidity at lower level provides significant prerequisite for the formation of intense updraft and the mesovortex which is comparable to mesocyclone.

Key words: Numerical simulation    Central temperature increment assimilation    Southwest vortex    Mesovortex    Mesocyclone
收稿日期: 2016-06-23 出版日期: 2016-12-20
:  P435+.1  
基金资助:

公益性行业(气象)科研专项(GYHY201406001);中国气象局气象关键技术集成与应用项目(CMAGJ2015M49),中国气象局预报员专项(CMAYBY2013-055)

通讯作者: 谌芸.E-mail:chenyun@cma.gov.cn     E-mail: chenyun@cma.gov.cn
作者简介: 陈贵川(1973-),男,重庆万州人,正高级工程师,主要从事天气预报、数值模拟研究.E-mail:cgccq@163.com
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引用本文:

陈贵川, 吴钲, 谌芸, 李强, 朱岩. 中低层增温对强降水中涡旋形成的敏感性研究[J]. 高原气象, 2016, 35(6): 1498-1511.

CHEN Guichuan, WU Zheng, CHEN Yun, LI Qiang, ZHU Yan. Sensitivity Study of Middle-low Level Temperature Increase for Mesovortex Formation in a Heavy Rainfall Case. PLATEAU METEOROLOGY, 2016, 35(6): 1498-1511.

链接本文:

http://www.gyqx.ac.cn/CN/10.7522/j.issn.1000-0534.2016.00070        http://www.gyqx.ac.cn/CN/Y2016/V35/I6/1498

Browning K A. 1978. The structure and mechanisms of hailstorms[J]. Meteor Monogr, 38:1-36.

Browning K A. 1962. Cellular structures of convective storms[J]. Meteor Mag, 91(1085):341-350.

DeWald V L, Funk T W. 2000. WSR-88D reflectivity and velocity trends of a damaging squall line event on 20 April 1996 over south-central Indiana and central Kentucky[C]//Preprints, 20th Conf on Severe Local Storms, Orlando, FL, Amer Meteor Soc, 177-180.

Forbes G S, Wakimoto R M. 1983. A concentrated outbreak of tornadoes, downbursts and microbursts, and implications regarding vortex classification[J]. Mon Wea Rev, 111:220-235.

Fujita T T. 1978. Manual of downburst identification for project NIMROD[C]//Satellite and Mesometeorology Research Paper 156, Dept. of Geophysical Sciences. Chicago:University of Chicago, 104.

Hu M, Xue M, Brewster K. 2006a. 3DVAR and cloud analysis with WSR-88D level-Ⅱdata for the prediction of the Fort Worth Tornadic thunderstorms. Part I:Cloud analysis and its impact[J]. Mon Wea Rev, 134:675-698.

Hu M, Xue M, Brewster K. 2006b. 3DVAR and cloud analysis with WSR-88D level-Ⅱdata for the prediction of the Fort Worth Tornadic thunderstorms. Part Ⅱ:Impact of radial velocity analysis via 3DVAR[J]. Mon Wea Rev, 134:699-721.

Marwitz J D. 1972. The structure and motion of severe hailstorms. PartⅠ, Ⅱ, Ⅲ[J]. J Appl Meteor, 11(1):166-201.

Miller D J, Johns R H. 2000. A detailed look at extreme wind damage in derecho events[C]//Preprints, 20th Conf on Severe Local Storms, Orlando, FL, Amer Meteor Soc, 52-55.

Moller A R, Doswell C A Ⅲ, Foster M P, et al. 1994. The operational recognition of supercell thunderstorm envirments and storm structures[J]. Wea Forecasting, 9:327-347.

Smull B F, Houze R A. 1987. Rear inflow in squall lines with trailing stratiform precipitation[J]. Mon Wea Rev, 115:2869-2889.

Trapp R J, Weisman M L. 2003. Low-Level Mesovortices within Squall Lines and Bow Echoes. PartⅡ:Their Genesis and Implications[J]. Mon Wea Rev, 131:2804-2823.

Wakimoto R M. 1983. The West Bend, Wisconsin storm of 4 April 1981:A problem in operational meteorology[J]. J Climate Appl Meteor, 22:181-189.

Weisman M L, Trapp R J. 2003. Low-Level Mesovortices within Squall Lines and Bow Echoes. Part I:Overview and Dependence on Environmental Shear[J]. Mon Wea Rev, 131:2779-2803.

Zhang J, Carr F H, Brewster K. 1998. ADAS cloud analysis 12th Conference on Numerical Weather Prediction, Phoenix[C]//Amer Meteor Soc, 185-188.

陈宝君, 郑凯琳, 郭学良. 2012. 超级单体风暴中大冰雹增长机制的模拟研究[J]. 气候与环境研究, 17(6):767-778. Chen Baojun, Zheng Kailin, Guo Xueliang. 2012. Numerical investigation on the growth of large hail in a simulated supercell thunderstorm[J]. Climatic and Environmental Research, 17 (6):767-778.

陈贵川, 谌芸, 张勇, 等. 2013. "12.7.21"西南涡极端强降雨的成因分析[J]. 气象, 39(12):1529-1541. Chen Guichuan, Chen Yun, Zhang Yong, et al. 2013. Causes Analysis of the Southwest Vortex Extremely Heavy Rainfall on 21 July 2012. Meteor Mon[J], 39(12):1529-1541.

陈明轩, 王迎春, 肖现, 等. 2012. 基于雷达资料四维变分同化和三维云模式对一次超级单体风暴发展维持热动力机制的模拟分析[J]. 大气科学, 36(5):929-944. Chen Mingxuan, Wang Yingchun, Xiao Xian, et al. 2012. A case simulation analysis on thermodynamical mechanism of supercell storm development using 3-D cloud model and 4-D variational assimilation on radar data[J]. Chinese J Atmos Sci, 36(5):929-944.

戴建华, 陶岚, 丁杨, 等. 2012. 一次罕见飑前强降雹超级单体风暴特征分析[J]. 气象学报, 70(4):609-627. Dai Jianhua, Tao Lan, Ding Yang, et al. 2012. Case analysis of a large hail-producing severe supercell ahead of a squall line[J]. Acta Meteor Sinica, 70(4):609-627.

高守亭. 1987. 流场配置及地形对西南低涡形成的动力作用[J]. 大气科学, 11(3):263-271. Gao Shouting. 1987. The dynamic action of the disposition of the fluid fields and the topography on the formation of the south-west vortex[J]. Chinese J Atmos Sci, 11(3):263-271.

李国平, 万军, 卢敬华. 1991. 暖性西南低涡生成的一种可能机制[J]. 应用气象学报, 2(1):91-99. Li Guoping, Wan Jun, Lu Jinghua. 1991. A potential mechanism of the warm vortex genesis in Southwest China[J]. J Appl Meteor Sci, 2(1):91-99.

廖玉芳, 俞小鼎, 唐小新, 等. 2007a. 基于多普勒天气雷达观测的湖南超级单体风暴特征[J]. 南京气象学院学报, 30(4):433-443. Liao Yufang, Yu Xiaoding, Tang Xiaoxin, et al. 2007a. Characteristics of supercell storms in hunan detected by Doppler weather radars[J]. J Nanjing Insti Meteor, 30(4):433-443.

廖玉芳, 俞小鼎, 唐小新. 2007b. 2004年4月29日常德超级单体研究[J]. 南京气象学院学报, 30(5):579-589. Liao Yufang, Yu Xiaoding, Tang Xiaoxin. 2007a. Investigation into supercell storm on 29 April 2004 in Changde[J]. J Nanjing Insti Meteor, 30(5):579-589.

刘晓冉, 李国平. 2014. 一次东移型西南低涡的数值模拟及位涡诊断[J]. 高原气象, 33(5):1204-1216. Liu Xiaoran, Li Guoping. 2014. Numerical simulation and potential vorticity diagnosis of an eastward moving southwest vortex[J]. Plateau Meteor, 33(5):1204-1216. DOI:10.7522/j. issn. 1000-0534.2013.00151.

卢敬华. 1986. 西南低涡概论[M]. 北京:气象出版社, 129-146. Lu Jinghua. 1988. Introduction to the southwest vortex[M]. BeiJing:China Meteotological Press, 129-146.

卢敬华. 1988. 利用热成风适应原理对暖性西南低涡生成机制的再分析[J]. 高原气象, 7(4):345-356. Lu Jinghua. 1988. Apply the thermal wind adjustment theorem to analyse genesis mechanism of the warm southwest vortex of China[J]. Plateau Meteor, 7(4):345-356.

陶诗言. 1980. 中国之暴雨[M]. 北京:科学出版社, 91-145. Tao Shiyan. 1980. China storms[M]. BeiJing:China Science Press, 91-145.

王福侠, 俞小鼎, 闫雪瑾. 2014. 一次超级单体分裂过程的雷达回波特征分析[J]. 气象学报, 72(1):152-167. Wang Fuxia, Yu Xiaoding, Yan Xuejin. 2014. Analysis of the splitting processes of the supercell storms based on the Doppler weather radar data[J]. Acta Meteor Sinica, 72(1):152-167.

王秀明, 钟青, 韩慎友. 2009. 一次冰雹天气强对流(雹)云演变及超级单体结构的个例模拟研究[J]. 高原气象, 28(2):352-365. Wang Xiuming, Zhong Qing, Han Shenyou. 2009. A numerical case study on the evolution of hail cloud and the three-dimensional structure of supercell[J]. Plateau Meteor, 28(2):352-365.

吴芳芳, 俞小鼎, 张志刚, 等. 2013. 苏北地区超级单体风暴环境条件与雷达回波特征[J]. 气象学报, 71(2):209-227. Wu Fangfang, Yu Xiaoding, Zhang Zhigang, et al. 2013. A study of the environmental conditions and radar echo characteristics of the supercell-storms in northern Jiangsu[J]. Acta Meteor Sinica, 71(2):209-227.

吴木贵, 张信华, 傅伟辉, 等. 2013.2010年3月5日闽北经典超级单体风暴天气过程分析[J]. 高原气象, 32(1):250-267. Wu Mugui, Zhang Xinhua, Fu Weihu, et al. 2013. Analysis on weather process of classic supercell storm in northern part of Fujian on 5 March 2010[J]. Plateau Meteor, 32(1):250-267. DOI:10.7522/j. issn. 1000-0534.2013.00025.

徐琪, 慕熙昱, 刘韻蕊, 等. 2015. 南京空域一次高空致灾冰粒过程的可预报性分析[J]. 高原气象, 34(1):258-268. Xu qi, Mu Xiyu, Liu Yunrui, et al. 2015. Analysis of predictability on a high altitude hail/graupel disaster weather in Nanjing airspace[J]. Plateau Meteor, 34(1):258-268. DOI:10.7522/j. issn. 1000-0534.2013.00105.

俞小鼎, 姚秀萍, 熊廷南, 等. 2006a. 多普勒天气雷达原理与业务应用[M]. 北京:气象出版社, 90-129, 130-163, 172-174, 208. Yu xiaoding, Yao Xiuping, Xiong Tingnan, et al. 2006a. Principle and Application of Doppler Weather Radar[M]. BeiJing:China Meteotological Press, 90-128, 130-163, 172-174, 208.

俞小鼎, 张爱民, 郑媛媛, 等. 2006b. 一次系列下击暴流事件的多普勒天气雷达分析[J]. 应用气象学报, 17(4):385-393. Yu Xiaoding, Zhang Aimin, Zheng Yuanyuan, et al. 2006b. Doppler radar analysis on a series of downburst events[J]. J Appl Meteor Sci, 17(4):385-393.

俞小鼎, 郑媛媛, 张爱民, 等. 2006c. 安徽一次强烈龙卷的多普勒天气雷达分析[J]. 高原气象, 25(5):914-924. Yu Xiaoding, Zheng Yuanyuan, Zhang Aimin, et al. 2006c. The detection of a severe tornado event in Anhui with China new generation weather radar[J]. Plateau Meteor, 25(5):914-924.

俞小鼎, 郑媛媛, 廖玉芳, 等. 2008. 一次伴随强烈龙卷的强降水超级单体风暴研究[J]. 大气科学, 32(3):508-522. Yu Xiaoding, Zheng Yuanyuan, Liao Yufang, et al. 2008. Observational investigation of a tornadic heavy precipitation supercell storm[J]. Chinese J Atmos Sci, 32(3):508-522.

张琳娜, 郭锐, 何娜, 等. 2015. "7·21"北京特大暴雨过程龙卷形成可能性探究[J]. 高原气象, 34(4):1074-1083. Zhang Linna, Guo rui, He na, et al. 2015. Study on whether a tornado occurred of ‘7·21’ rainstorm in Beijing[J]. Plateau Meteor, 34(4):1074-1083. DOI:10.7522/j. issn. 1000-0534.2014.00025.

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