论文

上海“7·31”局地强对流快速更新同化数值模拟研究

  • 王晓峰 ,
  • 王平 ,
  • 张蕾 ,
  • 许晓林 ,
  • 李佳
展开
  • 中国气象科学研究院, 北京 100081;2. 中国科学院大学, 北京 100049;3. 中国气象局上海台风研究所/ 中国气象局台风数值预报重点实验室, 上海 200030

收稿日期: 2013-01-09

  网络出版日期: 2015-02-28

基金资助

公益性行业(气象)科研专项(GYHY201006003, GYHY201206006); 上海市科学技术委员会重点基金 (13231203300); 十二五科技支撑计划项目(2012BAC21B02)

Numerical Simulation of ‘7·31' Severe Convection Event in Shanghai Using Rapid Refresh Technique

  • WANG Xiaofeng ,
  • WANG Ping ,
  • ZHANG Lei ,
  • XU Xiaolin ,
  • LI Jia
Expand
  • Chinese Academy of Meteorological Sciences, Beijing 100081, China;2. University of Chinese Academy of Sciences, Beijing 100049, China;3. Shanghai Typhoon Institute of China Meteorological Administration, Key Laboratory of Numerical Modeling for Tropical Cyclone, China Meteorological Administration, Shanghai 200030, China

Received date: 2013-01-09

  Online published: 2015-02-28

摘要

利用雷达、自动气象站、飞机观测(AMDAR)和探空等多种观测资料, 采用中尺度数值预报模式WRF和资料同化系统ADAS, 对2011年7月31日上海局地强对流过程进行了快速更新同化数值试验.结果表明, 数值试验模拟降水的发生时间、落区和随时间演变与实况基本一致, 较好再现了海陆热力差异导致上海南北两支海陆风爆发、形成低层辐合线, 在热岛效应的叠加下进一步增强, 继而引发局地强对流的过程.快速更新同化技术可有效延长此次过程的预警时效, 这为城市强对流业务预报提供了新的思路.

本文引用格式

王晓峰 , 王平 , 张蕾 , 许晓林 , 李佳 . 上海“7·31”局地强对流快速更新同化数值模拟研究[J]. 高原气象, 2015 , 34(1) : 124 -136 . DOI: 10.7522/j.issn.1000-0534.2013.00202

Abstract

Using multi-source observations, such as Doppler radar, AWS, AMDAR and radiosonde measurements, and the high-resolution numerical model WRF as well as the advanced data assimilation system ADAS, a numerical simulation of the server convection event, which occurred in Shanghai on 31 July 2011, was conducted using rapid refresh technique. The results showed that the model correctly predicted this server convective weather process, the timing and location, as well as the variation of the precipitation along with the time were well consistent with the observations. It was also found that due to the thermal difference between land and sea, two sea breeze from different north and south directions met in shanghai area and low level convergence line formed, as a results, weak updraft in boundary layer appeared, combined with the local urban heat island effect, created favorable conditions for triggering the server convections; and the high gradient of moisture between low level and middle level and its unstable vertical structure provided favorable conditions for moisture vertical transportation. The numerical simulation using rapid refresh technique issued early warning of this server convection occurrence 10 hours in advance, and this provided a new way for the megacity operational convection forecasts.

参考文献

[1]Seed A W. A dynamic and spatial scaling approach to advection forecasting[J]. J Appl Meteor, 2003, 42: 381-388.
[2]Pierce C E, Hardaker P J, Collier C G, et al. GANDOLF: A system for generating automated nowcasts of convective precipitation[J]. Meteor Appl, 2000, 7: 341-360.
[3]Lapczak S, Aldcroft E, Stanley-Jones M, et al. The Canadian national radar project[C]. Preprints, 29th International Conf. on Radar Meteorology, Montreal, Canada, Amer Meteor Soc, 1999: 327-330.
[4]Mueller C, Saxen T, Roberts R, et al. NCAR auto-nowcast system[J]. Wea Forecasting, 2003, 18: 545-561.
[5]Mass Clifford. Nowcasting: The promise of new technologies of communication, modeling, and observation[J]. Bull Amer Meteor Soc, 2012, 93: 797-809.
[6]Benjamin S G, Dezs Dévényi, Stephen S W. An hourly assimilation-forecast cycle: The RUC[J]. Mon Wea Rev, 2004, 132: 495-518.
[7]Bornstein R, Lin Q. Urban heat islands and summertime convective thunderstorms in Atlanta: Three case studies[J]. Atmos Environ, 2000, 34: 507-516.
[8]Inamura Tomohiko, Takeki Izumi, Hiroshi Matsuyama, et al. Diagnostic study of the effects of a large city on heavy rainfall as revealed by an ensemble simulation: A case study of central Tokyo[J]. Japan J Appl Meteor Climatol, 2011, 50: 713-728.
[9]Kishtawal C M, Niyogi D, Tewari M, et al. Urbanization signature in the observed heavy rainfall climatology over India[J]. Int J Climatol, 2010, 30: 1908-1916.
[10]殷健, 梁珊珊. 城市化对上海市区域降水的影响[J]. 水文, 2010, 30(2): 66-73.
[11]Baker David R, Barry H Lynn, Aaron Boone, et al. The influence of soil moisture, coastline curvature, and land-breeze circulations on sea-breeze-initiated precipitation[J]. J Hydrometeor, 2001, 2: 193-211.
[12]Shepherd J M, Carter M, Manyin M, et al. The impact of urbanization on current and future coastal precipitation: A case study for Houston[J]. Environ Plann, 2010, 37: 284-304.
[13]陈燕, 蒋维楣. 城市建筑物对边界层结构影响的数值试验研究[J]. 高原气象, 2006, 25(5): 824-833.
[14]陈燕, 蒋维楣, 吴洞, 等. 利用区域边界层模式对杭州热岛的模拟研究[J]. 高原气象, 2004, 23(4): 519-528.
[15]陈磊, 田文涛, 王禅. 半干旱区植被减少与城市化对大气的局地和非局地影响的数值模拟[J]. 高原气象, 2009, 28(2): 233-245.
[16]周定文, 胡隐樵. 下垫面特性突变时的内边界层数值研究[J]. 高原气象, 1988, 7(4): 357-366.
[17]尹红萍, 曹晓岗. 盛夏上海地区副热带高压型强对流特点分析仁[J]. 气象, 2010, 36(8): 19-25.
[18]顾问, 路璐, 施春红, 等. 上海盛夏连续清晨对流天气过程的边界层结构分析[J]. 大气科学研究与应用, 2011, 2: 55-62.
[19]苗曼倩, 唐有华. 长江三角洲夏季海陆风与热岛环流的相互作用及城市化的影响[J]. 高原气象, 1998, 17(3): 280-289.
[20]王晓峰, 许晓林, 张蕾, 等. 上海"7·31"局地强对流观测分析[J]. 高原气象, 2014, 33(6): 16271639, doi: 10.7522/j.issn.1000-0534.2013.00204.
[21]Bratseth A M. Statistical interpolation by means of successive corrections[J]. Tellus, 1986, 38: 439-447.
[22]Wilson J W, Schreiber W E. Initiation of convective storms at radar-observed boundary-layer convergence lines[J]. Mon Wea Rev, 1986, 114: 2516-2536.
[23]Wilson J W, Foote G B, Crook N A, et al. The role of boundary-layer convergence zones and horizontal rolls in the initiation of thunderstorms: A case study[J]. Mon Wea Rev, 1992, 120: 1785-1815.
[24]Wilson J W, Mueller C. Nowcasts of thunderstorm initiation and evolution[J]. Wea Forecasting, 1993, 8: 113-131.
[25]郑祚芳, 张秀丽. 边界层急流与北京局地强降水关系的数值研究[J]. 南京气象学院学报, 2007, 30(4): 457-462.
文章导航

/