Duan Jingxin, Zhao Tianliang, Xu Xiangde, et al. Simulation of basin topography impacts on rainstorm in Sichuan. J Appl Meteor Sci, 2018, 29(3): 307-320. DOI:  10.11898/1001-7313.20180305.
Citation: Duan Jingxin, Zhao Tianliang, Xu Xiangde, et al. Simulation of basin topography impacts on rainstorm in Sichuan. J Appl Meteor Sci, 2018, 29(3): 307-320. DOI:  10.11898/1001-7313.20180305.

Simulation of Basin Topography Impacts on Rainstorm in Sichuan

DOI: 10.11898/1001-7313.20180305
  • Received Date: 2017-10-25
  • Rev Recd Date: 2018-02-02
  • Publish Date: 2018-05-31
  • Topography, especially the height and shape conditions have significant effects on precipitation. Previous studies focus on effects of mountain topography upon precipitation, while influencing mechanisms of the basin topography are not widely discussed. The Weather Research and Forecasting (WRF) with Chemistry model is used to simulate a heavy rain event which occurs on 20 July 2012, over Sichuan Basin. A sensitive test is designed in which the topography of Sichuan Basin is uplifted, with other conditions the same as the control test. The topography in the sensitivity test shows a trend of slow decline from west to east, eliminating the role of basin topography, but keeping the influence of the Tibetan Plateau around the Basin.From the atmospheric dynamics, thermal and cloud micro-physics standpoints, diagnostic analysis is used to analyze results of these two tests, and differences between two experiments are discussed. Results show that the time of heavy rainstorm in the control test is later than that in the sensitivity test, and the rainfall intensity in control test is strongly enhanced. From the point of atmospheric dynamics, when southwesterly airflow through the basin from south, a stronger positive vorticity center forms in the south of the Basin in the lower layer of troposphere in the control test, and southern wind is weakened. Therefore, the water vapor and energy reach the northern part of the Basin later, leading to the precipitation delaying. At the same time, with the southward wind transport, the positive relative vorticity of the lower layer in the northern part of the Basin is continuously strengthened. Favorable dynamic structure strengthens the vertical motion and thus increases the precipitation intensity. From the thermodynamic view, there is more heat and water vapor in control test due to its lower height. Besides, these variables accumulate subjected to topographic dynamics, and are less likely to diffuse, providing sufficient water vapor for the rainstorm. In addition, the high temperature and high humidity condition makes the low level of the control test accumulates moist static energy. When airflow carrying moist static energy reaches the northwest of the Basin, strong upward is stimulated under the influence of topography and the positive relative vorticity in the lower troposphere. From the opinion of micro-physics, the stronger vertical motion provides advantage for the vertical development of the cloud system, and more water vapor provides greater supersaturation for precipitation particles in the control test. Under these conditions, precipitation particles, especially rain water, snow crystals and graupel, are generated and transformed in large quantities, enhancing the precipitation intensity to heavy rainstorm.
  • Fig. 1  Accumulated precipitation(the shaded) and topography(the contour, unit:m) from 2000 BT 20 July to 1100 BT 21 July in 2012

    (a)observation, (b)control test, (c)sensitivity test, (d)the difference between control test and sensitivity test (the topography in Fig. 1a from control test)

    Fig. 2  Rain rate of rainstorm center from 20 Jul to 21 Jul in 2012

    Fig. 3  10 m wind speed, 2 m relative humidity and 2 m temperature for observation and control test from 20 Jul to 21 Jul in 2012

    Fig. 4  Wind(the vector) and relative vorticity(the shaded) at 800 hPa from 20 Jul to 21 Jul in 2012 (difference is between control test and sensitivity test)

    (a)control test at 2100 BT 20 Jul, (b)control test at 0100 BT 21 Jul, (c)control test at 0500 BT 21 Jul, (d)difference at 2100 BT 20 Jul, (e)difference at 0100 BT 21 Jul, (f)difference at 0500 BT 21 Jul

    Fig. 5  Cross-section of relative vorticity(the shaded) and wind(the vector) difference between control test and sensitivity test along 104.6°E from 20 Jul to 21 Jul in 2012

    (a)2100 BT 20 Jul, (b)0100 BT 21 Jul, (c)0500 BT 21 Jul

    Fig. 6  Cross-section of wind(the vector) temperature(the contour, unit:℃) and specific humidity(the shaded) along 104.6°E from 20 Jul to 21 Jul 2012

    (a)2100 BT 20 Jul in control test, (b)0100 BT 21 Jul in control test, (c)0500 BT 20 Jul in control test, (d)2100 BT 20 Jul in sensitivity test, (e)0100 BT 21 Jul in sensitivity test, (f)0500 BT 21 Jul in sensitivity test

    Fig. 7  Cross-section of moist static energy(the contour, unit:J·kg-1) from 20 Jul to 21 Jul in 2012(the shaded denotes the terrain)

    (a)2100 BT 20 Jul in control test, (b)0100 BT 21 Jul in control test, (c)0500 BT 21 Jul in control test, (d)2100 BT 20 Jul in sensitivity test, (e)0100 BT 21 Jul in sensitivity test, (f)0500 BT 21 Jul in sensitivity test

    Fig. 8  Time series of convective available potential energy and convective inhibition energy difference between the control test and the sensitivity test from 20 Jul to 21 Jul in 2012

    Fig. 9  Cross-section of temperature(the contour, unit:℃), wind(the vector) and mass concentration(the shade) of precipitation particle along 104.6°E from 20 Jul to 21 Jul in 2012

    (a)cloud water in control test at 0500 BT 21 Jul, (b)rain water in control test at 0500 BT 21 Jul, (c)cloud water in sensitivity test at 0100 BT 21 Jul, (d)rain water in sensitivity test at 0100 BT 21 Jul

    Fig. 10  Cross-section of temperature(the contour, unit:℃), wind(the vector) and mass concentration(the shade) of precipitation particle from 20 Jul to 21 Jul in 2012

    (a)ice crystals in control test at 0500 BT 21 Jul, (b)snow crystals in control test at 0500 BT 21 Jul, (c)graupel in control test at 0500 BT 21 Jul, (d)ice crystals in sensitivity test at 0100 BT 21 Jul, (e)snow crystals in sensitivity test at 0100 BT 21 Jul, (f)graupel in sensitivity test at 0100 BT 21 Jul

  • [1]
    姜大膀, 王会军.20世纪后期东亚夏季风年代际减弱的自然属性.科学通报, 2005, 50(20):2256-2262. doi:  10.3321/j.issn:0023-074X.2005.20.013
    [2]
    倪允琪, 周秀骥, 张人禾, 等.我国南方暴雨的试验与研究.应用气象学报, 2006, 17(6):690-704. doi:  10.11898/1001-7313.20060607
    [3]
    杨薇, 苗峻峰, 谈哲敏.太湖地区湖陆风对雷暴过程影响的数值模拟.应用气象学报, 2014, 25(1):59-70. doi:  10.11898/1001-7313.20140107
    [4]
    王学锋, 郑小波, 黄玮, 等.近47年云贵高原汛期强降水和极端降水变化特征.长江流域资源与环境, 2010, 19(11):1350-1355.
    [5]
    胡豪然, 毛晓亮, 梁玲.近50年四川盆地汛期极端降水事件的时空演变.地理学报, 2009, 64(3):278-288. doi:  10.11821/xb200903003
    [6]
    谌芸, 李强, 李泽椿.青藏高原东北部强降水天气过程的气候特征分析.应用气象学报, 2006, 17(增刊Ⅰ):98-103. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=yyqxxb2006z1014
    [7]
    楼小凤, 胡志晋, 王广河.对流云降水过程中地形作用的数值模拟.应用气象学报, 2001, 12(增刊Ⅰ):113-121. http://www.cqvip.com/QK/97586X/2001z1/1000514972.html
    [8]
    何立富, 陈涛, 孔期.华南暖区暴雨研究进展.应用气象学报, 2016, 27(5):559-569. doi:  10.11898/1001-7313.20160505
    [9]
    Miglietta M M, Rotunno R.Numerical simulations of sheared conditionally unstable flows over a mountain ridge.J Atmos Sci, 2009, 66(7):1865-1885. doi:  10.1175/2009JAS2902.1
    [10]
    姚文清, 徐祥德.一次特大暴雨形成中天气尺度和次天气尺度系统的作用.应用气象学报, 2003, 14(3):287-298. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20030336&flag=1
    [11]
    廖菲, 胡娅敏, 洪延超.地形动力作用对华北暴雨和云系影响的数值研究.高原气象, 2009, 28(1):115-126. http://www.cqvip.com/QK/91655X/200901/29556456.html
    [12]
    刘洋, 钱贞成, 朱宇宁, 等."8·31"云阳特大暴雨地形动力作用数值研究.高原山地气象研究, 2015, 35(3):9-17. http://industry.wanfangdata.com.cn/dl/Magazine?magazineId=scqx&yearIssue=2015_3
    [13]
    Wang D, Miao J, Tan Z.Impacts of topography and land cover change on thunderstorm over the Huangshan (Yellow Mountain) area of China.Natural Hazards, 2013, 67(2):675-699. doi:  10.1007/s11069-013-0595-0
    [14]
    何光碧, 屠妮妮, 张利红.一次低涡暴雨过程发生机制及其模式预报分析.暴雨灾害, 2014, 33(3):239-246. http://www.cnki.com.cn/Article/CJFDTotal-HBQX201403006.htm
    [15]
    刘新超, 陈永仁.两次高原涡与西南涡作用下的暴雨过程对比分析.高原山地气象研究, 2014, 34(1):1-7. http://mall.cnki.net/magazine/Article/SCCX201401001.htm
    [16]
    卢萍, 郑伟鹏, 赵兴炳.川西西南涡加密探空资料分析及数值模拟试验.高原山地气象研究, 2012, 32(1):1-7. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=scqx201201001
    [17]
    苏涛, 苗峻峰, 蔡亲波.海南岛海风雷暴结构的数值模拟.地球物理学报, 2016, 59(1):59-78. doi:  10.6038/cjg20160106
    [18]
    张小玲, 程麟生."96.1"暴雪期中尺度切变线发生发展的动力诊断Ⅰ:涡度和涡度变率诊断.高原气象, 2000, 19(3):285-294. http://d.wanfangdata.com.cn/Periodical_gyqx200003003.aspx
    [19]
    张元春, 孙建华, 傅慎明.冬季一次引发华北暴雪的低涡涡度分析.高原气象, 2012, 31(2):387-399. http://www.oalib.com/paper/4182538
    [20]
    赵宇, 高守亭.对流涡度矢量在暴雨诊断分析中的应用研究.大气科学, 2008, 32(3):444-456. http://www.cmsjournal.net/qxxb_cn/ch/reader/create_pdf.aspx?file_no=20090405&flag=1&journal_id=qxxb_cn&year_id=2009
    [21]
    吴乃庚, 林良勋, 曾沁, 等.南海季风爆发前罕见连续3场暴雨特征及成因.应用气象学报, 2013, 24(2):129-139. doi:  10.11898/1001-7313.20130201
    [22]
    杨晓霞, 万丰, 刘还珠, 等.山东省春秋季暴雨天气的环流特征和形成机制初探.应用气象学报, 2006, 17(2):183-191. doi:  10.11898/1001-7313.20060209
    [23]
    苏涛, 苗峻峰, 王语卉.辐射参数化对海南岛海风雷暴结构模拟的影响.地球物理学报, 2017, 60(8):3023-3040. doi:  10.6038/cjg20170811
    [24]
    Fan J, Rosenfeld D, Yang Y, et al.Substantial contribution of anthropogenic air pollution to catastrophic floods in Southwest China.Geophys Res Lett, 2015, 42(14):6066-6075. doi:  10.1002/2015GL064479
  • 加载中
  • -->

Catalog

    Figures(10)

    Article views (4128) PDF downloads(423) Cited by()
    • Received : 2017-10-25
    • Accepted : 2018-02-02
    • Published : 2018-05-31

    /

    DownLoad:  Full-Size Img  PowerPoint