Vol.30, NO.5, 2019
Turn off MathJax
Article Contents
Article Navigation >  Journal of Applied Meteorological Science  > 2019  >  30(5): 629-640
Li Fangfang, Chen Qiying, Wu Hongkun. A statistical study of brunt-vaisala frequency with second-level radiosonde data in China. J Appl Meteor Sci, 2019, 30(5): 629-640. DOI:  10.11898/1001-7313.20190511.
Citation: Li Fangfang, Chen Qiying, Wu Hongkun. A statistical study of brunt-vaisala frequency with second-level radiosonde data in China. J Appl Meteor Sci, 2019, 30(5): 629-640. DOI:  10.11898/1001-7313.20190511.
shu

A Statistical Study of Brunt-vaisala Frequency with Second-level Radiosonde Data in China

DOI: 10.11898/1001-7313.20190511
  • 1.

    School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225

  • 2.

    National Meteorological Center, Beijing 100081

  • Received Date: 2018-12-12
  • Rev Recd Date: 2019-05-05
  • Publish Date: 2019-09-30
    Abstract
  • Based on the second-level sounding data of high vertical resolution in China from June 2014 to May 2017, time and space distribution characteristics of brunt-vaisala frequency in China are analyzed. Results show that the distribution of atmospheric brunt-vaisala frequency increases with height, data of lower stratosphere is larger than the troposphere, and the brunt-vaisala frequency remains constant in the vertical direction in the troposphere and low stratosphere. The brunt-vaisala frequency in the troposphere is greatly affected by the topography, and gradually increases from west to east with the change of longitude, with a small value area in the plateau region. The brunt-vaisala frequency in the low stratosphere is less affected by the topography and mainly changes with latitude, and it's greater in the southern region than that in the northern region. The brunt-vaisala frequency of the transition layer varies greatly with height. The southern part of lower transition layer changes faster with height than the northern part. The middle and southern parts of the upper transition layer change faster with height than the northern part. The brunt-vaisala frequency in the transition layer increases with latitude. The brunt-vaisala frequency doesn't change significantly with seasons at 5-10 km height and low stratosphere, but in the transition layer between troposphere and stratosphere (10-18 km), the seasonal change is significant. It changes most significantly in winter, less significantly in spring and autumn, and minimally in summer. Below 5 km, the seasonal variation is obvious, and it changes the most in winter. The brunt-vaisala frequency below 5 km in the northern region troposphere shows annually variation characteristics, and the peak value is in winter. The brunt-vaisala frequency doesn't change significantly with time in the stratosphere of north and south regions, and changes little with time in the troposphere in north and south regions. The brunt-vaisala frequency shows annually variation characteristics in the lower troposphere over the northern region, with peaks appearing in the winter, and there is also a one-year periodic variation in the transition layer, the peak is in winter and the valley is in summer. The brunt-vaisala frequency changes at the same height of the southern region and the northern region are similar in the transition layer. There is an annual change, the peak is in winter and the valley is in summer, but the central value of the transition layer in the southern region is smaller than the central value in the northern region. In the transition layer, the influence of the brunt-vaisala frequency with the height on the gravity-wave momentum flux is considered. The brunt-vaisala frequency and wind speed calculated by second-level sounding data are finely changed, and the change of atmospheric stability can be grasped more accurately than the conventional sounding.
    • FullText(HTML)
    References(25)

  • Fig. 1  The distribution of L-band sounding stations in China

    DownLoad: Full-Size Img PowerPoint

    Fig. 2  Comparison of two kinds of data at Beijing Station at 0000 UTC 1 Jan 2017

    (a)the comparison of two radiosonde data, (b)the comparison of second-level sounding data before and after interpolation

    DownLoad: Full-Size Img PowerPoint

    Fig. 3  Vertical profile of the average brunt-vaisala frequency in China from 2014 to 2017

    DownLoad: Full-Size Img PowerPoint

    Fig. 4  Zonal section of the brunt-vaisala frequency in China from 2014 to 2017(unit:10-4 s-2)

    DownLoad: Full-Size Img PowerPoint

    Fig. 5  Meridional section of brunt-vaisala frequency in China from 2014 to 2017(unit:10-4 s-2)

    DownLoad: Full-Size Img PowerPoint

    Fig. 6  Horizontal distribution of brunt-vaisala frequency in China from 2014 to 2017(unit:10-4 s-2)

    (a)troposphere, (b)low stratosphere

    DownLoad: Full-Size Img PowerPoint

    Fig. 7  Seasonal variation of brunt-vaisala frequency at tropospheric atmospheric(unit:10-4 s-2)

    DownLoad: Full-Size Img PowerPoint

    Fig. 8  Seasonal variation of brunt-vaisala frequency in low stratosphere(unit:10-4 s-2)

    DownLoad: Full-Size Img PowerPoint

    Fig. 9  Monthly average variation of atmospheric brunt-vaisala frequency in China from 2014 to 2017(unit:10-4 s-2)

    (a)the north region, (b)the south region

    DownLoad: Full-Size Img PowerPoint

    Fig. 10  Comparison of gravity flux fluctuations at different brunt-vaisala frequency in transition layer at Beijing Station at 0000 UTC 6 Jun 2014

    (a)momentum flux changes with brunt-vaisala frequency change, (b)brunt-vaisala frequency changes with height, (c)momentum flux changes with buoyancy frequency as constant, (d)brunt-vaisala frequency is a constant

    DownLoad: Full-Size Img PowerPoint

    Fig. 11  Comparison of gravity flux fluctuations at different brunt-vaisala frequency in troposphere layer at Beijing Station at 0000 UTC 6 Jun 2014

    (a)momentum flux changes with brunt-vaisala frequency change, (b)brunt-vaisala frequency changes with height, (c)momentum flux changes with buoyancy frequency as constant, (d)brunt-vaisala frequency is a constan

    DownLoad: Full-Size Img PowerPoint

    Fig. 12  The comparison of Ri for two types of data at Xuzhou Station

    DownLoad: Full-Size Img PowerPoint
  • [1]
    Good R E, Beland R W, Brown J H, et al.Evidence of Atmospheric Gravity Wave Perturbations of the Brunt-Vaisala Frequency in the Atmosphere//Middle Atmosphere Program Handbook for Map.Middle Atmosphere Program.Handbook for MAP, Volume 20, 1986.
    [2]
    Tsuda T, Vanzandt T E, Mizumoto M, et al.Spectral analysis of temperature and Brunt-Väisälä frequency fluctuations observed by radiosondes.J Geophys Res Atmos, 1989, 96(D9):17265-17278.
    [3]
    王丽吉, 陈泽宇, 凌超, 等.中层大气静力稳定性减弱趋势——历史火箭探空数据分析.物理学报, 2015, 64(16):451-458. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=wlxb201516055
    [4]
    赵平.非均匀大气层结下斜压大气长波的线性及非线性增长.应用气象学报, 1989(2):124-132. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=19890219&flag=1
    [5]
    马淑芬, 张若军.大气层结对青藏高原近地层湍流特征的影响.应用气象学报, 1989(3):264-272. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=19890339&flag=1
    [6]
    安洁, 张立凤.武汉地区"98.7"暴雨过程大气稳定性分析.应用气象学报, 2005, 16(3):313-321. doi:  10.3969/j.issn.1001-7313.2005.03.005
    [7]
    钱永甫.包络地形和重力波拖曳对气候模拟效果的影响.应用气象学报, 2000, 11(1):13-20. doi:  10.3969/j.issn.1001-7313.2000.01.002
    [8]
    Chen Qiying, Shen Xueshun, Sun Jian, et al.Momentum budget diagnosis and the parameterization of subgrid-scale orographic drag in global GRAPES.J Meteor Res, 2016, 30(5):771-788. doi:  10.1007/s13351-016-6033-y
    [9]
    朱红伟, 刘宇迪.三维变量配置对惯性重力波频散性模拟的影响.应用气象学报, 2003, 14(5):533-541. doi:  10.3969/j.issn.1001-7313.2003.05.003
    [10]
    袁韦华, 徐寄遥, 吴永富, 等.北京上空对流层和下平流层重力波谱统计特性.中国科学(D辑), 2009, 39(11):1505-1514. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK200901872408
    [11]
    Juckes M N.The static stability of the midlatitude troposphere:The relevance of moisture.J Atmosph Sci, 2000, 57(18):3050-3057. doi:  10.1175/1520-0469(2000)057<3050:TSSOTM>2.0.CO;2
    [12]
    刘玮, 田文寿, 舒建川, 等.热带平流层准两年振荡对热带对流层顶和深对流活动的影响.地球科学进展, 2015, 30(6):724-736. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dqkxjz201506011
    [13]
    杨婷, 闵锦忠, 张申龑.分层气流条件下地形降水的二维理想数值试验.气象科学, 2017, 37(2):222-230. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=qxkx201702009
    [14]
    吴永富, 徐寄遥, 袁韡, 等.北京上空高分辨率气球探空观测的温度垂直波数谱.空间科学学报, 2007, 27(1):47-54. doi:  10.3969/j.issn.0254-6124.2007.01.009
    [15]
    吴永富, 徐寄遥.冬季中层顶区域重力波谱特性.空间科学学报, 2004, 24(5):333-339. doi:  10.3969/j.issn.0254-6124.2004.05.003
    [16]
    常启海, 杨国韬, 宋娟, 等.通过瑞利激光雷达观测研究武汉上空中层大气(30~60 km)的稳定性.科学通报, 2005, 50(24):2786-2789. doi:  10.3321/j.issn:0023-074X.2005.24.018
    [17]
    陈权亮, 陈月娟, 邓淑梅.平流层Brunt-Vaisala频率的分布特征.中国科学技术大学学报, 2005, 35(6):909-918. doi:  10.3969/j.issn.0253-2778.2005.06.028
    [18]
    姚雯, 马颖, 徐文静.L波段电子探空仪相对湿度误差研究及其应用.应用气象学报, 2008, 19(3):356-361. doi:  10.3969/j.issn.1001-7313.2008.03.012
    [19]
    马颖, 姚雯, 黄炳勋.59型与L波段探空仪温度和位势高度记录对比.应用气象学报, 2010, 21(2):214-220. doi:  10.3969/j.issn.1001-7313.2010.02.011
    [20]
    颜晓露, 郑向东, 李蔚, 等.两种探空仪观测湿度垂直分布及其应用比较.应用气象学报, 2012, 23(4):433-440. doi:  10.3969/j.issn.1001-7313.2012.04.006
    [21]
    张立功, 王汝忠, 黄小明, 等.L波段测风雷达-电子探空仪系统简介.干旱气象, 2002, 20(4):30-32. doi:  10.3969/j.issn.1006-7639.2002.04.011
    [22]
    姚雯, 马颖, 高丽娜.L波段与59-701探空系统相对湿度对比分析.应用气象学报, 2017, 28(2):218-226. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20170209&flag=1
    [23]
    Alexander M J, Geller M, Mclandress C, et al.Recent developments in gravity-wave effects in climate models and the global distribution of gravity-wave momentum flux from observations and models.Quart J Roy Meteor Soc, 2010, 136(650):1103-1124.
    [24]
    易帆, 刘仁强.极区夏季中层顶大气波的共振非线性相互作用.中国科学(G辑), 2003, 33(2):158-167. http://d.old.wanfangdata.com.cn/Periodical/zgkx-cg200302010
    [25]
    曹艳察, 张涛.2016年6月大气环流和天气分析.气象, 2016, 42(9):1154-1160. http://d.old.wanfangdata.com.cn/Periodical/qx201609013
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中
  • -->

Catalog

    Figures(12)

    Get Citation
    PDF
    XML
    Article views (5470) PDF downloads(80) Cited by()
    • Received : 2018-12-12
    • Accepted : 2019-05-05
    • Published : 2019-09-30
    Journal Online
    Contact

    © 2020 Journal of Applied Meteorological Science   京ICP备15006967号-1

    Supported by Beijing Renhe Information Technology Co. Ltd

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return