留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

利用TWP-ICE试验资料对比两种边界层参数化方案

沈新勇 黄文彦 王卫国 郭春燕

沈新勇, 黄文彦, 王卫国, 等. 利用TWP-ICE试验资料对比两种边界层参数化方案. 应用气象学报, 2014, 25(4): 385-396..
引用本文: 沈新勇, 黄文彦, 王卫国, 等. 利用TWP-ICE试验资料对比两种边界层参数化方案. 应用气象学报, 2014, 25(4): 385-396.
Shen Xinyong, Huang Wenyan, Wang Weiguo, et al. Contrastive study on two boundary layer parameterization schemes using TWP-ICE experiment data. J Appl Meteor Sci, 2014, 25(4): 385-396.
Citation: Shen Xinyong, Huang Wenyan, Wang Weiguo, et al. Contrastive study on two boundary layer parameterization schemes using TWP-ICE experiment data. J Appl Meteor Sci, 2014, 25(4): 385-396.

利用TWP-ICE试验资料对比两种边界层参数化方案

资助项目: 

国家自然科学基金项目 41375058,41175065

国家重点基础研究发展计划973项目 013CB430103,2011CB403405

江苏高等学校优秀科技创新团队计划项目 PIT2012

详细信息
    通信作者:

    沈新勇, email:shenxy@nuist.edu.cn

Contrastive Study on Two Boundary Layer Parameterization Schemes Using TWP-ICE Experiment Data

  • 摘要: 利用高分辨率WRF单气柱模式,选取了两种边界层参数化方案 (YSU,MYJ),对TWP-ICE (Tropical Warm Pool International Cloud Experiment) 试验期间的个例进行数值模拟,比较了两种方案对边界层结构、云和降水模拟的影响。结果表明:季风活跃期,YSU方案模拟的湍流交换系数较小,湍流混合偏弱,边界层内热通量偏小,使地表热量和水汽不易向上输送,水汽含量在近地表明显偏多,而在边界层及其以上大气层具有显著的干偏差,因此该方案模拟的云中液态水和固态水含量偏低,云量偏少,降水率偏小;MYJ方案对于季风活跃期的边界层结构具有较好的模拟能力,其模拟的云和降水更为准确。季风抑制期,MYJ方案模拟的夜间边界层结构存在较大误差,这是因为该方案模拟的夜间湍流交换系数较大,湍流混合偏强,边界层内热通量偏大,模拟的位温和水汽混合比在边界层内随高度变化较小,而观测廓线在边界层内存在较大梯度。季风抑制期两种方案模拟的云和降水均比观测值偏多,方案之间的差异较小。
  • 图  1  FNL资料的海平面气压场 (阴影) 和850 hPa风场 (矢量)(三角符号代表达尔文站)

    Fig. 1  Sea level pressure (shaded) and 850 hPa wind (arrow) from FNL data (triangle mark indicates the location of Darwin Station)

    图  2  YSU方案和MYJ方案模拟的湍流交换系数随时间和高度分布

    Fig. 2  Time-height cross sections of simulated turbulent exchange coefficient by YSU scheme and MYJ scheme

    图  3  两种方案模拟的热通量随时间和高度分布

    (a) YSU方案模拟的感热通量, (b) MYJ方案模拟的感热通量, (c) YSU方案模拟的潜热通量, (d) MYJ方案模拟的潜热通量

    Fig. 3  Time-height cross sections of simulated heat flux by two schemes

    (a) sensible heat flux simulated by YSU scheme, (b) sensible heat flux simulated by MYJ scheme, (c) latent heat flux simulated by YSU scheme, (d) latent heat flux simulated by MYJ scheme

    图  4  季风活跃期 (2006年1月21—25日) 观测和模拟的气象要素垂直廓线

    (a)03:00平均位温, (b)03:00平均水汽混合比, (c)03:00平均风速, (d)15:00平均位温, (e)15:00平均水汽混合比, (f)15:00平均风速

    Fig. 4  Mean vertical profiles of observed and simulated meteorological elements during active monsoon (21 January 2006-25 January 2006)

    (a) potential temperature at 0300 UTC, (b) vapour mixing ratio at 0300 UTC, (c) wind speed at 0300 UTC, (d) potential temperature at 1500 UTC, (e) vapour mixing ratio at 1500 UTC, (f) wind speed at 1500 UTC

    图  5  图 4,但为季风抑制期 (2006年1月26日—2月2日)

    Fig. 5  The same as in Fig. 4, but for during suppressed monsoon (26 January 2006-2 February 2006)

    图  6  观测和模拟的液态水含量随时间和高度分布

    (a) 雷达观测, (b) 云模式模拟值, (c) YSU方案模拟值, (d) MYJ方案模拟值

    Fig. 6  Time-height cross sections of observed and simulated liquid water content

    (a) observed by radar, (b) simulated by cloud-resolving model, (c) simulated by YSU scheme, (d) simulated by MYJ scheme

    图  7  观测和模拟的相对湿度随时间和高度分布

    (a) 观测值, (b) YSU方案模拟值, (c) MYJ方案模拟值

    Fig. 7  Time-height cross sections of observed and simulated relative humidity

    (a) observed, (b) simulated by YSU scheme, (c) simulated by MYJ scheme

    图  8  观测和模拟的固态水含量随时间和高度分布

    (a) 卫星观测, (b) 云模式模拟值, (c) YSU方案模拟值, (d) MYJ方案模拟值

    Fig. 8  Time-height cross sections of observed and simulated frozen water content

    (a) observed by satellite, (b) sumulated by cloud-resolving model, (c) simulated by YSU scheme, (d) simulated by MYJ scheme

    图  9  观测和模拟的云量随时间和高度分布

    (a) 观测值, (b) 云模式模拟值, (c) YSU方案模拟值, (d) MYJ方案模拟值

    Fig. 9  Time-height cross sections of observed and simulated cloud fraction

    (a) observed, (b) simulated by cloud-resolving model, (c) simulated by YSU scheme, (d) simulated by MYJ scheme

    图  10  观测和模拟的降水率随时间变化曲线

    Fig. 10  Time series of observed and simulated rain rate

  • [1] 顾建峰, 殷鹤宝, 徐一鸣, 等.MM5在上海区域气象中心数值预报中的改进和应用.应用气象学报, 2000, 11(2):189-198. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20000228&flag=1
    [2] Xie B, Fung J C H, Chan A, et al.Evaluation of nonlocal and local planetary boundary layer schemes in the WRF model.J Geophys Res, 2012, 117:D12103. https://www.researchgate.net/publication/258662802_Evaluation_of_nonlocal_and_local_planetary_boundary_layer_schemes_in_the_WRF_model
    [3] Xie B, Hunt J C R, Carruthers D J, et al.Structure of the planetary boundary layer over Southeast England:Modeling and measurements.J Geophys Res, 2013, 118:7799-7818. https://www.researchgate.net/publication/260722166_Structure_of_the_planetary_boundary_layer_over_Southeast_England_Modeling_and_measurements
    [4] Cintineo R, Otkin J, Xue M, et al.Evaluating the performance of planetary boundary layer and cloud microphysical parameterization schemes in convection-permitting ensemble forecasts using synthetic GOES-13 satellite observations.Mon Wea Rev, 2014, 142:163-182. doi:  10.1175/MWR-D-13-00143.1
    [5] 陈炯, 王建捷.北京地区夏季边界层结构日变化的高分辨模拟对比.应用气象学报, 2006, 17(4):403-411. doi:  10.11898/1001-7313.20060403
    [6] 刘梦娟, 陈敏.BJ-RUC系统对北京夏季边界层的预报性能评估.应用气象学报, 2014, 25(2):212-221. doi:  10.11898/1001-7313.20140211
    [7] Hong S, Pan H.Nonlocal boundary layer vertical diffusion in a medium-range forecast model.Mon Wea Rev, 1996, 124:2322-2339. doi:  10.1175/1520-0493(1996)124<2322:NBLVDI>2.0.CO;2
    [8] Jankov I, Gallus W A, Segal M, et al.The impact of different WRF model physical parameterizations and their interactions on warm season MCS rainfall.Wea Forecasting, 2005, 20:1048-1060. doi:  10.1175/WAF888.1
    [9] Jankov I, Schultz P J, Anderson C J, et al.The impact of different physical parameterizations and their interactions on cold season QPF in the American River Basin.J Hydrometeor, 2007, 8:1141-1151. doi:  10.1175/JHM630.1
    [10] 王晨稀, 端义宏.短期集合预报技术在梅雨降水预报中的试验研究.应用气象学报, 2003, 14(1):69-78. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20030108&flag=1
    [11] 王康康, 张维桓, 秦凯兵.一η模式中高分辨边界层方案及对降水影响的数值试验.高原气象, 2004, 23(5):620-628. http://www.cnki.com.cn/Article/CJFDTOTAL-GYQX200405007.htm
    [12] 朱蓉, 徐大海.中尺度数值模拟中的边界层多尺度湍流参数化方案.应用气象学报, 2004, 15(5):543-555. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20040567&flag=1
    [13] 陈炯, 王建捷.边界层参数化方案对降水预报的影响.应用气象学报, 2006, 17(增刊I):11-17. http://www.cnki.com.cn/Article/CJFDTOTAL-YYQX2006S1001.htm
    [14] May P T, Mather J H, Vaughan G, et al.The tropcical warm pool international cloud experiment.Bull Amer Meteor Soc, 2008, 89:629-645. doi:  10.1175/BAMS-89-5-629
    [15] Ghan S, Randall D, Xu K, et al.A comparison of single column model simulation of summertime midlatitude continental convection.J Geophys Res, 2000, 105:2091-2124. doi:  10.1029/1999JD900971
    [16] Hack J J, Pedretti J A.Assessment of solution uncertainties in single-column modeling frameworks.J Climate, 2000, 13:352-365. doi:  10.1175/1520-0442(2000)013<0352:AOSUIS>2.0.CO;2
    [17] Xie S, Hume T, Jakob C, et al.Observed large-scale structures and diabatic heating and drying profiles during TWP-ICE.J Climate, 2010, 23:57-79. doi:  10.1175/2009JCLI3071.1
    [18] Zhang M H, Lin J L.Constrained variational analysis of sounding data based on column integrated budgets of mass, heat, moisture, and momentum:Approach and application to ARM measurements.J Atmos Sci, 1997, 54:1503-1524. doi:  10.1175/1520-0469(1997)054<1503:CVAOSD>2.0.CO;2
    [19] Hong S, Noh Y, Dudhia J.A new vertical diffusion package with an explicit treatment of entrainment processes.Mon Wea Rev, 2006, 134:2318-2341. doi:  10.1175/MWR3199.1
    [20] Janjic Z I.The Step-Mountain Eta Coordinate Model: Further developments of the convection, viscous sublayer, and turbulence closure schemes.Mon Wea Rev, 1994, 122:927-945. doi:  10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2
    [21] Xu K, Randall D.A semiempirical cloudiness parameterization for use in climate model.J Atmos Sci, 1996, 53:3084-3102. doi:  10.1175/1520-0469(1996)053<3084:ASCPFU>2.0.CO;2
    [22] Gibbs J A, Fedorovich E, Eijk A M J V.Evaluating Weather Research and Forecasting (WRF) model predictions of turbulent flow parameters in a dry convective boundary layer.J Appl Meteor Clim, 2011, 50:2429-2444. doi:  10.1175/2011JAMC2661.1
    [23] Varble A, Fridlind A M, Zipser E J, et al.Evaluation of cloud-resolving model intercomparison simulations using TWP-ICE observations: Precipitation and cloud structure.J Geophys Res, 2011, 116:D12206, doi: 10.1029/2010JD015180.
    [24] 郑晓辉, 徐国强, 魏荣庆.GRAPES新云量计算方案的引进和影响试验.气象, 2013, 39(1):57-66. doi:  10.7519/j.issn.1000-0526.2013.01.007
    [25] Clothiaux E E, Ackerman T P, Mace G G, et al.Objective determination of cloud heights and radar reflectivities using a combination of active remote sensors at the ARM CART sites.J Appl Meteor, 2000, 39:645-665. doi:  10.1175/1520-0450(2000)039<0645:ODOCHA>2.0.CO;2
    [26] Xie S, Cederwall R T, Zhang M.Developing long-term single-column model/cloud system-resolving model forcing data using numerical weather prediction products constrained by surface and top of the atmosphere observations.J Geophys Res, 2004, 109:D01104, doi: 10.1029/2003JD004045.
  • 加载中
图(10)
计量
  • 摘要浏览量:  2942
  • HTML全文浏览量:  1164
  • PDF下载量:  978
  • 被引次数: 0
出版历程
  • 收稿日期:  2014-02-07
  • 修回日期:  2014-05-16
  • 刊出日期:  2014-07-31

目录

    /

    返回文章
    返回