Vol.30, NO.4, 2019
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Article Navigation >  Journal of Applied Meteorological Science  > 2019  >  30(4): 443-455
Chang Wanting, Gao Wenhua, Duan Yihong, et al. The impact of cloud microphysical processes on typhoon numerical simulation. J Appl Meteor Sci, 2019, 30(4): 443-455. DOI:  10.11898/1001-7313.20190405.
Citation: Chang Wanting, Gao Wenhua, Duan Yihong, et al. The impact of cloud microphysical processes on typhoon numerical simulation. J Appl Meteor Sci, 2019, 30(4): 443-455. DOI:  10.11898/1001-7313.20190405.
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The Impact of Cloud Microphysical Processes on Typhoon Numerical Simulation

DOI: 10.11898/1001-7313.20190405

  • State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081

  • Received Date: 2019-02-18
  • Rev Recd Date: 2019-05-27
  • Publish Date: 2019-07-31
    Abstract
  • Previous studies show that the cloud microphysical process affects the precipitation, as well as the intensity, internal structure and evolution process of tropical cyclones. Thus, the rational description of the cloud microphysical process is crucial. And the correctness of the cloud microphysical process is the basis of the high-resolution model in simulating precipitation and fine-scale structure of typhoon. The two-moment bulk microphysics scheme developed by Chinese Academy of Meteorological Sciences (CAMS) is a mixed phase two-moment cloud microphysics scheme, which can simulate cloud microphysics processes in different weather systems. However, whether it can be applied to the simulation of tropical cyclones is still uncertain.Four numerical experiments of typhoon Usagi (2013) are conducted by using the Weather Research and Forecasting (WRF) model with Chinese Academy of Meteorological Sciences two-moment microphysics scheme (CAMS). The simulated track, intensity, cloud microphysics and rainfall are compared with the observed typhoon best track dataset and satellite observations to evaluate performances of CAMS microphysics scheme and investigate the possible impacts of cloud microphysical processes on Typhoon Usagi. To overcome the overestimation of snow content in control experiment (CTRL), three sensitivity experiments are designed:Modifying coefficients of snow particle mass and falling velocity (EXP1), using the typical oceanic cloud droplet parameter (EXP2), and including changes in both EXP1 and EXP2 (EXP3). It shows that the snow content is significantly reduced in the EXP1 and EXP3 due to the increased rate of accretion of snow by graupel and the slightly reduced snow mass flux, and the content of whole ice-phase hydrometeors are also reduced. The rapid intensification process in the early stage of typhoon Usagi is well captured in EXP2 and EXP3 owing to the better simulated CAPE in eye region, and their intensity and track are also better than those in CTRL. Although the hourly precipitation rate in each experiment is generally stronger, the spatial distribution of precipitation in EXP3 is more consistent with the observation. As a result, modifying coefficients of snow mass and falling velocity as well as using the typical oceanic cloud droplet concentration in CAMS microphysics will significantly reduce the snow content and improve the simulated track, intensity and precipitation. These results could not only provide ideology for improving the cloud microphysical parameterizations in simulating typhoon, but also improve the understanding of cloud microphysics impacts on typhoon process and help improving the cloud microphysical parameterization schemes in simulating typhoons.
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  • Fig. 1  The triply nested model domains

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    Fig. 2  Observed and simulated typhoon track(a) and minimum sea level pressure(solid lines) and surface maximum wind speed(dashed lines)(b) from 0000 UTC 18 Sep to 0600 UTC 22 Sep in 2013

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    Fig. 3  Horizontal distributions of radar reflectivity at 3 km and 8 km height by TRMM/PR measurements and CTRL simulation at 0200 UTC 21 Sep 2013

    (black lines denote scanning areas of TRMM/PR)

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    Fig. 4  Contoured frequency by altitude diagrams(CFAD) of radar reflectivity from TRMM/PR measurements(a) and CTRL simulation(b) at 0200 UTC 21 Sep 2013

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    Fig. 5  Area-averaged vertical profiles of hydrometeor contents within a radius of 300 km from the typhoon center in TMI/2A12 measurements(a) and CAMS microphysical scheme simulations(b) at 0200 UTC 21 Sep 2013

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    Fig. 6  Radius-time Hovmöller diagram of CAPE in the simulated Typhoon Usagi from 1200 UTC 18 Sep to 0000 UTC 22 Sep in 2013(black lines represent 2-time the radius of maximum wind) (a)CTRL, (b)EXP1, (c)EXP2, (d)EXP3

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    Fig. 7  Time-area averaged vertical profiles of hydrometeor contents within a radius of 300 km from the typhoon center from 1200 UTC 18 Sep to 0600 UTC 22 Sep in 2013 (a)CTRL, (b)EXP1, (c)EXP2, (d)EXP3

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    Fig. 8  Area-time averaged microphysical process rates within a radius of 300 km from the typhoon center for cloud, rain and snow content from 1200 UTC 18 Sep to 0600 UTC 22 Sep in 2013

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    Fig. 9  Spatial distribution of rainfall rate at 0200 UTC 21 Sep 2013 (a)TRMM/PR measurement, (b)CTRL, (c)EXP1, (d)EXP2, (e)EXP3

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  • [1]
    Tao W K, Simpson J, Sui C H, et al.Heating, moisture, and water budgets of tropical and midlatitude squall lines:Comparisons and sensitivity to long wave radiation.J Atmos Sci, 1993, 50(5):673-690. doi:  10.1175/1520-0469(1993)050<0673:HMAWBO>2.0.CO;2
    [2]
    Ramanathan V, Crutzen P J, Kiehl J T, et al.Aerosols, climate, and the hydrological cycle.Science, 2001, 294(5549):2119-2124. doi:  10.1126/science.1064034
    [3]
    McCumber M, Tao W, Simpson J, et al.Comparison of ice-phase microphysical parameterization schemes using numerical simulations of tropical convection.J Appl Meteor, 1991, 30:985-1004. doi:  10.1175/1520-0450-30.7.985
    [4]
    Li X, Pu Z.Sensitivity of numerical simulation of early rapid intensification of hurricane Emily (2005) to cloud microphysical and planetary boundary layer parameterizations.Mon Wea Rev, 2008, 136:4819-4838. doi:  10.1175/2008MWR2366.1
    [5]
    Wang M, Zhao K, Xue M, et al.Precipitation microphysics characteristics of a typhoon Matmo (2014) rain band after landfall over eastern China based on polarimetric radar observations.J Geophys Res Atmos, 2016, 121(20):12415-12433. doi:  10.1002/2016JD025307
    [6]
    杨挺, 端义宏, 徐晶, 等.城市效应对登陆热带气旋妮妲降水影响的模拟.应用气象学报, 2018, 29(4):410-422. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20180403&flag=1
    [7]
    冯佳宁, 端义宏, 徐晶, 等.雷达资料同化对2015年台风彩虹数值模拟改进.应用气象学报, 2017, 28(4):399-413. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20170402&flag=1
    [8]
    刘还珠, 陈德辉, 滕俏彬.不同物理过程参数化对模式台风的影响及其动力结构的研究.应用气象学报, 1998, 9(2):141-150. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=19980221&flag=1
    [9]
    孙晶, 楼小凤, 胡志晋, 等.CAMS复杂云微物理方案与GRAPES模式耦合的数值试验.应用气象学报, 2008, 19(3):315-325. doi:  10.3969/j.issn.1001-7313.2008.03.007
    [10]
    屈右铭, 蔡荣辉, 朱立娟, 等.云分析系统在台风莫拉菲数值模拟中的应用.应用气象学报, 2012, 23(5):551-561. doi:  10.3969/j.issn.1001-7313.2012.05.005
    [11]
    Hong S Y, Lim J O.The WRF single-moment 6-class microphysics scheme (WSM6).J Korean Meteor Soc, 2006, 42(2):129-151. http://cn.bing.com/academic/profile?id=88b7d963485cf080fae5c40fe7cbca20&encoded=0&v=paper_preview&mkt=zh-cn
    [12]
    Hong S Y, Lim K S, Kim J H, et al.Sensitivity study of cloud-resolving convective simulations with WRF using two bulk microphysical parameterizations:Ice-phase, microphysics versus sedimentation effects.J Appl Meteorol Climatol, 2009, 48(1):61-76. doi:  10.1175/2008JAMC1960.1
    [13]
    Morrison H, Curry J A, Khvorostyanov V I.A new double-moment microphysics parameterization for application in cloud and climate models.Part Ⅰ:Description.J Atmos Sci, 2005, 62:1665-1677. doi:  10.1175/JAS3446.1
    [14]
    Brown P R A, Swann H A.Evaluation of key microphysical parameters in three-dimensional cloud-model simulations using aircraft and multiparameter radar data.Q J R Meteorol Soc, 1997, 123:2245-2275. doi:  10.1002/qj.v123:544
    [15]
    Lord S J, Willoughby H E, Piotrowicz J M.Role of a parameterized ice-phase microphysics in an axisymmetric, nonhydrostatic tropical cyclone model.J Atmos Sci, 1984, 41:2836-2848. doi:  10.1175/1520-0469(1984)041<2836:ROAPIP>2.0.CO;2
    [16]
    Yang M L, Ching L.A modeling study of Typhoon Toraji (2001):Physical parameterization sensitivity and topographic effect.Terr Atmos and Oceanic Sci, 2005, 16(1):37. http://cn.bing.com/academic/profile?id=fa73e3d4ec569d3fe223ea75b03a32b7&encoded=0&v=paper_preview&mkt=zh-cn
    [17]
    Tao W K, Shi J J, Chen S S, et al.The impact of microphysical schemes on hurricane intensity and track.Asia-Pacific J Atmos Sci, 2011, 47(1):1-16. http://cn.bing.com/academic/profile?id=8ae922a3de27fd194bafb2d3a796aa26&encoded=0&v=paper_preview&mkt=zh-cn
    [18]
    Wang Y Q.Recent research progress on tropical cyclone structure and intensity.Tropical Cyclone Research and Review, 2012, 1:254-275. http://cn.bing.com/academic/profile?id=5f58930ff86e6f4954c211a46acc9423&encoded=0&v=paper_preview&mkt=zh-cn
    [19]
    Wang Y Q.An explicit simulation of tropical cyclones with a triply nested movable mesh primitive equation model:TCM3.Part Ⅱ:Model refinements and sensitivity to cloud microphysics parameterization.Mon Wea Rev, 2002, 30:3022-3036. http://cn.bing.com/academic/profile?id=d73955c543c81b32c87589568cda91ff&encoded=0&v=paper_preview&mkt=zh-cn
    [20]
    Fovell R G, Corbosiero K L, Kuo H C.Cloud microphysics impact on hurricane track as revealed in idealized experiments.J Atmos Sci, 2009, 66(6):1764-1778. doi:  10.1175/2008JAS2874.1
    [21]
    花丛, 刘奇俊.云微物理过程影响登陆台风结构及降水的数值试验.热带气象学报, 2013, 29(6):924-934. http://www.cnki.com.cn/Article/CJFDTOTAL-RDQX201306006.htm
    [22]
    Deng L, Gao W H, Duan Y H, et al.Microphysical properties of rainwater in Typhoon Usagi (2013):A numerical modeling study.Adv Atmos Sci, 2019, 10.1007/s00376-019-8170-6. http://cn.bing.com/academic/profile?id=95751ae19db15ec4c4c216fa9cb15660&encoded=0&v=paper_preview&mkt=zh-cn
    [23]
    胡志晋, 楼小凤, 包绍武, 等.一个简化的混合相云降水显式方案.应用气象学报, 1998, 9(3):257-264. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=19980338&flag=1
    [24]
    胡志晋, 严采蘩.层状云微物理过程的数值模拟(一)——微物理模式.气象科学研究院院刊, 1986(1):37-52. http://cdmd.cnki.com.cn/Article/CDMD-10335-1013186028.htm
    [25]
    胡志晋, 何观芳.积雨云微物理过程的数值模拟(一)——微物理模式.气象学报, 1987, 45(4):467-484. http://www.cnki.com.cn/Article/CJFDTotal-QXXB198704011.htm
    [26]
    Gao W H, Zhao F S, Hu Z J, et al.A two-moment bulk microphysics scheme coupled with a mesoscale model WRF:Model description and first results.Adv Atmos Sci, 2011, 28:1184-1200. doi:  10.1007/s00376-010-0087-z
    [27]
    楼小凤, 胡志晋, 王鹏云, 等.中尺度模式云降水物理方案介绍.应用气象学报, 2003, 14(增刊Ⅰ):49-59. http://d.old.wanfangdata.com.cn/Periodical/yyqxxb2003Z1007
    [28]
    李淑日, 胡志晋, 王广河.CAMS三维对流云催化模式的改进及个例模拟.应用气象学报, 2003, 14(增刊Ⅰ):78-91. http://d.old.wanfangdata.com.cn/Periodical/yyqxxb2003Z1010
    [29]
    史月琴, 楼小凤, 邓雪娇, 等.华南冷锋云系的中尺度和微物理特征模拟分析.大气科学, 2008, 32(5):1019-1036. doi:  10.3878/j.issn.1006-9895.2008.05.03
    [30]
    Gao W H, Sui C H, Wang T C, et al.An evaluation and improvement of microphysical parameterization from a two-moment cloud microphysics scheme and the southwest monsoon experiment (SoWMEX)/terrain-influenced monsoon rainfall experiment (TiMREX) observations.J Geophys Res, 2011, 116(D19):101. http://cn.bing.com/academic/profile?id=160d2c1c55428eca90ca49943315658e&encoded=0&v=paper_preview&mkt=zh-cn
    [31]
    Gao W H, Sui C H, Fan J, et al.A study of cloud microphysics and precipitation over the Tibetan Plateau by radar observations and cloud-resolving model simulations.J Geophys Res Atmos, 2016, 121:13735-13752. doi:  10.1002/2015JD024196
    [32]
    Ying M, Zhang W, Yu H, et al.An overview of the China Meteorological Administration tropical cyclone database.J Atmos Ocean Technol, 2014, 31(2):287-301. doi:  10.1175/JTECH-D-12-00119.1
    [33]
    Awaka J.Early Results on Rain Type Classification by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar.Proc URSI Commission F Triennial Open Symposium Aveiro Portugal, 1998:143-146.
    [34]
    Skamarock W C, Klemp J B.A time-split nonhydrostatic atmospheric model for weather research and forecasting applications.J Comput Phys, 2008, 227(7):3465-3485. doi:  10.1016/j.jcp.2007.01.037
    [35]
    Locatelli J D, Hobbs P V.Fall speeds and masses of solid precipitation particles.J Geophy Res, 1974, 79(15):2185-2197. doi:  10.1029/JC079i015p02185
    [36]
    Mason B J.云物理学.中国科学院大气物理研究所, 译.北京: 科学出版社, 1979.
    [37]
    Zeng S, Riedi J, Trepte C R, et al.Study of global cloud droplet number concentration with A-Train satellites.Atmos Chem and Phys, 2014, 14:7125-7134. doi:  10.5194/acp-14-7125-2014
    [38]
    陈渭民.卫星气象学.北京:气象出版社, 2005.
    [39]
    楼小凤.MM5模式的新显示云物理方案的建立和耦合及原微物理方案的对比分析.北京: 北京大学, 2002. http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y469445
    [40]
    Holliday C R, Thompson A H.Climatological characteristics of rapidly intensifying typhoons.Mon Wea Rev, 1979, 107(8):1022-1034. doi:  10.1175/1520-0493(1979)107<1022:CCORIT>2.0.CO;2
    [41]
    Kaplan J, Demaria M.Large-scale characteristics of rapidly intensifying tropical cyclones in the North Atlantic Basin.Wea Forecasting, 2003, 18(6):1093-1108. doi:  10.1175/1520-0434(2003)018<1093:LCORIT>2.0.CO;2
    [42]
    Masunaga H, Matsui T, Tao W K, et al.Satellite data simulator unit:A multisensor, multispectral satellite simulator package.Bull Amer Meteor Soc, 2010, 91:1625-1632. doi:  10.1175/2010BAMS2809.1
    [43]
    Franklin C N, Holland G J, May P T.Sensitivity of tropical cyclone rainbands to ice-phase microphysics.Mon Wea Rev, 2005, 133:2473-2493. doi:  10.1175/MWR2989.1
    [44]
    郭静超.基于WRF模式的暖云降水潜热物理反演算法研究.合肥: 中国科学技术大学, 2016. http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y2925918
    [45]
    姚小娟, 黎伟标, 陈淑敏.利用TMI反演的水汽凝结物对热带气旋潜热结构分布的探索研究.大气科学, 2014, 38(5):909-923. http://d.old.wanfangdata.com.cn/Periodical/daqikx201405008
    [46]
    Miyamoto Y, Takemi T.A transition mechanism for the spontaneous axisymmetric intensification of tropical cyclones.J Atmos Sci, 2013, 70(1):112-129. doi:  10.1175/JAS-D-11-0285.1
    [47]
    Bryan G H, Rotunno R.The maximum intensity of tropical cyclones in axisymmetric numerical model simulations.Mon Wea Rev, 2009, 137(6):1770-1789. doi:  10.1175/2008MWR2709.1
    [48]
    Xu J, Wang Y.Sensitivity of tropical cyclone inner-core size and intensity to the radial distribution of surface entropy flux.J Atmos Sci, 2010, 67(6):1831-1852. doi:  10.1175/2010JAS3387.1
    [49]
    Xu J, Wang Y.Sensitivity of the simulated tropical cyclone inner-core size to the initial vortex size.Mon Wea Rev, 2010, 138(11):4135-4157. doi:  10.1175/2010MWR3335.1
    [50]
    王慧.台风Megi(2010)强度和结构变化的数值研究.南京: 南京信息工程大学, 2013. http://cdmd.cnki.com.cn/Article/CDMD-10300-1013340783.htm
    [51]
    Powell M D.Boundary layer structure and dynamics in outer hurricane rainbands, Part Ⅱ:Downdraft modification and mixed layer recovery.Mon Wea Rev, 1990, 118:918-938. doi:  10.1175/1520-0493(1990)118<0918:BLSADI>2.0.CO;2
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    • Received : 2019-02-18
    • Accepted : 2019-05-27
    • Published : 2019-07-31
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