不同微物理方案对台风“利奇马”雨带模拟的影响分析

李冠秀; 吴宛真; 黄伟; 束炯; 邓琳

doi:10.16032/j.issn.1004-4965.2022.064

不同微物理方案对台风“利奇马”雨带模拟的影响分析

doi: 10.16032/j.issn.1004-4965.2022.064

李冠秀^{1, 2},
吴宛真^{2, 3},
黄伟^{2, 3},
束炯^1, ,,
邓琳^{2, 3}

1.
华东师范大学地理科学学院，上海 200041
2.
中国气象局上海台风研究所，上海 200030
3.
中国气象局台风数值预报重点实验室，上海 200030

基金项目:

政府间国际科技创新合作重点专项 2016YFE0109700

上海市科学技术委员会科研计划 19dz1200101

详细信息

通讯作者:
束炯，男，上海市人，教授，博士研究生导师，从事气候变化与大气环境遥感研究。E-mail：jshu@geo.ecnu.edu.cn

中图分类号: P435
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- 被引次数: 0
出版历程
- 收稿日期: 2021-03-31
- 修回日期: 2022-03-18
- 网络出版日期: 2023-01-17
- 刊出日期: 2022-10-20

INFLUENCE OF DIFFERENT MICROPHYSICAL SCHEMES ON SIMULATION OF TYPHOON LEKIMA'S RAINBAND

LI Guanxiu^{1, 2},
WU Wanzhen^{2, 3},
HUANG Wei^{2, 3},
SHU Jiong^{1
, ,},
DENG Lin^{2, 3}

1.
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
2.
Shanghai Typhoon Institute, CMA, Shanghai 200030, China
3.
Key Laboratory of Numerical Modeling for Tropical Cyclone, CMA, Shanghai 200030, China

摘要

摘要: 云微物理过程是影响台风降水数值模拟的关键过程。利用华东中尺度模式系统，选取Thompson与CLR两种微物理参数化方案对台风“利奇马”进行数值模拟，对比观测、卫星资料，评估两个微物理参数化方案对台风模拟的影响，结果表明：相比于Thompson方案，CLR方案对台风“利奇马”的模拟在登陆后的路径、强度、降水明显更接近观测；Thompson方案在距离台风中心约100 km形成较强的螺旋雨带，而CLR方案在距离台风中心150 km左右的位置形成了较弱的螺旋雨带。进一步的分析表明，CLR方案模拟出的外围雨带距离台风中心的距离更远，是由于CLR方案中冰、霰等冰相态水凝物下落速度更小，更有可能被推送到距离台风中心更远的位置，从而形成不同的雨带分布。
- 微物理 /
- 数值模拟 /
- 台风“利奇马” /
- 雨带
Abstract: Cloud microphysical process is a key process that may affect the numerical simulation of typhoon precipitation. In this paper, simulations of Typhoon Lekima are carried out by using the Shanghai Meteorological Service WRF ADAS Real-Time Modeling System with two different microphysical parameterization schemes, i.e., Thompson and CLR. Observational data and satellite data are compared to evaluate the impact of the two schemes on typhoon simulation. The results show that the simulation using the CLR scheme is significantly closer to observations compared with that using the Thompson scheme, especially after landing. The model using Thompson scheme shows strong spiral rainbands distribution about 100km away from the typhoon center, while the model with CLR scheme presents weaker rainbands at the distance of about 150km from the typhoon center. Further analysis indicates that the outer rainbands simulated using the CLR scheme are further away from the typhoon center due to lower falling speed and longer diameter of ice-phase hydrometeors in the CLR scheme; ice-phase hydrometeors are more likely to be pushed to places further away from typhoon center, leading to different rainbands.
- microphysics /
- numerical simulation /
- Typhoon Lekima /
- rainband

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图 1 模拟区域

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图 2 BABJ实况(黑色)与Thompson方案(蓝色)、CLR方案(红色)模拟的移动路径(逐小时)对比(实心点间隔24小时)

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图 3 BABJ实况(黑色)与Thompson方案(蓝色)、CLR方案(红色)模拟的最低中心气压(虚线)及10 m风速(实线)对比

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图 4 GPM卫星与地面观测融合1 h降水产品(a、d、g)与Thompson方案(b、e、h)、CLR方案(c、f、i)模拟的1 h降水结果对比

a~c、d~f、g~i分别为北京时间2019年8月8日18—19时、9日14—15时、10日05—06时的1 h降水模拟结果；e、f中红圈代表外围雨带位置。单位：mm。

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图 5 Thompson(a)、CLR(b)方案小时降水量的径向平均随时间变化

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图 6 8月8日00时—11日00时Thompson和CLR方案冰相态水凝物(冰、雪、霰)(a、b)、液态水凝物(云水、雨水)(c、d)的径向平均随时间变化

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图 7 台风主体(距台风中心190 km半径内)冰相态(a)、液态(b)

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图 8 8月9日08时水凝物质量混合比的径向平均随高度变化

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图 9 垂直速度(m/s)的径向平均随高度变化(a，b)、潜热释放(K/s)的径向平均随高度变化(c，d)

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图 10 8月9日08时雪粒子下落速度随直径变化情况

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表 1 微物理方案的水凝物预报变量

方案名称	质量浓度比	数浓度比
Thompson	q_c、q_r、q_i、q_s、q_g	n_c、n_r、n_i
CLR	q_c、q_r、q_i、q_s、q_g	n_c、n_r、n_i、n_s、n_g

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参考文献(28)

[1]	陈联寿, 罗哲贤, 李英. 登陆热带气旋研究的进展[J]. 气象学报, 2004, 62(5): 541-549.
[2]	董美莹, 陈联寿, 郑沛群. 登陆热带气旋暴雨突然增幅和特大暴雨之研究进展[J]. 热带气象学报, 2009, 25(4): 495-502.
[3]	张大林. 各种非绝热物理过程在中尺度模式中的作用[J]. 大气科学, 1998, 22(4): 548-561.
[4]	史月琴, 楼小凤. 显式云物理方案的研究进展[J]. 气象科技, 2006(5): 513-520.
[5]	ROGERS R F, BLACK M L, CHEN S S, et al. An evaluation of microphysics fields from mesoscale model simulations of tropical cyclones. Part Ⅰ: Comparisons with observations[J]. J Atmos Sci, 2007, 64(6): 1811-1834.
[6]	FRANKLIN C N, HOLLAND G J, MAY P T. Sensitivity of tropical cyclone rainbands to ice-phase microphysics[J]. Mon Wea Rev, 2005, 133(8): 2473-2493.
[7]	TAO W K, SHI J J, CHEN S S, et al. The impact of microphysical schemes on hurricane intensity and track[J]. Asia-Pacific J Atmos Sci, 2011, 47(1): 1-16.
[8]	WANG Y. An explicit simulation of tropical cyclones with a triply nested movable mesh primitive equation model: TCM3. Part Ⅰ: Model description and control experiment[J]. Mon Wea Rev, 2001, 129 (6): 1370-1394.
[9]	WILLOUGHBY H E, JIN H L, LORD S J, et al. Hurricane structure and evolution as simulated by an axisymmetric, nonhydrostatic numerical model[J]. J Atmos Sci, 1984, 41(7): 1169-1186.
[10]	YANG M J, CHING L. A modeling study of Typhoon Toraji (2001): physical parameterization sensitivity and topographic effect[J]. Terrestrial, Atmospheric and Oceanic Sciences, 2005, 16 (1): 177-213.
[11]	WANG Y. How do outer spiral rainbands affect tropical cyclone structure and intensity[J]. J Atmos Sci, 2009, 66(5): 1250-1273.
[12]	WANG Y. Recent research progress on tropical cyclone structure and intensity[J]. Tropical Cyclone Research and Review, 2012, 1(2): 254-275.
[13]	CHAN K T F, CHAN J C L. Sensitivity of the simulation of tropical cyclone size to microphysics schemes[J]. Adv Atmos Sci, 2016, 33(9): 1024-1035.
[14]	LI Z, ZHANG Y T, LIU Q J, et al. A study of the influence of microphysical processes on Typhoon Nida (2016) using a new double-moment microphysics scheme in the Weather Research and Forecasting model[J]. J Trop Meteor, 2018, 24(2): 123-130.
[15]	周炳君, 李昕, 陈耀登, 等. GPS ZTD资料同化对台风"利奇马"模拟的研究影响[J]. 气象科学, 2020, 40(1): 11-21.
[16]	SKAMAROCK W C, KLEMP J B, DUDHIA J, et al. A description of the advanced research WRF version 3[M]. 2008.
[17]	IACONO M J, DELAMERE J S, MLAWER E J, et al. Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models[J]. J Geophys Res Atmos, 2008, 113: D13103.
[18]	DUDHIA J. Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model[J]. J Atmos Sci, 1989, 46(20): 3077-3107.
[19]	HONG S Y, NOH Y, DUDHIA J. A new vertical diffusion package with an explicit treatment of entrainment processes[J]. Mon Wea Rev, 2006, 134(9): 2318-2341.
[20]	NIU G Y, YANG Z L, MITCHELL K E, et al. The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements[J]. J Geophys Res Atmos, 2011, 116(D12).
[21]	MEBUST M R, EDER B K, BINKOWSKI F S, et al. Models-3 Community Multiscale Air Quality (CMAQ) model aerosol component 2. Model evaluation[J]. J Geophys Res Atmos, 2003, 108(D6).
[22]	REISNER J, RASMUSSEN R M, BRUINTJES R T. Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model[J]. Quart J R Meteor Soc, 1998, 124(548): 1071-1107.
[23]	CHEN J P, LIU S. Physically based two‐moment bulkwater parametrization for warm‐cloud microphysics[J]. Quart J R Meteor Soc, 2004, 130(596): 51-78.
[24]	THOMPSON G, RASMUSSEN R M, MANNING K. Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part Ⅰ: Description and sensitivity analysis[J]. Mon Wea Rev, 2004, 132 (2): 519-542.
[25]	THOMPSON G, FIELD P R, RASMUSSEN R M, et al. Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. part ii: implementation of a new snow parameterization[J]. Mon Wea Rev, 2008, 136(12): 5095-5115.
[26]	李麒崙, 张万昌. GPM与TRMM降水数据在中国大陆的精度评估与对比[J]. 水科学进展, 2017, 29(3): 303-313.
[27]	杨文霞, 冉令坤, 洪延超. 台风Wipha云微物理特征数值模拟[J]. 科技导报, 2010, 28(23): 34-39.
[28]	邓琳. 台风的云微物理特征及其演变机制研究[D]. 北京: 中国气象科学研究院, 2020.