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热带气旋“苏迪罗”(2015)海上活动时段降水物理过程模拟诊断研究

王晓慧 崔晓鹏 郝世峰

王晓慧, 崔晓鹏, 郝世峰. 热带气旋“苏迪罗”(2015)海上活动时段降水物理过程模拟诊断研究[J]. 大气科学, 2019, 43(2): 417-436. doi: 10.3878/j.issn.1006-9895.1804.18118
引用本文: 王晓慧, 崔晓鹏, 郝世峰. 热带气旋“苏迪罗”(2015)海上活动时段降水物理过程模拟诊断研究[J]. 大气科学, 2019, 43(2): 417-436. doi: 10.3878/j.issn.1006-9895.1804.18118
Xiaohui WANG, Xiaopeng CUI, Shifeng HAO. Diagnostic and Numerical Study on Surface Rainfall Processes Associated with Tropical Cyclone Soudelor (2015) over the Ocean[J]. Chinese Journal of Atmospheric Sciences, 2019, 43(2): 417-436. doi: 10.3878/j.issn.1006-9895.1804.18118
Citation: Xiaohui WANG, Xiaopeng CUI, Shifeng HAO. Diagnostic and Numerical Study on Surface Rainfall Processes Associated with Tropical Cyclone Soudelor (2015) over the Ocean[J]. Chinese Journal of Atmospheric Sciences, 2019, 43(2): 417-436. doi: 10.3878/j.issn.1006-9895.1804.18118

热带气旋“苏迪罗”(2015)海上活动时段降水物理过程模拟诊断研究

doi: 10.3878/j.issn.1006-9895.1804.18118
基金项目: 

国家重点基础研究发展计划(973项目) 2015CB452804

国家自然科学基金项目 41175056

详细信息
    作者简介:

    王晓慧, 女, 1992年出生, 硕士研究生, 主要从事热带气旋暴雨过程研究。E-mail:xhwang@mail.iap.ac.cn

    通讯作者:

    崔晓鹏, E-mail:xpcui@mail.iap.ac.cn

  • 中图分类号: P444

Diagnostic and Numerical Study on Surface Rainfall Processes Associated with Tropical Cyclone Soudelor (2015) over the Ocean

Funds: 

National Basic Research Program of China 2015CB452804

National Natural Science Foundation of China 41175056

  • 摘要: 利用WRF模式对2015年热带气旋(TC)"苏迪罗"发展演变过程开展高分辨率数值模拟,模式较好地再现了"苏迪罗"路径、强度、高低空环流、云系演变和降水分布等。应用三维地面降水诊断方程对"苏迪罗"海上活动时段的降水物理过程模拟诊断指出,QWVA(三维水汽通量辐合辐散率)对TC环流区域内降水相关的水汽相关过程变率(QWV)变化起主导作用,但环流区域内QWVL(垂直积分负的水汽局地变化率)和QWVE(海面蒸发率)亦有重要贡献(尤其是后者),尽管QWVE贡献明显小于QWVA,但由环流区域外辐合来的水汽也可能主要源于区域外不同海域的海面蒸发,海面蒸发的总体贡献应更大。海上活动时段云相关过程变率(QCM)特征及变化与QWV相比更为复杂,环流区域内的QCLL(负的液相水凝物局地变率)基本维持正值(液相水凝物持续减少),其消耗主要用于向冰相水凝物转化和地面降水,以及向区域外的三维通量辐散,6日04时之前,环流区域内QCIL(负的冰相水凝物局地变率)的变化主要归因于微物理转化及地面降水,而6日04时之后,来自环流区域外的通量辐合也有一定作用;降水强度逐渐增强时期,水凝物含量的短暂增长(负值QCLLQCIL)主要归因于明显增强和垂直扩展的上升运动,伴随上升运动增强,水凝物含量明显增加,霰融化(Pgmlt)和雨滴碰并云滴(Pracw)是造成雨滴含量增加的主要微物理过程。"苏迪罗"环流内区域和时间平均的降水效率高达96%,其中QWVA是主要贡献项,而QWVEQWVL亦有重要贡献,这与TC所处海洋下垫面有关,海上活动时段,充足的降水源和较小的降水汇共同造成此时段的高降水效率,雨滴生成主要微物理来源中,Pgmlt约占Pracw的72%,体现出海上活动时段TC环流内旺盛的深对流活动特征。
  • 图  1  (a)模拟区域和(b)内层区域设置

    Figure  1.  (a) Model domain configuration and (b) two inner domains

    图  2  (a)8月4日18时至9日00时热带气旋“苏迪罗”逐6小时观测(红色)与模拟(蓝色)路径,(b)观测(红色)和模拟(蓝色)的近地面最大风速(虚线,单位:m s−1)及最低海平面气压(实线,单位:hPa)演变,(c)观测与模拟的路径差(单位:km)

    Figure  2.  (a) Tracks of observed (red) and simulated (blue) tropical cyclone Soudelor at 6-h interval from 1800 UTC 4 August to 0000 UTC August, (b) Time series of maximum wind speed (dashed, units: m s−1) and minimum sea surface pressure (solid, units: hPa) of observed (red) and simulated (blue) storms. (c)Distance deviation of observed and simulated storms (units: km)

    图  3  (a、c、e、g)FNL全球分析资料(分辨率0.25°×0.25°)与(b、d、f、h)模拟(分辨率27 km)500 hPa位势高度场(等值线,单位:gpm)、850 hPa风场(蓝色风矢量,大于12 m s−1)和200 hPa风场(红色风羽,大于30 m s−1)。2015年8月(a、b)5日06时、(c、d)6日12时、(e、f)7日18时、(g、h)9日00时

    Figure  3.  500 hPa geopotential height fields (contour, units: gpm), 850 hPa wind fields (blue vector, > 12 m s−1) and 200 hPa wind fields (red wind barb, > 30 m s−1) from (a, c, e, g) NCEP Final Operational Global Analysis and Forecast data on 0.25°×0.25° grid and (b, d, f, h) numerical simulation with 27 km horizontal resolution. (a, b) 0600 UTC 5 August, (c, d) 1200 UTC 6 August, (e, f) 1800 UTC 7 August, (g, h) 0000 UTC 9 August 2015

    图  4  (a、c、e、g)GMS(Geostationary meteorological satellite)卫星云图(分辨率0.05°×0.05°)和(b、d、f、h)模拟得到的OLR(Outgoing long-wave radiation,向外长波辐射,阴影,单位W s−2,分辨率27 km)分布。2015年8月(a、b)5日06时、(c、d)5日18时、(e、f)6日06时、(g、h)6日18时

    Figure  4.  (a, c, e, g) GMS satellite images (resolution: 0.05°×0.05°) and (b, d, f, h) simulated OLR (shaded, units: W s−2, resolution: 27 km). (a, b) 0600 UTC 5 August, (c, d) 1800 UTC 5 August, (e, f) 0600 UTC 6 August, (g, h) 1800 UTC 6 August 2015

    图  5  2015年8月5日06时至7日00时(a)CMORPH(CPC MORPHing technique)卫星观测(分辨率0.25°)的和(b,c,d)模拟(分辨率分别为27 km、3 km、1.5 km)的42小时累积降水量分布(单位:mm)。图中黑色圆点和粗折线分别表示观测和模拟的热带气旋中心位置与路径

    Figure  5.  42-h accumulated precipitation (units: mm) with horizontal resolution of 0.25° retrieved from (a) satellite through CPC MORPHing technique (CMORPH) and from simulations at resolutions of (b) 27 km, (c) 3 km, (d) 1.5 km from 0600 UTC 5 August to 0000 UTC 7 August 2015. The black dots and the thick black lines indicate the observed and simulated tracks of tropical cyclone

    图  6  (a1、b1、c1、d1)40 m、(a2、b2、c2、d2)3 km、(a3、b3、c3、d3)7 km高度模拟的雷达反射率分布(分辨率1.5 km,单位:dBZ)。2015年8月5日(a1–a3)14时、(b1–b3)22时、6日(c1–c3)06时和(d1–d3)14时

    Figure  6.  Simulated radar reflectivity (units: dBZ) at (a1, b1, c1, d1) 40 m, (a2, b2, c2, d2) 3 km, (a3, b3, c3, d3) 7 km height on 1.5 km grid. (a1–a3) 1400 UTC 5 August, (b1–b3) 2200 UTC 5 August, (c1–c3) 0600 UTC 6 August, (d1–d3) 1400 UTC 6 August 2015

    图  7  模拟(D03,分辨率1.5 km)区域平均(半径420 km圆形区域)垂直速度(彩色阴影和等值线,单位:cm s−1)的高度—时间演变

    Figure  7.  Height–time evolution of area averaged (in the 420 km radius domain) vertical velocity (color shading and contour, units: cm s−1) on 1.5 km grid (D03)

    图  8  2015年8月5日14时至6日20时区域平均(半径420 km圆形区域)的(a)地面降水强度(PS,黑色实线)、水汽相关过程变率(QWV,红色实线)和云相关过程变率(QCM,蓝色实线)(单位:mm h−1),(b)QWV/PS(红色实线)和QCM/PS(蓝色实线)的时间演变

    Figure  8.  Temporal evolutions of area averaged (in the 420 km radius domain) (a) surface rain rate (PS, black line), the change rates for moisture-related processes (QWV, red line) and cloud-related processes (QCM, blue line) (units: mm h−1), (b) the ratios of QWV (red line) and QCM (blue line) to PS from 1400 UTC 5 August to 2000 UTC 6 August 2015

    图  9  2015年8月5日14时至6日20时区域平均(半径420 km圆形区域)的(a)PS(黑色实线)、水汽相关过程(QWV:红色实线,QWVL:蓝色实线,QWVA:绿色实线,QWVD:橘黄色实线,QWVE:紫色实线;单位:mm h−1),(b)QWVL/QWVQWVA/QWVQWVD/QWVQWVE/QWV的时间演变

    Figure  9.  Temporal evolutions of area averaged (in the 420 km radius domain) (a) PS (black line), moisture-related processes (QWV: red line, QWVL: blue line, QWVA: green line, QWVD: orange line, QWVE: purple line; units: mm h−1), (b) the ratios of QWVL (blue line), QWVA (green line), QWVD (orange line), QWVE (purple line) to QWV from 1400 UTC 5 August to 2000 UTC 6 August 2015

    图  10  2015年8月5日14时至6日20时区域平均(半径420 km圆形区域)的(a)PS(黑色实线)、QCM(紫色实线)、液相云水凝物相关过程(QCL:红色实线,QCLL:蓝色实线,QCLA:绿色实线,QCLD:橘黄色实线;单位:mm h−1),(b)PS(黑色实线)、QCM(紫色实线)、冰相云水凝物相关过程(QCI:红色实线,QCIL:蓝色实线,QCIA:绿色实线,QCID:橘黄色实线;单位:mm h−1)的时间演变

    Figure  10.  Temporal evolutions of area averaged (in the 420 km radius domain) (a) surface rain rate (PS: black line), change rates for hydrometeor-related processes (QCM, purple line) and liquid-phase hydrometeor-related processes (QCL: red line, QCLL: blue line, QCLA: green line, QCLD: orange line; units: mm h−1), (b) surface rain rate (PS, black line), change rates for hydrometeor-related processes: (QCM, purple line) and ice-phase hydrometeor-related processes (QCI: red line, QCIL: blue line, QCIA: green line, QCID: orange line; units: mm h−1) from 1400 UTC 5 August to 2000 UTC 6 August 2015

    图  11  2015年8月5日14时至6日19时区域平均(半径420 km圆形区域)的云水凝物混合比(Qg:霰粒子,Qs:雪粒子,Qi:云冰,Qr:雨滴和Qc:云滴,单位:10−3 kg kg−1)垂直廓线逐时分布

    Figure  11.  Area-averaged (in the 420 km radius domain) vertical profiles of hydrometeor mixing ratios (Qg for graupel, Qs for snow, Qi for cloud ice, Qr for raindrops, Qc for cloud water, units: 10−3 kg kg−1) from 1400 UTC 5 August to 1900 UTC 6 August 2015

    图  12  图 11,但为雨滴相关主要微物理转化项。Pgmlt:霰粒子融化成雨滴,Pracw:雨滴与云滴碰并造成雨滴含量增长,Psmlt:雪融化造成雨滴含量增长,Ern:雨滴蒸发,单位:10−6 kg kg−1s−1

    Figure  12.  Same as Fig. 11, but for vertical profiles of cloud microphysical conversion rates (Pgmlt for melting of graupel, Pracw for accretion of cloud water by rainwater, Psmlt for melting of snow, Ern for evaporation of rainwater, units: 10−6 kg kg−1 s−1) associated with raindrop budget from 1400 UTC 5 August to 1900 UTC 6 August 2015

    表  1  模拟方案设置

    Table  1.   Model configuration

    模拟方案设置
    D01区域 D02区域 D03区域
    格点数(x, y 343×325 595×595 925×741
    网格距/km 27 3 1.5
    覆盖范围/km×km 9261×8775 1785×1785 1387.5×1111.5
    时间步长/s 90 15 10
    积分时间/h 0~108 6~60 12~54
    下载: 导出CSV

    表  2  三维地面降水诊断方程各项物理含义

    Table  2.   Physical descriptions of the terms in the three- dimensional WRF-based precipitation equation

    方程项 物理含义
    PS 降水强度
    QWVL 垂直积分的水汽局地变化率的负值
    QWVA 垂直积分的三维水汽通量辐合/辐散率
    QWVE 地(海)面蒸发率
    QWVD 垂直积分的三维水汽耗散率
    QCLL 垂直积分的液相水凝物(云滴和雨滴)局地变化率的负值
    QCLA 垂直积分的三维液相水凝物(云滴和雨滴)通量辐合/辐散率
    QCLD 垂直积分的三维液相水凝物(云滴和雨滴)耗散率
    QCIL 垂直积分的冰相水凝物(云冰、雪、霰等)局地变化率的负值
    QCIA 垂直积分的三维冰相水凝物(云冰、雪、霰等)通量辐合/辐散率
    QCID 垂直积分的三维冰相水凝物(云冰、雪、霰等)耗散率
    下载: 导出CSV

    表  3  雨滴相关云微物理转化率物理含义

    Table  3.   Physical descriptions of the raindrop-related microphysical conversion rates

    雨滴相关的云微物理转化率 物理含义
    Pracw 雨滴碰并云滴造成雨滴增长
    Pgmlt 霰融化造成雨滴增长
    Qsacw 雪碰并云滴转化成雨滴
    Praut 云滴自动转化成雨滴
    Qgacw 霰碰并云滴转化成雨滴
    Psmlt 雪融化造成雨滴增长
    Piacr 云冰粘附雨滴造成雪或霰增长
    Dgacr 霰碰并雨滴干增长
    Psacr 雪碰并雨滴生成雪或霰
    Pgfr 雨滴冻结成霰
    Wgacr 霰碰并雨滴湿增长
    Ern 雨滴蒸发
    下载: 导出CSV

    表  4  2015年8月5日14时至6日20时距“苏迪罗”中心420 km半径区域和时间平均的物理量(PSLSPEQWVLQWVAQWVEQWVDQCLLQCLAQCLDQCILQCIAQCID以及雨滴相关的云微物理转化率)。其中,物理量列表中括号中数值为实际物理量值,括号外数值为将该时段PS设为100后,物理量的相对数值;与雨滴相关的云微物理转化率物理含义参见表 3

    Table  4.   Comparisons of regionally and temporally averaged (from 1400 UTC 5 August to 2000 UTC 6 August 2015 within a 420km radius of the center of Soudelor) physical quantities (Ps, LSPE, QWVL, QWVA, QWVE, QWVD, QCLL, QCLA, QCLD, QCIL, QCIA, QCID and raindrop-related microphysical conversion rates). Values in brackets represent absolute magnitudes of the above physical quantities and values outside represent relative magnitudes of these physical quantities when Ps is set to 100. Physical descriptions of the raindrop-related microphysical conversion rates can be referred to in Table 3

    平均时段 物理量
    2015年8月5日14时至8月6日20时 PS*=100 (2.96 mm h−1) QCLL=2.68 (0.08 mm h−1) Pracw*=71.51 (2.12 mm h−1) Piacr=−1.59 (-0.05 mm h −1
    LSPE = 96% QCLA= −1.90(0.06 mm h−1) Pgmlt* = 51.35 (1.52 mm h−1) Dgacr = −1.37 (−0.04 mm h−1)
    QWVL* = 8.35 (0.25 mm h−1) QCLD = −0.24 (−0.01 mm h−1) Qsacw = 0.15 (0.00 mm h−1) Psacr = −6.67 (−0.20 mm h−1)
    QWVA* = 77.22 (2.28 mm h−1) QCIL = −1.08 (−0.03 mm h−1) Praut = 0.23 (0.01 mm h−1) Pgfr = −1.62 (−0.05 mm h−1)
    QWVD* = −0.65 (−0.02 mm h−1) QCIA = 1.06 (0.03 mm h−1) Qgacw = 1.73 (0.05 mm h−1) Wgacr = 3.40 (0.10 mm h−1)
    QWVE* = 14.59 (0.43 mm h−1) QCID =−0.04 (−0.00 mm h−1) Psmlt = 6.59 (0.19 mm h−1) Ern* = −24.58 (−0.73 mm h−1)
    *表示对地面降水贡献较大的项。
    下载: 导出CSV
  • [1] Atallah E, Bosart L F, Aiyyer A R. 2007. Precipitation distribution associated with landfalling tropical cyclones over the Eastern United States[J]. Mon. Wea. Rev., 135 (6):2185-2206, doi: 10.1175/MWR3382.1.
    [2] Braham R R Jr. 1952. The water and energy budgets of the thunderstorm and their relation to thunderstorm development[J]. J. Meteor., 9 (4):227-242, doi:10.1175/1520-0469(1952)009<0227:TWAEBO>2.0.CO;2.
    [3] Brown P R A, Swann H A. 1997. Evaluation of key microphysical parameters in three-dimensional cloud-model simulations using aircraft and multiparameter radar data[J]. Quart. J. Roy. Meteor. Soc., 123 (544):2245-2275, doi: 10.1002/qj.49712354406.
    [4] Chan K T F, Chan J C J. 2016. Sensitivity of the simulation of tropical cyclone size to microphysics schemes[J]. Advances in Atmospheric Sciences, 33 (9):1024-1035, doi: 10.1007/s00376-016-5183-2.
    [5] 陈联寿, 罗哲贤, 李英. 2004.登陆热带气旋研究的进展[J].气象学报, 62 (5):541-549. doi: 10.3321/j.issn:0577-6619.2004.05.003

    Chen Lianshou, Luo Zhexian, Li Ying. 2004. Research advances on tropical cyclone landfall process[J]. Acta Meteorologica Sinica (in Chinese), 62 (5):541-549, doi: 10.3321/j.issn:0577-6619.2004.05.003.
    [6] Chen L S, Li Y, Cheng Z Q. 2010. An overview of research and forecasting on rainfall associated with landfalling tropical cyclones[J]. Advances in Atmospheric Science, 27 (5):967-976, doi: 10.1007/s00376-010-8171-y.
    [7] Chen S M, Qian Y K, Peng S Q. 2015. Effects of various combinations of boundary layer schemes and microphysics schemes on the track forecasts of tropical cyclones over the South China Sea[J]. Natural Hazards, 78 (1):61-74, doi: 10.1007/s11069-015-1697-7.
    [8] Chen S S, Knaff J A, Marks F D Jr. 2006. Effects of vertical wind shear and storm motion on tropical cyclone rainfall asymmetries deduced from TRMM[J]. Mon. Wea. Rev., 134 (11):3190-3208, doi: 10.1175/MWR3245.1.
    [9] 陈忠明, 黄福均, 何光碧. 2002.热带气旋与西南低涡相互作用的个例研究Ⅰ.诊断分析[J].大气科学, 26 (3):352-360. doi: 10.3878/j.issn.1006-9895.2002.03.06

    Chen Zhongming, Huang Fujun, He Guangbi. 2002. A case study of interactions between the tropical cyclone and the southwest vortex. Part Ⅰ:Diagnostic analysis[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 26 (3):352-360, doi: 10.3878/j.issn.1006-9895.2002.03.06.
    [10] Cheng R, Yu R C, Fu Y F, et al. 2011. Impact of cloud microphysical processes on the simulation of typhoon Rananim near shore. Part Ⅰ:Cloud structure and precipitation features[J]. Acta Meteorologica Sinica, 25 (4):441-455, doi: 10.1007/s13351-011-0405-0.
    [11] 崔晓鹏. 2009.地面降水诊断方程对降水过程的定量诊断[J].大气科学, 33 (2):375-387. doi: 10.3878/j.issn.1006-9895.2009.02.15

    Cui Xiaopeng. 2009. Quantitative diagnostic analysis of surface rainfall processes by surface rainfall equation[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 33 (2):375-387, doi: 10.3878/j.issn.1006-9895.2009.02.15.
    [12] Cui X P, Li X F. 2006. Role of surface evaporation in surface rainfall processes[J]. J. Geophys. Res., 111 (D17):D17112, doi: 10.1029/2005JD006876.
    [13] Cui X P, Li X F. 2009. Diurnal responses of tropical convective and stratiform rainfall to diurnally varying sea surface temperature[J]. Meteor. Atmos. Phys., 104 (1-2):53-61, doi: 10.1007/s00703-008-0016-1.
    [14] Cui X P, Xu F W. 2009. A cloud-resolving modeling study of surface rainfall processes associated with landfalling typhoon Kaemi (2006)[J]. Journal of Tropical Meteorology, 15 (2):181-191. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=rdqxxb-e200902007
    [15] Cui X P, Wang Y P, Yu H. 2015. Microphysical differences with rainfall intensity in severe tropical storm Bilis[J]. Atmospheric Science Letters, 16 (1):27-31, doi: 10.1002/asl2.515.
    [16] Doswell Ⅲ C A, Brooks H E, Maddox R A. 1996. Flash flood forecasting:An ingredients-based methodology[J]. Wea. Forecasting, 11 (4):560-581, doi:10.1175/1520-0434(1996)011<0560:FFFAIB>2.0.CO;2.
    [17] Franklin C N, Holland G J, May P T. 2005. Sensitivity of tropical cyclone rainbands to ice-phase microphysics[J]. Mon. Wea. Rev., 133 (8):2473-2493, doi: 10.1175/MWR2989.1.
    [18] Fritsch J M, Chappell C F. 1980. Numerical prediction of convectively driven mesoscale pressure systems. Part Ⅰ:Convective parameterization[J]. J. Atmos. Sci., 37 (8):1722-1733, doi:10.1175/1520-0469(1980)037<1722:NPOCDM>2.0.CO;2.
    [19] Gao S T, Cui X P, Zhou Y S, et al. 2005. Surface rainfall processes as simulated in a cloud-resolving model[J]. J. Geophys. Res., 110 (D10):D10202, doi: 10.1029/2004JD005467.
    [20] Gao S T, Li X F. 2010. Precipitation equations and their applications to the analysis of diurnal variation of tropical oceanic rainfall[J]. J. Geophys. Res., 115 (D8):D08204, doi: 10.1029/2009JD012452.
    [21] Grell G A. 1993. Prognostic evaluation of assumptions used by cumulus parameterizations[J]. Mon. Wea. Rev., 121 (3):764-787, doi:10.1175/1520-0493(1993)121<0764:PEOAUB>2.0.CO;2.
    [22] Heymsfield G M, Schotz S. 1985. Structure and evolution of a severe squall line over Oklahoma[J]. Mon. Wea. Rev., 113 (9):1563-1589, doi:10.1175/1520-0493(1985)113<1563:SAEOAS>2.0.CO;2.
    [23] Huang Y J, Cui X P, Li X F. 2016. A three-dimensional WRF-based precipitation equation and its application in the analysis of roles of surface evaporation in a torrential rainfall event[J]. Atmospheric Research, 169:54-64, doi: 10.1016/j.atmosres.2015.09.026.
    [24] Jiang H Y, Halverson J B, Zipser E J. 2008. Influence of environmental moisture on TRMM-derived tropical cyclone precipitation over land and ocean[J]. Geophys. Res. Lett., 35 (17):L17806, doi: 10.1029/2008GL034658.
    [25] Jiang H Y, Zipser E J. 2009. Contribution of tropical cyclones to the global precipitation from eight seasons of TRMM data:Regional, seasonal, and interannual variations[J]. J. Climate, 23 (6):264-279, doi: 10.1175/2009JCLI3303.1.
    [26] Kain J S, Fritsch J M. 1993. Convective parameterization for mesoscale models: The Kain-Fritsch scheme[C]//Emanuel K A, Raymond D J. The Representation of Cumulus Convection in Numerical Models. Boston, MA: American Meteorological Society, 46: 165-177, doi: 10.1007/978-1-935704-13-3_16.
    [27] Kuo H L. 1965. On formation and intensification of tropical cyclones through latent heat release by cumulus convection[J]. J. Atmos. Sci., 22 (1):40-63, doi:10.1175/1520-0469(1965)022<0040:OFAIOT>2.0.CO;2.
    [28] Kuo H L. 1974. Further studies of the parameterization of the influence of cumulus convection on large-scale flow[J]. J. Atmos. Sci., 31 (5):1232-1240, doi:10.1175/1520-0469(1974)031<1232:FSOTPO>2.0.CO;2.
    [29] Kurihara Y. 1975. Budget analysis of a tropical cyclone simulated in an axisymmetric numerical model[J]. J. Atmos. Sci., 32 (1):25-59, doi:10.1175/1520-0469(1975)032<0025:BAOATC>2.0.CO;2.
    [30] Lau K M, Wu H T. 2003. Warm rain processes over tropical oceans and climate implications[J]. Geophys. Res. Lett., 30 (24):2290, doi: 10.1029/2003GL018567.
    [31] Lau K M, Zhou Y P, Wu H T. 2008. Have tropical cyclones been feeding more extreme rainfall?[J]. J. Geophys. Res., 113 (D23):D23113, doi: 10.1029/2008JD009963.
    [32] 雷小途, 陈联寿. 2001.热带气旋与中纬度环流系统相互作用的研究进展[J].热带气象学报, 17 (4):452-461. doi: 10.3969/j.issn.1004-4965.2001.04.015

    Lei Xiaotu, Chen Lianshou. 2001. An overview on the interaction between tropical cyclone and mid-latitude weather systems[J]. Journal of Tropical Meteorology (in Chinese), 17 (4):452-461, doi: 10.3969/j.issn.1004-4965.2001.04.015.
    [33] 李江南, 王安宇, 杨兆礼, 等. 2003.台风暴雨的研究进展[J].热带气象学报, 19 (S1):152-159. doi: 10.3969/j.issn.1004-4965.2003.z1.017

    Li Jiangnan, Wang Anyu, Yang Zhaoli, et al. 2003. Advancement in the study of typhoon rainstorm[J]. Journal of Tropical Meteorology (in Chinese), 19 (S1):152-159, doi:10.3969/j.issn. 1004-4965.2003.z1.017.
    [34] 李江南, 蒙伟光, 闫敬华, 等. 2005.热带风暴Fitow(0114)暴雨的中尺度特征及成因分析[J].热带气象学报, 21 (1):24-32. doi: 10.3969/j.issn.1004-4965.2005.01.003

    Li Jiangnan, Meng Weiguang, Yan Jinghua, et al. 2005. Mesoscale characteristics and causes of tropical storm Fitow (0114) heavy rain[J]. Journal of Tropical Meteorology (in Chinese), 21 (1):24-32, doi: 10.3969/j.issn.1004-4965.2005.01.003.
    [35] 李英, 陈联寿, 张胜军. 2004.登陆我国热带气旋的统计特征[J].热带气象学报, 20 (1):14-23. doi: 10.3969/j.issn.1004-4965.2004.01.002

    Li Ying, Chen Lianshou, Zhang Shengjun. 2004. Statistical characteristics of tropical cyclone making landfalls on China[J]. Journal of Tropical Meteorology (in Chinese), 20 (1):14-23, doi: 10.3969/j.issn.1004-4965.2004.01.002.
    [36] 梁必骐, 梁经萍, 温之平. 1995.中国台风灾害及其影响的研究[J].自然灾害学报, 4 (1):84-91. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199500670127

    Liang Biqi, Liang Jingping, Wen Zhiping. 1995. Study of typhoon disasters and its affects in China[J]. Journal of Natural Disasters (in Chinese), 4 (1):84-91. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199500670127
    [37] 刘圣楠, 崔晓鹏. 2018. "碧利斯"(2006)暴雨过程降水强度和降水效率分析[J].大气科学, 42 (1):192-208. doi: 10.3878/j.issn.1006-9895.1704.17148

    Liu Shengnan, Cui Xiaopeng. 2018. Diagnostic analysis of rate and efficiency of torrential rainfall associated with Bilis (2006)[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 42 (1):192-208, doi: 10.3878/j.issn.1006-9895.1704.17148.
    [38] Lonfat M, Marks F D, Chen S S. 2004. Precipitation distribution in tropical cyclones using the tropical rainfall measuring mission (TRMM) microwave imager:A global perspective[J]. Mon. Wea. Rev., 132 (7):1645-1660, doi:10.1175/1520-0493(2004)132<1645:PDITCU>2.0.CO;2.
    [39] McCumber M, Tao W K, Simpson J, et al. 1991. Comparison of ice-phase microphysical parameterization schemes using numerical simulations of tropical convection[J]. J. Appl. Meteor., 30 (7):124-128, doi: 10.1175/1520-0450-30.7.985.
    [40] 潘旸, 宇婧婧, 廖捷, 等. 2011.地面和卫星降水产品对台风莫拉克降水监测能力的对比分析[J].气象, 37 (5):564-570. doi: 10.3969/j.issn.1671-1742.2011.05.017

    Pan Yang, Yu Jingjing, Liao Jie, et al. 2011. Assessment on the rainfall monitoring of typhoon Morakot by ground-gauged and satellite precipitation products[J]. Meteorological Monthly (in Chinese), 37 (5):564-570. doi: 10.3969/j.issn.1671-1742.2011.05.017
    [41] Peyrillé P, Lafore J P, Boone A. 2016. The annual cycle of the West African monsoon in a two-dimensional model:Mechanisms of the rain-band migration[J]. Quart. J. Roy. Meteor. Soc., 142 (696):1473-1489, doi: 10.1002/qj.2750.
    [42] Ren C P, Cui X P. 2014. The cloud-microphysical cause of torrential rainfall amplification associated with Bilis (0604)[J]. Science China Earth Sciences, 57 (9):2100-2111, doi: 10.1007/s11430-014-4884-6.
    [43] Sapiano M R P, Arkin P A. 2009. An intercomparison and validation of high-resolution satellite precipitation estimates with 3-hourly gauge data[J]. Journal of Hydrometeorology, 10 (1):149-166, doi: 10.1175/2008JHM1052.1.
    [44] Skamarock W C, Klemp J B, Dudhia J, et al. 2008. A description of the Advanced Research WRF version 3[R]. NCAR Technical Note NCAR/TN-475+STR, doi: 10.5065/D68S4MVH..
    [45] Sui C H, Li X F, Yang M J. 2007. On the definition of precipitation efficiency[J]. J. Atmos. Sci., 64 (12):4506-4513, doi: 10.1175/2007JAS2332.1.
    [46] Tao W K, Shi J J, Lin P L, et al. 2011. High-resolution numerical simulation of the extreme rainfall associated with typhoon Morakot. Part Ⅰ:Comparing the impact of microphysics and PBL parameterizations with observations[J]. Terrestrial Atmospheric and Oceanic Sciences, 22 (6):673, doi: 10.3319/TAO.2011.08.26.01(TM).
    [47] 王黎娟, 任晨平, 崔晓鹏, 等. 2013. "碧利斯"暴雨增幅高分辨率数值模拟及诊断分析[J].大气科学学报, 36 (2):147-157. doi: 10.3969/j.issn.1674-7097.2013.02.003

    Wang Lijuan, Ren Chenping, Cui Xiaopeng, et al. 2013. High-resolution numerical simulation and diagnostic analysis of rainfall amplification of Bills (0604)[J]. Transactions of Atmospheric Science (in Chinese), 36 (2):147-157, doi: 10.3969/j.issn.1674-7097.2013.02.003.
    [48] Wang J J, Li X F, Carey L D. 2007. Evolution, structure, cloud microphysical, and surface rainfall processes of monsoon convection during the South China Sea monsoon experiment[J]. J. Atmos. Sci., 64 (2):360-380, doi: 10.1175/JAS3852.1.
    [49] 韦青, 任福民, 张庆红, 等. 2010.西北太平洋热带气旋降水特征分析[J].热带气象学报, 26 (3):293-300. doi: 10.3969/j.issn.1004-4965.2010.03.005

    Wei Qing, Ren Fumin, Zhang Qinghong, et al. 2010. Climatological characteristics of tropical cyclone precipitation over western North Pacific[J]. Journal of Tropical Meteorology (in Chinese), 26 (3):293-300, doi: 10.3969/j.issn.1004-4965.2010.03.005.
    [50] Wu C C, Yen T H, Kuo Y H, et al. 2002. Rainfall simulation associated with typhoon Herb (1996) near Taiwan. Part Ⅰ:The topographic effect[J]. Wea. Forecasting, 17 (5):1001-1015, doi:10.1175/1520-0434(2003)017<1001:RSAWTH>2.0.CO;2.
    [51] 吴联要, 雷小途. 2012.内核及外围尺度与热带气旋强度关系的初步研究[J].热带气象学报, 28 (5):719-725. doi: 10.3969/j.issn.1004-4965.2012.05.011

    Wu Lianyao, Lei Xiaotu. 2012. Preliminary research on the size of inner core and periphery and their relationship with the intensity of tropical cyclones[J]. Journal of Tropical Meteorology (in Chinese), 28 (5):719-725, doi:10.3969/j.issn. 1004-4965.2012.05.011.
    [52] Yang M J, Braun S A, Chen D S. 2011. Water budget of typhoon Nari (2001)[J]. Mon. Wea. Rev., 139 (12):3809-3828, doi: 10.1175/MWR-D-10-05090.1.
    [53] Yu Z F, Yu H, Chen P Y, et al. 2008. Verification of tropical cyclone-related satellite precipitation estimates in mainland China[J]. Journal of Applied Meteorology and Climatology, 48 (11):2227-2241, doi: 10.1175/2009JAMC2143.1.
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  • 收稿日期:  2018-01-24
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