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The Impact of Cloud Microphysical Processes on Typhoon Numerical Simulation
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摘要: 将中国气象科学研究院（CAMS）混合双参数云微物理方案用于中尺度天气模式WRF，开展了对2013年超强台风天兔（1319）的模拟，通过与台风最佳路径、强度及热带降雨测量卫星（TRMM）资料对比，分析CAMS云微物理方案在模拟台风中的适用性及云微物理过程对模拟台风天兔的影响机制。设计了3组敏感性试验：修改雪粒子质量和落速系数（EXP1），采用海洋性云滴参数（EXP2），同时修改雪粒子质量和落速系数并采用海洋性云滴参数（EXP3）。结果表明：EXP1和EXP3由于霰碰并雪速率的增加及减小的雪下落通量，导致雪含量显著降低，同时也减少了整体冰相物的含量；EXP2和EXP3模拟的台风眼区对流有效位能快速减小，再现了前期台风的快速增强过程，路径偏差也最小；各试验模拟的小时降水率总体偏强，EXP3的降水空间分布与实况更接近，明显降低雪粒子含量，并一定程度上改善模拟的台风路径、强度及降水分布等。该结果不但可为改进适用于台风的云微物理参数化方案提供思路，也可加深云微物理过程对台风影响的认识。
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关键词:
- CAMS云微物理方案;
- 台风;
- 微物理过程;
- 数值模拟
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.-
Key words:
- CAMS microphysics;
- typhoon;
- microphysical processes;
- numerical simulation
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图 2 2013年9月18日00:00—22日06:00台风天兔路径(a)，海平面最低气压(实线)和中心最大风速(虚线)(b)时间演变
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
图 3 2013年9月21日02:00 TRMM/PR产品和CTRL模拟的3 km及8 km高度的雷达反射率因子
(黑线区域表示与TRMM/PR轨道相近的台风主体区域)
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)
图 4 2013年9月21日02:00 TRMM/PR产品(a)，CTRL模拟(b)的雷达反射率因子的等高频率图
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
图 5 2013年9月21日02:00台风中心半径300 km范围内TMI/2A12产品(a)和CAMS微物理方案模拟(b)的区域平均水成物含量垂直分布
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
图 6 2013年9月18日12:00—22日00:00 4个数值试验模拟的对流有效位能径向时间演变(黑实线表示两倍最大风速半径) (a)CTRL，(b)EXP1，(c)EXP2, (d)EXP3
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
图 7 2013年9月18日12:00—22日06:00台风中心半径300 km范围内时间-区域平均的水成物含量垂直廓线(a)CTRL，(b)EXP1，(c)EXP2，(d)EXP3
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
图 8 2013年9月18日12:00—22日06:00台风中心300 km半径内区域-时间平均的云水、雨水、雪粒子含量主要微物理过程转化率
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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