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Construction of a 3D structure of typhoon cloud based on an A-train satellite sensor

  • role： First author第一作者
  • Affiliation：

    College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China

  • Email：15754314335@163.com
  • Introduction：程崇慧，研究方向为大气环境遥感技术。E-mail： 15754314335@163.com
CHENG Chonghui1,  
  • Affiliation：

    College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China

CHEN Sijie1,  
  • Affiliation：

    College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China

ZHENG Zhuofan1,  
  • Affiliation：

    Shanghai Satellite Engineering Institute, Shanghai 200240, China

DONG Changzhe2,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

SU Lin3,  
  • Affiliation：

    College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China

KE Ju1,  
  • Affiliation：

    College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China

WANG Shuaibo1,  
  • Affiliation：

    College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China

TONG Bowen1,  
  • role： Corresponding author通信作者
  • Affiliation：

    College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China

  • Email：liudongopt@zju.edu.cn
  • Introduction：刘东，研究方向为环境激光雷达。E-mail： liudongopt@zju.edu.cn
LIU Dong1*

Resümee

Based on the satellite-based active-passive sensor data, this study uses the Constrained Spectral Radiance Matching (CSRM) algorithm to construct 3D structural models of deep convective clouds in eight western Pacific typhoon events, and accordingly analyses the deep convective clouds in different stages of typhoon development in terms of The horizontal distribution characteristics and microphysical characteristics of deep convective clouds in different stages of typhoon development are analysed. The significance of using CSRM algorithm for atmospheric 3D structure construction is to transfer the vertical distribution information from active remote sensing to the detection range of passive remote sensing, increase the number of contours available for statistical analysis of the eight typhoon events, and further ensure the validity of statistical analysis of deep convective clouds. The results of statistical analysis show that: (1) The proportion of deep convective clouds in the enhanced typhoons studied in this paper is 61.4% on average, and the standard deviation along all directions is 12.4% on average. In comparison, the proportion and standard deviation of typhoons in the weakening period decreased, which were 25.3% and 8.4%, respectively. Compared with typhoons, the average proportion of deep convective clouds in tropical storms is 45.2%, and the difference is greater in different directions, with a standard deviation of 23.1%. (2) The ice cloud effective radius of deep convective clouds in tropical cyclones is proportional to the height. The ice water number concentration first increases and then decreases with the increase in height. The vertical distribution of Ice Water Content (IWC) of deep convective clouds at different development stages of the same tropical cyclone is quite different. When a tropical cyclone develops into a typhoon, the IWC high-value area of its deep convective clouds gradually concentrates toward the top of the cloud layer, and the maximum value of IWC significantly increases as the typhoon transforms from an intensified period to a weakened period.

Schlüsselwort

Typhoon event;data fusion;Deep convective cloud;Three-dimensional structure;Microphysical properties

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