A-Train卫星传感器的台风云体三维结构构建

程崇慧; 陈斯婕; 郑卓凡; 董长哲; 苏林; 柯举; 王帅博; 仝博文; 刘东

doi:10.11834/jrs.20210154

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A-Train卫星传感器的台风云体三维结构构建
Construction of a 3D structure of typhoon cloud based on an A-train satellite sensor
2022年26卷第11期页码：2192-2203
纸质出版日期： 2022-11-07 ，
DOI： 10.11834/jrs.20210154

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程崇慧，陈斯婕，郑卓凡，董长哲，苏林，柯举，王帅博，仝博文，刘东.2022.A-Train卫星传感器的台风云体三维结构构建.遥感学报，26（11）： 2192-2203

Cheng C H，Chen S J，Zheng Z F，Dong C Z，Su L，Ke J，Wang S B，Tong B W and Liu D. 2022. Construction of a 3D structure of typhoon cloud based on an A-train satellite sensor. National Remote Sensing Bulletin， 26（11）：2192-2203
程崇慧，陈斯婕，郑卓凡，董长哲，苏林，柯举，王帅博，仝博文，刘东.2022.A-Train卫星传感器的台风云体三维结构构建.遥感学报，26（11）： 2192-2203 DOI： 10.11834/jrs.20210154.

Cheng C H，Chen S J，Zheng Z F，Dong C Z，Su L，Ke J，Wang S B，Tong B W and Liu D. 2022. Construction of a 3D structure of typhoon cloud based on an A-train satellite sensor. National Remote Sensing Bulletin， 26（11）：2192-2203 DOI： 10.11834/jrs.20210154.

摘要

基于星载主‒被动传感器数据，本研究利用约束光谱辐射匹配CSRM（Constrained Spectral Radiance Matching）算法构建了8个西太平洋台风事件中的深对流云层三维结构模型，并据此分析深对流云在台风不同发展阶段中的水平分布特征和微物理特征。利用CSRM算法进行大气三维结构构建的意义在于将主动遥感的垂直分布信息向被动遥感的探测范围传递，增加统计分析8个台风事件可用的廓线数量，进一步保证对深对流云统计分析的有效性，统计分析结果表明：（1）衰弱期台风的深对流云占比（占所有种类云的比例）比增强期台风更低，并且其值在各个方向上更稳定。相比于台风，热带风暴中的深对流云占比在各个方向上差异更大，即不对称性更强；（2）热带气旋中深对流云的冰云有效粒子半径与高度成正比。随着高度增加，冰水粒子数浓度先增加后减少。同一热带气旋不同发展阶段的深对流云的冰水含量IWC（Ice Water Content）的垂直分布有着较大的差别。当热带气旋发展成台风时，其内部深对流云的IWC高值区逐渐向云层顶部集中，并且随着台风从增强期转化为衰弱期，IWC的最大值显著增大。

Abstract

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.

关键词

台风事件星载主—被动数据融合深对流云三维结构微物理特性

Keywords

typhoon eventdata fusiondeep convective cloudthree-dimensional structuremicrophysical properties

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