基于多源数据的云中过冷水反演方法研究

• 1:南京信息工程大学气象灾害预报预警与评估协同创新中心

• 2:中国气象局气溶胶与云降水重点开放实验室

• 3:中国科学院中层大气和全球环境探测重点实验室

• 4:南京信大安全应急管理研究院

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摘要(Abstract)：

云中过冷水的含量及分布是造成飞机积冰的主要原因，因此准确识别云中过冷水区域尤为重要.利用英国Chilbolton观测场的35 GHz、94 GHz毫米波测云雷达、激光雷达以及微波辐射计，结合探空资料，对阈值法和模糊逻辑算法识别云中过冷水分布情况进行对比研究，以及利用多普勒密度算法对不同水凝物含水量情况进行计算.结果表明：1)对比阈值法以及微波辐射计液态水路径的反演结果后认为模糊逻辑算法对水凝物的识别具有更高的反演精度；2)混合相态云中由于冰晶粒子主导雷达回波强度，会导致云中液态水含量被低估，需分别计算不同水凝物的雷达反射率因子.
The content and distribution of supercooled water in the cloud are the main reasons for aircraft icing, so it is particularly important to accurately identify the supercooled water area in the cloud. In this paper, the 35 GHz and 94 GHz millimeter wave cloud radar and lidar of chilbolton observation field in Britain are used to compare the distribution of supercooled water in clouds identified by threshold method and fuzzy logic algorithm, and the water content of different water condensates is calculated by Doppler density algorithm. The results show that: 1)compared with the inversion results of threshold method and microwave radiometer, the fuzzy logic algorithm has higher inversion accuracy for the identification of water condensate; 2)In mixed phase clouds, because ice crystal particles dominate the radar echo intensity, the liquid water content in the clouds will be underestimated. It is necessary to calculate the radar reflectivity factors of different water condensates.

关键词(KeyWords)：过冷水;毫米波雷达;模糊逻辑;多普勒谱
supercooled water;millimeter wave radar;fuzzy logic;Doppler spectrum

基金项目(Foundation):国家自然科学基金(41905026);; 江苏省自然科学基金(BK20170945);; 南京信息工程大学人才启动基金资助项目(2016r028);; 江苏省333工程高层次人才培养资助(第三层次);; 中国博士后科学基金第63批面上资助(2018M631554)

作者(Authors):王金虎;肖安虹;王宇豪;王昊亮;包金旺;
Wang Jinhu;Xiao Anhong;Wang Yuhao;Wang Haoliang;Bao Jinwang;Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology;Key Open Laboratory of Aerosol and Cloud Precipitation,China Meteorological Administration;Key Laboratory of Middle Atmosphere and Global Environment Observation, Chinese Academy of Sciences;Nanjing Xinda Institute of Safety and Emergency Management;

DOI:10.16366/j.cnki.1000-2367.2023.04.014

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