红外与毫米波学报2025，Vol.44Issue(6)：875-886,12.DOI:10.11972/j.issn.1001-9014.2025.06.006
基于CALIOP数据的气溶胶垂直分布特征聚类分析
Clustering analysis of aerosol vertical distribution characteristics based on CALIOP data
摘要
Abstract
The vertical distribution of aerosols plays a critical role in improving the accuracy of aerosol retrieval in satel-lite remote sensing due to its complexity and spatiotemporal variability.This study investigated the vertical characteris-tics of aerosols using unsupervised clustering methods,based on CALIOP(Cloud-Aerosol Lidar with Orthogonal Polar-ization)Level 3 aerosol profile data from 2010 to 2020.Three clustering algorithms—Gaussian Mixture Model(GMM),K-means,and spectral clustering—were evaluated using multiple performance metrics.The profiles of extinc-tion coefficients were clustered into five representative types using the GMM algorithm:low-pollution composite type,high-pollution composite type,exponential decay type,low-pollution uniform type,and high-pollution oscillatory type.The seasonal and regional distributions of these profile types were further analyzed over the Tibetan Plateau,the Beijing-Tianjin-Hebei region,and the Yangtze River Delta.The results show that aerosol vertical profiles exhibit dis-tinct seasonal and regional patterns.These findings provide a basis for improving aerosol profile parameterization and re-trieval accuracy in remote sensing applications.关键词
气溶胶/气溶胶垂直分布/聚类分析/CALIPSOKey words
aerosols/aerosol vertical distribution/cluster analysis/CALIPSO分类
天文与地球科学引用本文复制引用
王宇轩,孙晓兵,提汝芳,黄红莲,刘晓,余海啸..基于CALIOP数据的气溶胶垂直分布特征聚类分析[J].红外与毫米波学报,2025,44(6):875-886,12.基金项目
航天科技创新应用研究项目(E23Y0H555S1)、航空科技创新应用研究项目(62502510201)、中国科学院重点实验室基金项目(E33Y0HB42P1) Supported by the Aerospace Science and Technology Innovation Application Research Project(E23Y0H555S1),the Aviation Sci-ence and Technology Innovation Application Research Project(62502510201),the Chinese Academy of Sciences Key Laboratory Fund Program(E33Y0HB42P1) （E23Y0H555S1）
