摘要
气溶胶是地气系统辐射强迫评估的主要不确定来源之一,激光雷达探测的气溶胶廓线数据有助于定量评估气溶胶的气候效应。除已发布的气溶胶观测产品外,大量气溶胶激光雷达观测数据分布于文献中。然而,目前尚缺乏对气溶胶历史文献数据的整合分析。因此,聚焦现有观测产品较缺乏的激光雷达比参数,充分考虑气溶胶的类型差异,提出了一种激光雷达比历史文献数据的模糊综合评价分析方法。基于Web of Science数据库,发现不同类型气溶胶(沙尘、沙尘混合、火山灰、海洋、烟尘、城市工业气溶胶)的激光雷达比均呈高斯分布,且集中范围均存在重叠。历史文献数据能与气溶胶观测数据产品提供的数据形成互补,所提出的模糊综合评价分析方法有助于提升人们对气溶胶光学特性的认识。
Objective Aerosols are one of the major uncertain sources in radiative forcing assessments of the land-atmosphere system,and aerosol profile data detected by lidar can help quantitatively assess the climate effects of aerosols.In addition to published aerosol observation products,a large amount of aerosol lidar observation data are distributed in the references.However,there is still a lack of integrated analysis of historical aerosol reference data.Thus,we focus on the lidar ratio parameters that are relatively lacking in the existing observation products and propose a fuzzy comprehensive evaluation and analysis method of historical lidar ratio data with aerosol type differences fully considered.The historical data can complement the products of aerosol observation data,and the proposed evaluation and analysis method can help improving the understanding of optical aerosol properties.Methods Based on the idea of fuzzy comprehensive evaluation,we propose a fuzzy comprehensive evaluation and analysis method for the historical reference data of aerosol lidar ratio,and design the evaluation index of confidence level.The confidence level analysis is shown in Fig.1.First,the evaluation factors of the historical data are selected,and the analytic hierarchy process(AHP)is employed to determine the contribution proportion of each evaluation factor to the confidence level.Then,according to the characteristics of these factors,the membership function of each factor is determined,and the contribution weights are multiplied by the membership function to get the confidence value.Finally,the confidence values of all historical data are calculated,and the historical data of the same type and wavelength are accumulated to obtain the distribution of the total confidence values of the lidar ratio.To enable comparative evaluation,we normalize the total confidence values to obtain the distribution of confidence level for different types of aerosols lidar ratio over historical data.Results and Discussions All observations of aerosol lidar ratios in the Web of Science database are analyzed with confidence level by the proposed evaluation method.We find that all aerosol types show different aggregation trends similar to Gaussian distribution on the lidar ratio distribution,and the larger amount of historical data lead to a better Gaussian fitting effect.Additionally,the analysis is carried out for sand and dust aerosols from different sources,and the results shown in Fig.5 indicate that the optical properties of the same aerosol will be different for different sources.Finally,the confidence ranges of the lidar ratios for various aerosol types are summarized in Table 3 for reference,and the results are compared with the simulation data in Fig.6 with good consistency.Conclusions We propose a fuzzy comprehensive evaluation and analysis method for the historical reference data of aerosol lidar ratios,which makes up for the analysis method gap of historical aerosol data and provides references for analyzing the aerosol research basis.Analysis of all the relevant observations in the Web of Science database show that the historical data of lidar ratios of all aerosol types have Gaussian distributions.The traditional aerosol type recognition method is the decision tree,which adopts a fixed threshold to truncate the aerosol data and is prone to cause aerosol type misidentification and discontinuous classification limitation.The lidar ratios of different aerosol types overlap,and they alone are unable to differentiate various aerosol types.Therefore,at least one more classification index should be introduced when aerosol type identification is needed.We present a more comprehensive historical data analysis of the aerosol lidar ratio to improve the understanding of optical aerosol properties and refine the aerosol classification results,providing an accurate reference basis for data analysis of on-board lidars.
作者
胡先哲
刘东
肖达
张凯
毕磊
张敬昕
李蔚泽
李晓涛
邓洁松
周雨迪
刘群
吴兰
刘崇
万学平
陈文泰
陈晓龙
周剑烽
Hu Xianzhe;Liu Dong;Xiao Da;Zhang Kai;Bi Lei;Zhang Jingxin;Li Weize;Li Xiaotao;Deng Jiesong;Zhou Yudi;Liu Qun;Wu Lan;Liu Chong;Wan Xueping;Chen Wentai;Chen Xiaolong;Zhou Jianfeng(State Key Laboratory of Extreme Photonics and Instrumentation,College of Optical Science and Engineering,Zhejiang University,Hangzhou 310027,Zhejiang,China;Donghai Laboratory,Zhoushan 316021,Zhejiang,China;ZJU-Hangzhou Global Scientific and Technological Innovation Center,Hangzhou 311200,Zhejiang,China;Jiaxing Research Institute,Zhejiang University,Jiaxing 314000,Zhejiang,China;Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province,School of Earth Sciences,Zhejiang University,Hangzhou 310027,Zhejiang,China;Ningbo Innovation Center,Zhejiang University,Ningbo 315100,Zhejiang,China;Wuxi Zhongke Optoelectronic Technology Co.,Ltd.,Wuxi 214135,Jiangsu,China)
出处
《光学学报》
EI
CAS
CSCD
北大核心
2023年第24期88-99,共12页
Acta Optica Sinica
基金
国家重点研发计划(2022YFB3901704,2022YFC2203904,2021YFC2202001)
中央引导地方科技发展资金项目(2022ZYYDSAA00273)
国家自然科学基金(62205289)
浙江省自然科学基金(LQ23F050011)。
关键词
气溶胶
激光雷达比
历史数据
模糊综合评价
aerosol
lidar ratio
historical data
fuzzy comprehensive evaluation
