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An Overview of Passive and Active Dust Detection Methods Using Satellite Measurements

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【作者】 陈斌张鹏张北斗贾瑞张芝娟王天河周天

【Author】 CHEN Bin;ZHANG Peng;ZHANG Beidou;JIA Rui;ZHANG Zhijuan;WANG Tianhe;ZHOU Tian;Key Laboratory for Semi-Arid Climate Change of the Ministry of Education,College of Atmospheric Sciences,Lanzhou University;National Satellite Meteorological Center,China Meteorological Administration;

【机构】 Key Laboratory for Semi-Arid Climate Change of the Ministry of Education,College of Atmospheric Sciences,Lanzhou UniversityNational Satellite Meteorological Center,China Meteorological Administration

【摘要】 In this paper,the methods to detect dust based on passive and active measurements from satellites have been summarized.These include the visible and infrared(VIR) method,thermal infrared(TIR) method,microwave polarized index(MPI) method,active lidar-based method,and combined lidar and infrared measurement(CLIM) method.The VIR method can identify dust during daytime.Using measurements at wavelengths of 8.5,11.0,and 12.0 fan,the TIR method can distinguish dust from other types of aerosols and cloud,and identify the occurrence of dust over bright surfaces and during night.Since neither the VIR nor the TIR method can penetrate ice clouds,they cannot detect dust beneath ice clouds.The MPI method,however,can identify about 85%of the dust beneath ice clouds.Meanwhile,the active lidar-based method,which uses the Cloud-Aerosol Lidar with Orthogonal Polarization(CALIOP) data and five-dimensional probability distribution functions,can provide very high-resolution vertical profiles of dust aerosols.Nonetheless,as the signals from dense dust and thin clouds are similar in the CALIOP measurements,the lidar-based method may fail to distinguish between them,especially over dust source regions.To address this issue,the CLIM method was developed,which takes the advantages of both TIR measurements(to discriminate between ice cloud and dense dust layers) and lidar measurements(to detect thin dust and water cloud layers).The results obtained by using the new CLIM method show that the ratio of dust misclassification has been significantly reduced.Finally,a concept module for an integrated multi-satellites dust detection system was proposed to overcome some of the weaknesses inherent in the single-sensor dust detection.

【Abstract】 In this paper,the methods to detect dust based on passive and active measurements from satellites have been summarized.These include the visible and infrared(VIR) method,thermal infrared(TIR) method,microwave polarized index(MPI) method,active lidar-based method,and combined lidar and infrared measurement(CLIM) method.The VIR method can identify dust during daytime.Using measurements at wavelengths of 8.5,11.0,and 12.0 fan,the TIR method can distinguish dust from other types of aerosols and cloud,and identify the occurrence of dust over bright surfaces and during night.Since neither the VIR nor the TIR method can penetrate ice clouds,they cannot detect dust beneath ice clouds.The MPI method,however,can identify about 85%of the dust beneath ice clouds.Meanwhile,the active lidar-based method,which uses the Cloud-Aerosol Lidar with Orthogonal Polarization(CALIOP) data and five-dimensional probability distribution functions,can provide very high-resolution vertical profiles of dust aerosols.Nonetheless,as the signals from dense dust and thin clouds are similar in the CALIOP measurements,the lidar-based method may fail to distinguish between them,especially over dust source regions.To address this issue,the CLIM method was developed,which takes the advantages of both TIR measurements(to discriminate between ice cloud and dense dust layers) and lidar measurements(to detect thin dust and water cloud layers).The results obtained by using the new CLIM method show that the ratio of dust misclassification has been significantly reduced.Finally,a concept module for an integrated multi-satellites dust detection system was proposed to overcome some of the weaknesses inherent in the single-sensor dust detection.

【基金】 Supported by the National Basic Research and Development (973) Program of China(2012CB955301);National Natural Science Foundation of China(41305026,41075021,41305027);Fundamental Research Fund for the Central Universities of China(LZUJBKY-2013-104)
  • 【文献出处】 Journal of Meteorological Research ,气象学报(英文版) , 编辑部邮箱 ,2014年06期
  • 【分类号】X831;P412.27
  • 【被引频次】4
  • 【下载频次】72
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