An Overview of Passive and Active Dust Detection Methods Using Satellite Measurements
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 measu...
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Published in | Acta meteorologica Sinica Vol. 28; no. 6; pp. 1029 - 1040 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
Heidelberg
The Chinese Meteorological Society
01.12.2014
Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences,Lanzhou University, Lanzhou 730000%National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081 |
Subjects | |
Online Access | Get full text |
ISSN | 0894-0525 2095-6037 2198-0934 2191-4788 |
DOI | 10.1007/s13351-014-4032-4 |
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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. |
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AbstractList | 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. 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 µm, 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. 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 mu m, 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. |
Author | 陈斌 张鹏 张北斗 贾瑞 张芝娟 王天河 周天 |
AuthorAffiliation | Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000 National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081 |
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Notes | 11-2277/P 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. dust detection integrated multi-sensors passive and active measurements CHEN Bin, ZHANG Peng, ZHANG Beidou, JIA Rui( 1 Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000 2 National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081) ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
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Publisher | The Chinese Meteorological Society Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences,Lanzhou University, Lanzhou 730000%National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081 |
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Snippet | In this paper,the methods to detect dust based on passive and active measurements from satellites have been summarized.These include the visible and... 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... |
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SubjectTerms | Atmospheric Protection/Air Quality Control/Air Pollution Atmospheric Sciences Earth and Environmental Science Earth Sciences Geophysics and Environmental Physics IR方法 Meteorology MPI方法 卫星测量 无源 有源 沙尘气溶胶 激光雷达 粉尘检测 |
Title | An Overview of Passive and Active Dust Detection Methods Using Satellite Measurements |
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