Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1007/s13351-014-3051-5 |
Discrimination and validation of clouds and dust aerosol layers over the Sahara desert with combined CALIOP and IIR measurements | |
Liu Jingjing; Chen Bin; Huang Jianping | |
通讯作者 | Huang Jianping |
来源期刊 | JOURNAL OF METEOROLOGICAL RESEARCH |
ISSN | 2095-6037 |
EISSN | 2198-0934 |
出版年 | 2014 |
卷号 | 28期号:2页码:185-198 |
英文摘要 | This study validates a method for discriminating between daytime clouds and dust aerosol layers over the Sahara Desert that uses a combination of active CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) and passive IIR (Infrared Imaging Radiometer) measurements; hereafter, the CLIM method. The CLIM method reduces misclassification of dense dust aerosol layers in the Sahara region relative to other techniques. When evaluated against a suite of simultaneous measurements from CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations), CloudSat, and the MODIS (Moderate-resolution Imaging Spectroradiometer), the misclassification rate for dust using the CLIM technique is 1.16% during boreal spring 2007. This rate is lower than the misclassification rates for dust using the cloud aerosol discriminations performed for version 2 (V2-CAD; 16.39%) or version 3 (V3-CAD; 2.01%) of the CALIPSO data processing algorithm. The total identification errors for data from in spring 2007 are 13.46% for V2-CAD, 3.39% for V3-CAD, and 1.99% for CLIM. These results indicate that CLIM and V3-CAD are both significantly better than V2-CAD for discriminating between clouds and dust aerosol layers. Misclassifications by CLIM in this region are mainly limited to mixed cloud-dust aerosol layers. V3-CAD sometimes misidentifies low-level aerosol layers adjacent to the surface as thin clouds, and sometimes fails to detect thin clouds entirely. The CLIM method is both simple and fast, and may be useful as a reference for testing or validating other discrimination techniques and methods. |
英文关键词 | CALIPSO CLIM dust detection |
类型 | Article |
语种 | 英语 |
国家 | Peoples R China |
收录类别 | SCI-E |
WOS记录号 | WOS:000337596600002 |
WOS关键词 | A-TRAIN ; SATELLITE ; CALIPSO ; LIDAR ; TRANSPORT ; STORMS ; MODIS ; RETRIEVAL ; CLIMATE ; MISSION |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
来源机构 | 兰州大学 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/183570 |
作者单位 | Lanzhou Univ, Minist Educ, Coll Atmospher Sci, Key Lab Semiarid Climate Change, Lanzhou 730000, Peoples R China |
推荐引用方式 GB/T 7714 | Liu Jingjing,Chen Bin,Huang Jianping. Discrimination and validation of clouds and dust aerosol layers over the Sahara desert with combined CALIOP and IIR measurements[J]. 兰州大学,2014,28(2):185-198. |
APA | Liu Jingjing,Chen Bin,&Huang Jianping.(2014).Discrimination and validation of clouds and dust aerosol layers over the Sahara desert with combined CALIOP and IIR measurements.JOURNAL OF METEOROLOGICAL RESEARCH,28(2),185-198. |
MLA | Liu Jingjing,et al."Discrimination and validation of clouds and dust aerosol layers over the Sahara desert with combined CALIOP and IIR measurements".JOURNAL OF METEOROLOGICAL RESEARCH 28.2(2014):185-198. |
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