DOI: 10.1002/2014GL062111
论文题名: Global dust distribution from improved thin dust layer detection using A-train satellite lidar observations
作者: Luo T. ; Wang Z. ; Zhang D. ; Liu X. ; Wang Y. ; Yuan R.
刊名: Geophysical Research Letters
ISSN: 0094-9055
EISSN: 1944-8786
出版年: 2015
卷: 42, 期: 2 起始页码: 620
结束页码: 628
语种: 英语
英文关键词: A-train observation
; dust detection
; dust global distribution
Scopus关键词: Aerosols
; Algorithms
; Clouds
; Optical radar
; A-train
; Aerosol-cloud interaction
; Cloud-aerosol lidar and infrared pathfinder satellite observations
; Depolarization ratio
; Dust detection
; Dust distribution
; Global distribution
; Upper troposphere
; Dust
; algorithm
; altitude
; CALIPSO
; dust
; global climate
; optical property
; polarization
; troposphere
英文摘要: A new dust detection algorithm was developed to take advantage of strong dust signals in the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) 532 nm perpendicular channel to more accurately identify optically thin dust layer boundaries. Layer mean particulate depolarization ratios and improved thin ice cloud detections by combining CALIPSO and CloudSat products were used to further refine the dust mask. Three year global mean results show that the new method detects dust occurrences total detected dust case numbertotal observation number of 0.12 and 0.028 below and above 4 km altitudes, while CALIPSO Level 2 products reported 0.07 and 0.012, respectively. The improvements are mainly in weak source and transporting regions, and the upper troposphere, where optically thin, but significant dust layers from the point of view of aerosol-cloud interactions are dominated. The results can help us to better understand global dust transportation and dust-cloud interactions and improve model simulations. © 2015. American Geophysical Union. All Rights Reserved. URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84923543866&doi=10.1002%2f2014GL062111&partnerID=40&md5=abb1088e773592433e1ba1cfc27fd764
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/8671
Appears in Collections: 科学计划与规划 气候变化与战略
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作者单位: Department of Atmospheric Science, University of Wyoming, Laramie, WY, United States
Recommended Citation:
Luo T.,Wang Z.,Zhang D.,et al. Global dust distribution from improved thin dust layer detection using A-train satellite lidar observations[J]. Geophysical Research Letters,2015-01-01,42(2).