干旱区生态环境知识资源中心(Arid): A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar

Arid

DOI	10.5194/amt-14-1743-2021
	A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar
	Hu, Xiaoyu; Ge, Jinming; Du, Jiajing; Li, Qinghao; Huang, Jianping; Fu, Qiang
通讯作者	Ge, JM (corresponding author), Lanzhou Univ, Key Lab Semiarid Climate Change, Minist Educ, Lanzhou 730000, Peoples R China. ; Ge, JM (corresponding author), Lanzhou Univ, Coll Atmospher Sci, Lanzhou 730000, Peoples R China.
来源期刊	ATMOSPHERIC MEASUREMENT TECHNIQUES
ISSN	1867-1381
EISSN	1867-8548
出版年	2021
卷号	14 期号:2 页码:1743-1759
英文摘要	Low-level clouds play a key role in the energy budget and hydrological cycle of the climate system. The accurate long-term observation of low-level clouds is essential for understanding their climate effect and model constraints. Both ground-based and spaceborne millimeter-wavelength cloud radars can penetrate clouds but the detected low-level clouds are always contaminated by clutter, which needs to be removed. In this study, we develop an algorithm to accurately separate low-level clouds from clutter for ground-based cloud radar using multi-dimensional probability distribution functions along with the Bayesian method. The radar reflectivity, linear depolarization ratio, spectral width, and their dependence on the time of the day, height, and season are used as the discriminants. A low-pass spatial filter is applied to the Bayesian undecided classification mask by considering the spatial correlation difference between clouds and clutter. The final feature mask result has a good agreement with lidar detection, showing a high probability of detection rate (98.45 %) and a low false alarm rate (0.37 %). This algorithm will be used to reliably detect low-level clouds at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) site for the study of their climate effect and the interaction with local abundant dust aerosol in semi-arid regions.
类型	Article
语种	英语
开放获取类型	gold, Green Submitted
收录类别	SCI-E
WOS记录号	WOS:000626292800002
WOS关键词	MELTING LAYER RECOGNITION ; MICRO-PULSE LIDAR ; DOPPLER RADAR ; SHALLOW CUMULUS ; CLIMATE ; PRECIPITATION ; CIRRUS ; IMPACT ; RAIN ; CLASSIFICATION
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/2XILL650/349645
作者单位	[Hu, Xiaoyu; Ge, Jinming; Du, Jiajing; Li, Qinghao; Huang, Jianping] Lanzhou Univ, Key Lab Semiarid Climate Change, Minist Educ, Lanzhou 730000, Peoples R China; [Hu, Xiaoyu; Ge, Jinming; Du, Jiajing; Li, Qinghao; Huang, Jianping] Lanzhou Univ, Coll Atmospher Sci, Lanzhou 730000, Peoples R China; [Fu, Qiang] Univ Washington, Dept Atmospher Sci, Seattle, WA 98105 USA
推荐引用方式 GB/T 7714	Hu, Xiaoyu,Ge, Jinming,Du, Jiajing,et al. A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar[J]. 兰州大学,2021,14(2):1743-1759.
APA	Hu, Xiaoyu,Ge, Jinming,Du, Jiajing,Li, Qinghao,Huang, Jianping,&Fu, Qiang.(2021).A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar.ATMOSPHERIC MEASUREMENT TECHNIQUES,14(2),1743-1759.
MLA	Hu, Xiaoyu,et al."A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar".ATMOSPHERIC MEASUREMENT TECHNIQUES 14.2(2021):1743-1759.