干旱区生态环境知识资源中心(Arid): The Strong Precipitation of the Dry Warm Front Cyclone in Syria and Its Prediction by Data Mining Modeling

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DOI	10.3390/atmos12121667
	The Strong Precipitation of the Dry Warm Front Cyclone in Syria and Its Prediction by Data Mining Modeling
	Wang, Jianhong; Alakol, Nour; Wang, Xing; He, Dongpo; Kumar, Kanike Raghavendra; Miao, Chunsheng
通讯作者	Wang, JH (corresponding author)，Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing 210044, Peoples R China. ; Wang, JH ; Wang, X (corresponding author)，Nanjing Univ Informat Sci & Technol, Coll Atmospher Sci, Nanjing 210044, Peoples R China. ; Wang, JH (corresponding author)，Nanjing Univ Informat Sci & Technol, Sch Marine Sci, Nanjing 210044, Peoples R China. ; Wang, X (corresponding author)，Nanjing Xinda Inst Meteorol Sci & Technol, Nanjing 210044, Peoples R China.
来源期刊	ATMOSPHERE
EISSN	2073-4433
出版年	2021
卷号	12 期号:12
英文摘要	The Eastern inland of Syria has a Mediterranean climate in the north and a tropical desert climate in the south, which results in a dry south and wet north climate feature, especially in winter. The circulation dynamics analysis of 16 winter strong precipitation events shows that the key system is the dry and warm front cyclone. In most cases (81-100% of the 16 cases), the moisture content in the northern part of the cyclone is higher than that in the southern part (influenced by the Mediterranean climate zone). The humidity in the middle layer is higher than that near the surface (uplifting of the dry warm front), and the thickness of the wet layer and the vertical ascending layer obviously expands upward (as shown by the satellite cloud top reflection). These characteristics lead to the moisture thermodynamic instability in the eastern part of the cyclone (dry and warm air at low level and wet and cold air at upper level). The cyclone flow transports momentum to the local humid layer of the Mediterranean climate belt and then causes unstable conditions and strong rainfall. Considering the limitations of the Syrian ground station network, the NCEP/CFSR global reanalysis data and MODIS aqua-3 cloud parameter data are used to build a multi-source factor index of winter precipitation from 2002 to 2016. A decision tree prediction model is then established and the factors index is constructed into tree shapes by the nodes and branches through calculating rules of information entropy. The suitable tree shape models are adjusted and selected by an automated training and testing process. The forecast model can classify rainfall with a forecast accuracy of more than 90% for strong rainfall over 30 mm.
英文关键词	Mediterranean climate zone dry warm front cyclone Syria winter strong precipitation MODIS Aqua Level-3 cloud parameters moisture thermodynamic instability decision tree prediction model
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000735737500001
WOS关键词	MODIS
WOS类目	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/375821
作者单位	[Wang, Jianhong] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing 210044, Peoples R China; [Wang, Jianhong; Alakol, Nour; Wang, Xing; Miao, Chunsheng] Nanjing Univ Informat Sci & Technol, Coll Atmospher Sci, Nanjing 210044, Peoples R China; [Wang, Jianhong] Nanjing Univ Informat Sci & Technol, Sch Marine Sci, Nanjing 210044, Peoples R China; [Wang, Xing; Miao, Chunsheng] Nanjing Xinda Inst Meteorol Sci & Technol, Nanjing 210044, Peoples R China; [He, Dongpo] Guizhou Meteorol Observ, Guiyang 550000, Peoples R China; [Kumar, Kanike Raghavendra] Koneru Lakshmaiah Educ Fdn KLEF, Dept Phys, Guntur 522502, Andhra Pradesh, India
推荐引用方式 GB/T 7714	Wang, Jianhong,Alakol, Nour,Wang, Xing,et al. The Strong Precipitation of the Dry Warm Front Cyclone in Syria and Its Prediction by Data Mining Modeling[J],2021,12(12).
APA	Wang, Jianhong,Alakol, Nour,Wang, Xing,He, Dongpo,Kumar, Kanike Raghavendra,&Miao, Chunsheng.(2021).The Strong Precipitation of the Dry Warm Front Cyclone in Syria and Its Prediction by Data Mining Modeling.ATMOSPHERE,12(12).
MLA	Wang, Jianhong,et al."The Strong Precipitation of the Dry Warm Front Cyclone in Syria and Its Prediction by Data Mining Modeling".ATMOSPHERE 12.12(2021).