DocumentCode :
3023813
Title :
Relation between Cumulonimbus(Cb) preicitiation and cloud dynamical features over Huaihe River Basin of China based on FY-2C image
Author :
Yu Liu ; Zhao-Liang Li ; Chun-Xiang Shi ; Bo-Hui Tang ; Hua Wu ; Qingsheng Liu
Author_Institution :
State Key Lab. of Resources & Environ. Inf. Syst., Inst. of Geogr. Sci. & Natural Resources Res., Beijing, China
fYear :
2013
fDate :
21-26 July 2013
Firstpage :
554
Lastpage :
557
Abstract :
The crowning objective of this research are to analyze precipitation character of Cb for different dynamical characters in Huai river basin(HRB) with China´s first operational geostationary meteorological satellite FengYun-2C (FY-2C) data. Firstly, 5 cloud patch dynamic parameters with respect to life stage and moving parameters are derived based on the Cb tracking method the author has proposed by combing artificial neural network (ANN) cloud classification[1], and cross-correlation-based approach to track Cb patch motion. Secondly, Cb precipitation over different life cycles and motion characters are analyzed. The result shows that: 1) Rain probability has a similar variation to rain rate, and rain rate is generally not more than 6 mm/hour, and probability is randomly higher than 50%. 2) Both rain rate and probability of single Cb is lower than that of complicated Cb which involves cell-merger and cell-split of some minor Cb patches. 3) Motion features such as horizontal moving speed of cloud patch (HMSP), horizontal moving direction of cloud patch (HMDP), and vertical moving character of cloud patch (VMCP) have no obvious impact on rain.
Keywords :
clouds; geophysical signal processing; rain; remote sensing; China; Cumulonimbus precipitation; FY-2C image; FengYun-2C data; Huaihe river basin; artificial neural network; cloud classification; cloud dynamical features; cloud patch dynamic parameters; cross correlation based approach; geostationary meteorological satellite; horizontal moving direction of cloud patch; rain probability; rain rate; vertical moving character of cloud patch; Artificial neural networks; Clouds; Dynamics; Radar tracking; Rain; Rivers; Tracking; Cumulonimbus; Dynamic features; FY-2C; Precipitation; cloud patch;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
ISSN :
2153-6996
Print_ISBN :
978-1-4799-1114-1
Type :
conf
DOI :
10.1109/IGARSS.2013.6721216
Filename :
6721216
Link To Document :
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