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