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Atmosphere 2014, 5(2), 211-229; doi:10.3390/atmos5020211

Analysis and Application of the Relationship between Cumulonimbus (Cb) Cloud Features and Precipitation Based on FY-2C Image

4,5,*  and 6
1 Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China 2 Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China 3 Naval Institute of Hydrographic Surveying and Charting, Tianjin 300061, China 4 Key Laboratory of Agri-Informatics, Ministry of Agriculture / Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China 5 ICube, UdS, CNRS, 300 Bld Sebastien Brant, BP10413, 67412 Illkirch, France 6 National Meteorological Information Center, China Meteorological Administration, Beijing 100081, China
* Author to whom correspondence should be addressed.
Received: 29 December 2013 / Revised: 25 March 2014 / Accepted: 28 March 2014 / Published: 14 April 2014
(This article belongs to the Special Issue Cloud and Precipitation)
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Although cumulonimbus (Cb) clouds are the main source of precipitation in south China, the relationship between Cb cloud characteristics and precipitation remains unclear. Accordingly, the primary objective of this study was to thoroughly analyze the relationship between Cb cloud features and precipitation both at the pixel and cloud patch scale, and then to apply it in precipitation estimation in the Huaihe River Basin using China’s first operational geostationary meteorological satellite, FengYun-2C (FY-2C), and the hourly precipitation data of 286 gauges from 2007. First, 31 Cb parameters (14 parameters of three pixel features and 17 parameters of four cloud patch features) were extracted based on a Cb tracking method using an artificial neural network (ANN) cloud classification as a pre-processing procedure to identify homogeneous Cb patches. Then, the relationship between Cb cloud properties and precipitation was analyzed and applied in a look-up table algorithm to estimate precipitation. The results were as follows: (1) Precipitation increases first and then declines with increasing values for cold cloud and time evolution parameters, and heavy precipitation may occur not only near the convective center, but also on the front of the Cb clouds on the pixel scale. (2) As for the cloud patch scale, precipitation is typically associated with cold cloud and rough cloud surfaces, whereas the coldest and roughest cloud surfaces do not correspond to the strongest rain. Moreover, rainfall has no obvious relationship with the cloud motion features and varies significantly over different life stages. The involvement of mergers and splits of minor Cb patches is crucial for precipitation processes. (3) The correlation coefficients of the estimated rain rate and gauge rain can reach 0.62 in the cross-validation period and 0.51 in the testing period, which indicates the feasibility of the further application of the relationship in precipitation estimation.
Keywords: FY-2C; cumulonimbus; cloud features; precipitation; Huaihe River Basin FY-2C; cumulonimbus; cloud features; precipitation; Huaihe River Basin
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Liu, Y.; Xi, D.-G.; Li, Z.-L.; Shi, C.-X. Analysis and Application of the Relationship between Cumulonimbus (Cb) Cloud Features and Precipitation Based on FY-2C Image. Atmosphere 2014, 5, 211-229.

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