Application of a Cloud-Texture Analysis Scheme to the Cloud Cluster Structure Recognition and Rainfall Estimation in a Mesoscale Rainstorm Process

• Published in: Advances in atmospheric sciences Vol. 23; no. 5; pp. 767 - 774
• Main Author: 寿亦萱 励申申 寿绍文 赵忠明
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Nature B.V 01.09.2006; Nanjing University of Information Science and Technology,Nanjing,210044%Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101
• Subjects: Atmospheric sciences; Classification; Clouds; Rain; Rainfall; River basins; Studies; 中尺度; 暴风雨; 红外图像; China, People's Rep., Changjiang R; textural features; rainfall estimation; meso-scalc torrential rainstorms; infrared (IR) images; cloud classification
• ISSN: 0256-1530; 1861-9533
• DOI: 10.1007/s00376-006-0767-x

It is thought that satellite infrared （IR） images can aid the recognition of the structure of the cloud and aid the rainfall estimation. In this article, the authors explore the application of a classification method relevant to four texture features, viz. energy, entropy, inertial-quadrature and local calm, to the study of the structure of a cloud cluster displaying a typical meso-scaie structure on infrared satellite images. The classification using the IR satellite images taken during 4-5 July 2003, a time when a meso-scale torrential rainstorm was occurring over the Yangtze River basin, illustrates that the detailed structure of the cloud cluster can be obviously seen by means of the neural network classification method relevant to textural features, and the relationship between the textural energy and rainfall indicates that the structural variation of a cloud cluster can be viewed as an exhibition of the convection intensity evolvement. These facts suggest that the scheme of following a classification method relevant to textural features applied to cloud structure studies is helpful for weather analysis and forecasting.