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

机译:云纹理分析方案在中尺度暴雨过程中云团结构识别与降雨估算中的应用

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摘要

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-scale 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.
机译:人们认为,卫星红外(IR)图像可以帮助识别云的结构并有助于降雨估计。在本文中,作者探索了与四个纹理特征相关的分类方法的应用。能量,熵,惯性正交和局部平静,以研究在红外卫星图像上显示典型的中尺度结构的云团的结构。使用2003年7月4日至5日(当时长江流域发生中尺度暴雨)拍摄的IR卫星图像进行分类,表明可以通过神经网络清楚地看到云团的详细结构。构造特征相关的网络分类方法,以及构造能量和降雨之间的关系表明,云团的结构变化可以看作是对流强度演变的一种表现。这些事实表明,遵循与纹理特征相关的分类方法应用于云结构研究的方案有助于进行天气分析和预报。

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