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Volume 23 Issue 5

Sep.  2006

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2006 >  23(5): 767-774

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

  • 1.

    Nanjing University of Information Science and Technology, Nanjing 210044,Nanjing University of Information Science and Technology, Nanjing 210044,Nanjing University of Information Science and Technology, Nanjing 210044,Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101


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-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.
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    • Manuscript History

    Manuscript received: 10 September 2006
    Manuscript revised: 10 September 2006
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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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

    • 1. Nanjing University of Information Science and Technology, Nanjing 210044,Nanjing University of Information Science and Technology, Nanjing 210044,Nanjing University of Information Science and Technology, Nanjing 210044,Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101
    • Manuscript received: 2006-09-10
    • Manuscript revised: 2006-09-10

    Abstract: 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.

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