红外云图上中尺度对流系统的自动识别*

南京大学学报(自然科学版) ›› 2010, Vol. 46 ›› Issue (3): 337–348.

红外云图上中尺度对流系统的自动识别*

束宇** , 潘益农

出版日期:2015-03-30 发布日期:2015-03-30
作者简介: (南京大学大气科学学院中尺度灾害性天气教育部重点实验室, 南京, 210093)
基金资助:
国家自然科学基金( 40875028) , 国家基础研究发展规划项目( 2009CB421502)

Self?identification of mesoscale convective system from satellite infrared imagery

Shu Yu, Pan Yi Nong

Online:2015-03-30 Published:2015-03-30
About author: ( Key Laboratory for Mesoscale of Severe Weather/Ministry of Education, and School of Atmospheric Sciences, Nanjing University, Nanjing, 210093, China)

摘要/Abstract

摘要： 中尺度对流系统( MCS) 是夏季造成暴雨等灾害性天气的重要天气系统. 高时空分辨率的静止卫星红外云图是监测 MCS 的主要手段之一. 在以往的研究中, 对 M CS 的普查是通过对打印出的增强显
示的红外云图进行人工对比的方法. 本文提出了一种计算机自动识别方法来普查 MCS. 和已有的人工普查方法相比, 新方法具有快速、准确、可移植性强的优点, 这就为准确的研究 M CS 的冷云盖面积、长轴
长度、形状、地理分布、生命史日变化等的统计特征提供了机会, 给 MCS 的气候学特征和区域特征的研究提供了机会. 新方法适用于 GMS、风云、 GOES 等不同格式的静止卫星资料, 在具体应用时只需将数
据处理这一块的程序加以修改. 本文中以 GMS?5 原始数值资料为例介绍新方法的原理. 首先通过轮廓编码的方法来查找和计算某一时次云图上的 MCS 轮廓, 再通过系统查找法来追踪系统, 最后判断该系
统是否满足 MCS 的标准. 以 1999 年 GMS?5 资料为例进行的抽样普查表明, 新方法可以较为准确和快速的普查到 MCS,?尺度系统的误差率为每个系统 0 ? 191 处, 尺度系统的误差率为每个系统 0 ? 101处.
新方法为 MCS 的普查提供了一个新的快速可行之路, 但新方法中也存在一些问题, 需要在进一步的研究中加以完善.

Abstract: Mesoscale convective systems ( MCSs) cause heavy rain and other severe weather events during the warmseason. Geostationary satellite infrared imagery with fine spatial and temporal resolution can provide much available
information for M CS surveillance. The previous method of MCS census was to compare the plotting infrared imagerymanually. In this article, however, a new method of identifying MCS from infrared imagery by selfidentification is
developed, as is much more time saving, more accurate and better transplantable than the old method. T hus, it becomes possible to learn the M CS characteristics accurately, such as the area of the shield, long axis, shape,
distribution and dayvary of lifecycle, etc. At the same time, the new method brings the chance to learn theclimatology and distribution of MCS. New method is applied for different kinds of satellite data, such as GM S, FY
and GOES, etc. The framework of the new method is however illustrated by the example of GMS. By the new method, MCS profile is from the contour coding, and then the profile features are further computed in the paper.
The system?lookup means is used to track the MCS system. After that, whether the system be M CS or not is objectively judged according to the MCS definition. T rough the census of the year 1999, the new method is found to
work very well in MCS census. Areragely, error occurs 0 191 and 0 ? 101 times per and MCS system, respectively. But, some exiguous problems still exist in the new method, which should be solved in the furtherstudy.

束宇** , 潘益农 . 红外云图上中尺度对流系统的自动识别*

[J]. 南京大学学报(自然科学版), 2010, 46(3): 337–348.

Shu Yu, Pan Yi Nong . Self?identification of mesoscale convective system from satellite infrared imagery

[J]. Journal of Nanjing University(Natural Sciences), 2010, 46(3): 337–348.

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