首页> 外文期刊>Quarterly Journal of the Royal Meteorological Society >A climatology of mesoscale convective systems over Europe using satellite infrared imagery. I: methodology
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A climatology of mesoscale convective systems over Europe using satellite infrared imagery. I: methodology

机译:使用卫星红外图像对欧洲中尺度对流系统进行的气候学研究。一:方法论

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摘要

An automated method aimed at producing a significant European mesoscale convective system (MCS) climatology is presented. It uses Meteosat infrared window channel images and is composed of two main tools: an automated cloud-shield tracking method and a robust method of discriminating between convective and non-convective cloud shields. The automated cloud-tracking method defines cloud systems as connected sets of pixels, named 'cells', after temperature and area thresholding and it is based on theoverlapping between cells in successive images. It handles splits and merges of cells and takes cell movement into account. It has three parameters: the temperature and area thresholds and a minimum overlapping threshold. It is concluded that it performsa correct tracking at any temperature threshold between -30 deg C and -55 deg C and for an area threshold greater than 1000 km~2, so that it allows the tracking of MCSs during most of their life cycle. The automated discrimination between convective andnon-convective cloud shields uses a discrimination parameter based on brightness-temperature gradients on the edges of cells, because strong values of this gradient are observed at the beginning of the life cycle of MCSs when cold anvils develop. A seasonal study, and the sensitivity of the method to the temperature threshold, are presented. The method shows significant quality during the entire warm season (from April to September): it correctly discriminates 80 percent of MCSs and more than 90 percent of the most electrically active ones, while showing a low false-alarm rate around 8 percent; therefore the method seems to be useful for climatological purposes.
机译:提出了一种旨在产生重要的欧洲中尺度对流系统(MCS)气候学的自动化方法。它使用Meteosat红外窗口通道图像,并且由两个主要工具组成:自动云屏蔽跟踪方法和区分对流和非对流云屏蔽的可靠方法。自动云跟踪方法将云系统定义为经过温度和面积阈值处理后的连接像素集,称为“单元”,它基于连续图像中单元之间的重叠。它处理单元格的拆分和合并,并考虑单元格移动。它具有三个参数:温度和面积阈值以及最小重叠阈值。结论是,它可以在-30摄氏度到-55摄氏度之间的任何温度阈值以及大于1000 km〜2的面积阈值下执行正确的跟踪,从而可以跟踪MCS的大部分生命周期。对流云罩和非对流云罩之间的自动判别使用基于细胞边缘上的亮度-温度梯度的判别参数,因为当冷砧发展时,在MCS的生命周期开始时会观察到该梯度的强值。介绍了季节性研究以及该方法对温度阈值的敏感性。该方法在整个温暖季节(从四月到九月)显示出显着的质量:可以正确地区分80%的MCS和90%的最活跃的MCS,而误报率却低至8%。因此该方法似乎对气候学目的是有用的。

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