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Thunderstorm Feature Dataset and Characteristics of Thunderstorm Activities in China
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摘要: 基于FY-2E气象卫星相当黑体亮度温度（TBB）和云分类数据（CLC）及全球闪电探测网（WWLLN）闪电数据，通过对TBB不超过-32℃的云区进行椭圆拟合，定义1 h内上述云区或椭圆区域有WWLLN闪电发生的个例为雷暴云，获得雷暴云时间、位置、形态、结构、闪电活动等特征参量，构建雷暴云特征数据集，并基于该数据集初步分析了我国陆地和毗邻海域的雷暴活动特征。研究表明：我国华南、西南、青藏高原东、中部和南海雷暴最为活跃，华北和东北地区是北方雷暴活动较强的区域。雷暴活动时间变化海陆差异明显，陆地雷暴活动峰值出现在6—8月，南海雷暴活动一个峰值出现在5月左右，另一峰值出现在8月后，且纬度越低出现越晚。陆地大部分地区雷暴活动在14：00—20：00（北京时）达到峰值，毗邻海域雷暴活动峰值主要出现在早上。雷暴云TBB不超过-32℃面积符合对数正态分布，峰值区间位于1×103~1×104 km2，平均值为3.0×104 km2。南海雷暴云面积最大，陆地上大于雷暴云面积平均值1.2×105 km2的区域主要分布于我国地形的第一阶梯和柴达木盆地。Abstract: A thunderstorm feature dataset (TFD) is built up based on the black body temperature (TBB) product and cloud classification (CLC) product of FY-2E meteorological satellite as well as the lightning data of the World-Wide Lightning Location Network (WWLLN). In the TFD, thunderstorm cloud is determined when there is WWLLN lightning in the area with TBB not higher than -32℃ or its fitted ellipse. The characteristic parameters of thunderstorms including time, location, morphology, structure, and lightning activities are obtained to establish the TFD. Based on the dataset, thunderstorms in the land of China and the adjacent seas are analyzed after the quality control.The results show that South China, Southwest China, Eastern and Central of Tibetan Plateau and South China Sea are the areas with most frequent thunderstorm activities. North China and Northeast China are two areas with relatively frequent thunderstorm activities in the north part of China. Meanwhile, thunderstorm activity is the weakest in Northwest China.The seasonal variation of thunderstorm activity shows obvious differences between land and sea. The active stage of thunderstorms on land is from June to August. In high latitudes, the peak appears earlier. There is a peak of thunderstorm activity in the South China Sea around May, and another peak after August. The lower the latitude is, the later the second peak appears. The peak time of thunderstorm activity in diurnal variation in most parts of the land is from 1400 BT to 2000 BT and the peak of thunderstorm activity in adjacent sea areas mainly occurs in the morning. In the Sichuan Basin, thunderstorms are more frequent in the early morning. The diurnal variation of thunderstorm activity in the South China Sea is relatively weak.The area of thunderstorm cloud with TBB not higher than -32℃ follows a log-normal distribution, with the peak interval being 1×103-1×104 km2, and the average area is 3.0×104 km2. The area of thunderstorm cloud over the sea is obviously larger than that of land, and the South China Sea has the largest area of thunderstorm clouds. On the land, the area of thunderstorm clouds in the east is larger than that in the west, and the average area of thunderstorm clouds greater than 1.2×105 km2 can be predominantly found in the first step of Chinese topography. Meanwhile, there is a local center with an average area of thunderstorm clouds greater than 1.2×105 km2 in the Qaidam Basin.
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图 1 雷暴云区域识别示意图
(红线包围区域为TBB不超过-32℃的区域，蓝线表示针对上述区域的拟合椭圆，黄色*为叠加的1 h内WWLLN闪电；红色和蓝色实线表示雷暴云，红色和蓝色虚线表示非雷暴云)
Fig. 1 Schematic diagram of thunderstorm cloud area identification
(red lines enclose the areas with TBB not higher than-32℃, blue lines represent the fitted ellipses for these areas, and the yellow * marks superimposed one-hour WWLLN lightning flash;red and blue solid lines represent thunderstorms, and red and blue dashed lines represent non-thunderstorms)
图 2 2010—2018年不同闪电频次(F)和雷暴云面积(A)区间的样本量分布
Fig. 2 Sample number in lightning frequency(F) and thunderstorm cloud area(A)
图 4 1961—2014年中国陆地年平均雷暴日数
Fig. 4 Annual thunderstorm days in land area of China during 1961-2014
图 5 2010—2018年30°~32°N范围内和112°~114°E范围内雷暴小时数的逐旬占比
Fig. 5 Proportion of ten-day thunderstorm-hour along 30°-32°N and 112°-114°E during 2010-2018
图 7 2010—2018年30°~32°N范围内和12°~114°E范围内雷暴小时数的逐时占比
Fig. 7 Proportion of thunderstorm-hour along 30°-32°N and 112°-114°E during 2010-2018
图 8 2010—2018年5—9月研究区域内雷暴云面积(A)的概率和累积概率分布
Fig. 8 Probability and cumulative probability distributions of thunderstorm cloud area(A) in the study area from May to Sep during 2010-2018
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