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河北春季一次飞机人工增雪的综合分析 总被引：1，自引：0，他引：1
2013年4月19日,河北省人工影响天气办公室在河北中南部地区根据云系特点首次采用多层次水平催化和垂直验证的方式对层状云进行人工催化和探测。本文利用机载仪器所取得的飞机探测资料,结合实时天气、卫星、雷达、探空和雨量观测资料,分析了河北春季层状云增雪作业的技术指标,探讨了航测微物理参量和卫星、雷达、探空等资料在作业中的应用。结果表明：云在发展期雷达回波由15 dBZ逐步上升到25-35 dBZ,卫星反演的云顶高度、云顶温度、有效粒子半径、光学厚度等都有增加;云在中后期有效粒子半径、光学厚度、液水路径迅速下降,雷达回波同时减弱。在高度3 177-5 723 m之间过冷云滴达100-700个/cm^3,含水量在0.01 g·m^-3左右,最大0.081 g·m^-3,云粒子主要在此增长,形成降水粒子,该区间适宜催化。作业后,影响区内云体发展,雷达回波增强,出现35 dBZ强回波,且强回波中心扩大;卫星反演的云顶高度、光学厚度等比对比区有明显增加。 相似文献
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In this article, the Multi-Fractal Detrended Fluctuation Analysis (MF-DFA) method is adopted to study the temperature, i. e., the maximum temperature (Tmax), mean temperature (Tavg) and minimum (Tmin) air temperature, multifractal characteristics and their formation mechanism, in the typical temperature zones in the coastal regions in Guangdong, Jiangsu and Liaoning Provinces. Following are some terms and concepts used in the present study. Multifractality is defined as a term that characterizes the complexity and self-similarity of objects, and fractal characteristics depict the distribution of probability over the whole set caused by different local conditions or different levels in the process of evolution. Fractality strength denotes the fluctuation range of the data set, and long-range correlation (LRC) measures the stability of the climate system and the trend of climate change in the future. In this research, it is found that the internal stability and feedback mechanism of climate systems in different regions show regional differences. Furthermore, the research also proves that the Tavg, Tmax and Tmin of the above three provinces are highly multifractal. The temperature series multifractality of each province decreases in the order of temperature series multifractality of Liaoning > temperature series multifractality of Guangdong > temperature series multifractality of Jiangsu, and the corresponding long-range correlations follow the same order. It reveals that the most stable temperature series is that of Liaoning, followed by the temperature series of Guangdong, and the most unstable one is that of Jiangsu. Liaoning has the most stable climate system, and it will thus be less responsive to the future climate warming. The stability of the climate system in Jiangsu is the weakest, and its temperature fluctuation will continue to increase in the future, which will probably result in the meteorological disasters of high temperature and heat wave there. Guangdong possesses the strongest degree of multifractal strength, which indicates that its internal temperature series fluctuation is the largest among the three regions. The Tmax multifractal strength of Jiangsu is stronger than that of Liaoning, while the Tavg and Tmin multifractal strength of Jiangsu is weaker than that of Liaoning, showing that Jiangsu has a larger internal Tmax fluctuation than Liaoning does, while it has a smaller fluctuation of Tavg and Tmin than Liaoning does. Guangdong and Liaoning both show the strongest Tmin multifractal strength, followed by Tavg multifractal strength, and the weakest Tmax multifractal strength. However, Jiangsu has the strongest Tmax, followed by Tavg, and the weakest Tmin. The research findings show that these phenomena are closely related to solar radiation, monsoon strength, topography and some other factors. In addition, the multifractality of the temperature time series results from the negative power-law distribution and long-range correlation, in which the long-range correlation influence of temperature series itself plays the dominant role. With the backdrop of global climate change, this research can provide a theoretical basis for the prediction of the spatial-temporal air temperature variation in the eastern coastal areas of China and help us understand its characteristics and causes, and thus the present study will be significant for the environmental protection of coastal areas. 相似文献
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