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On temporal evolution of precipitation probability of the Yangtze River delta in the last 50 years

机译:近50年长江三角洲降水概率的时间演变

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The monthly precipitation observational data of the Yangtze River delta are transformed into the temporal evolution of precipitation probability (PP) and its hierarchically distributive characters have been revealed in this paper. Research results show that precipitation of the Yangtze River delta displays the interannual and interdecadal characters and the periods are all significant at a confidence level of more than 0.05. The interdecadal is an important time scale, because it is on the one hand a disturbance of long period changes and on the other hand it is also the background for interannual change. The interdecadal and 3-7y oscillations have different motion laws in the data-based mechanism self-memory model (DAMSM). Meanwhile, this paper also provides a new train of thought for dynamic modelling. Because this method only involves a certain length of data series, it can be used in many fields, such as meteorology, hydrology, seismology and economy etc and thus has a bright perspective in practical applications.
机译:将长江三角洲的月度降水观测数据转换为降水概率的时间演变,揭示了其分层分布特征。研究结果表明,长江三角洲地区的降水表现出年际和年代际特征,且周期均在0.05以上的置信水平下具有显着性。年代际是一个重要的时间尺度,因为它一方面是长期变化的干扰,另一方面也是年际变化的背景。在基于数据的机构自记忆模型(DAMSM)中,年代际和3-7y振荡具有不同的运动规律。同时,本文也为动态建模提供了新的思路。由于该方法仅涉及一定长度的数据序列,因此可用于气象,水文,地震和经济等许多领域,在实际应用中具有广阔的前景。

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