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符号动力学和信息熵在暴雨监测中的应用研究

     

摘要

Rainstorms is the main disaster in the world and lead huge losses of national economy and people’s life and property every year, but the prediction of rainstorms is very difficult. The basic reason is that we are unclear to the sudden change of atmospheric circulation and the occurrence and development mechanism of severe convective weather;include the inner dynamic mechanism and the physical interaction process of it with the external atmospheric circulation and the abnormal change mechanism of various weather system in tropical and middle latitude zone. Especially, the research on multi-scale interaction is lack. Atmospheric system is a deterministic nonlinear system if a few random factors are ignored. Symbolic dynamic which have gradually become a tool of practitioners is a branch of nonlinear science and has a strong theoretical foundation. Entropy is a basic physical quantity and it is apply widely in nonlinear science, statistical mechanics, and optimum signal processing, and so on. Using symbolic dynamics to explore storm event has some certain significance, the entropy curves of a large number of heavy rain are analyzed and the entropy has reached its minimum ten days before most of the heavy rainfall in the storm. So it is valuable in monitoring and forecasting heavy rain events.%暴雨是世界上最主要的灾害之一,每年都会给国民经济和人民的生命财产造成巨大的损失。但是,暴雨预报是非常困难的,造成这种情况的根本原因是对大气环流短时间的突变和强对流天气系统发生、发展的机理了解得非常少。这其中包括对大气内部的动力机制及其与外部环流之间相互作用的物理过程和热带、中纬度的各种天气系统异常变化的机理,特别是对多尺度相互作用的研究还非常浅显。假如忽略一些随机因素的影响,大气系统可以被认为是一个确定性的非线性系统。符号动力学是非线性科学的一个分支,有着深厚的理论基础,它已慢慢成为实际工作中所要掌握的工具之一。信息熵是信息论中最重要的物理量之一,它把非线性科学与统计学结合起来,已经成为了一种分析非线性问题的重要工具。利用符号动力学和信息熵对暴雨过程进行研究具有一定的探索意义,通过分析大量暴雨过程的熵曲线,发现大部分暴雨过程在发生前10 d内,其熵值达到了极小值。这一征兆的发现表明,该方法在对暴雨事件进行监测和预报方面具有一定的研究价值。

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