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Statistical scaling, Shannon entropy, and Generalized space-time q-entropy of rainfall fields in tropical South America

机译:南美洲热带地区降雨场的统计标度,香农熵和广义时空q熵

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摘要

We study diverse scaling and information theory characteristics of Mesoscale Convective Systems (MCSs) as seen by the Tropical Rainfall Measuring Mission (TRMM) over continental and oceanic regions of tropical South America, and 2/D radar rainfall fields from Amazonia. The bi-dimensional Fourier spectra of MCSs exhibit inverse power laws with respect to the spatial scale, whose scaling exponents, beta, capture the type of spatial correlation of rainfall among the study regions, including those over the Andes of Colombia as well as over oceanic and Amazonian regions. The moment-scaling analysis evidences that the structure function deviates from simple scaling at order q > 1.0, thus signaling the multi-scaling nature of rainfall fields within MCSs in tropical South America, with departures from simple scaling associated with the physical characteristics of MCSs over the different study regions. Entropy is estimated for a large set of radar rainfall fields during the distinctive atmospheric regimes (Easterly and Westerly events) in this part of Amazonia. Results evidence that there are significant differences in the dynamics of rainfall among regimes. No clear-cut relationship is found between entropy and the first two statistical moments, but power fits in space and time, S(gamma) similar to gamma(-eta) for skewness and, S(kappa) similar to kappa(-c) for kurtosis. The exponents eta and epsilon are statistically different between Easterly and Westerly events, although the significance of fits is less when L-moments are used to estimate skewness and kurtosis. Interesting differences are identified between the time and space generalized q-entropy functions of Amazonian rainfall fields. In both cases, the functions are a continuous set of power laws (analogous to the structure function in turbulence), S(T, q) similar to T-beta, and, S(lambda, q) similar to lambda(beta), covering a broad range of temporal and spatial scales. Both time and space generalized q-entropy functions exhibit linear growth in the range -1.0 < q < -0.5, and saturation of the exponent beta for q >= 1.0. In the case of the spatial analysis, the exponent saturates at similar to 1. 0, whereas at = 0.5 for the temporal case. Results are similar for time series extracted from the S-POL radar and time series of rainfall in tropical Andes. Additionally, differences in values of for q >= 1.0 between Easterly and Westerly events are not statistically significant. (C) 2015 AIP Publishing LLC.
机译:我们研究了中尺度对流系统(MCS)的各种尺度和信息论特征,如热带雨量测量任务(TRMM)在南美热带地区的大陆和海洋区域以及亚马逊河的2D雷达降雨场中所见。 MCSs的二维傅立叶光谱在空间尺度上表现出反幂定律,其尺度指数β捕获了研究区域(包括哥伦比亚安第斯山脉和大洋洲地区)降雨之间的空间相关性类型。和亚马逊地区。矩尺度分析表明,结构函数在q> 1.0的阶次上偏离了简单尺度,从而表明了南美热带地区MCS内部降雨场的多尺度性质,而与MCS物理特征相关的简单尺度偏离不同的研究区域。在亚马孙地区的独特大气状态(东风和西风事件)期间,估计了大量雷达降雨场的熵。结果表明,各地区的降雨动态存在显着差异。在熵和前两个统计矩之间未发现明确的关系,但是幂适合于空间和时间,S(gamma)类似于gamma(-eta)的偏度,S(kappa)类似于kappa(-c)峰度。尽管使用L矩估计偏度和峰度时,拟合的重要性较小,但在复活节和西风事件之间,指数eta和epsilon在统计上是不同的。在亚马孙降雨场的时间和空间广义q熵函数之间发现了有趣的差异。在这两种情况下,函数都是连续的幂定律集(类似于湍流中的结构函数),类似于T-beta的S(T,q)和类似于lambdaβ的S(lambda,q),涵盖了广泛的时空尺度。时间和空间广义q熵函数均在-1.0 = 1.0的指数beta饱和。在空间分析的情况下,指数在<β>处类似于1. 0饱和,而在时间情况下在<β> = 0.5处饱和。从S-POL雷达提取的时间序列和热带安第斯山脉降雨的时间序列的结果相似。此外,东风事件和西风事件之间的q> = 1.0的值的差异在统计上并不显着。 (C)2015 AIP Publishing LLC。

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