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Optimal Evolutionary Window for the Nonlinear Local Lyapunov Exponent

机译:非线性局部Lyapunov指数的最优进化窗

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The impact of the length of the evolutionary window (EW) on the estimation of the predictability limit of the Lorenz-63 model using the nonlinear local Lyapunov exponent (NLLE) method is studied. The structure of the initial errors and error growth dynamics are analyzed. It is found that there exists an optimal EW, at which the estimated predictability limit is closest to its theoretical value. With a shorter EW, the predictability limit is underestimated, while at longer EWs it is overestimated. The optimal EW is approximately equal to the decorrelation time of the system. A preliminary explanation for this link, based on the loss of information from the initial state, is given.
机译:研究了使用非线性局部Lyapunov指数(NLLE)方法的演化窗口(EW)长度对Lorenz-63模型的可预测性限制的估计的影响。分析了初始误差的结构和误差的增长动态。发现存在一个最佳电子战,估计的可预测性极限最接近其理论值。 EW越短,可预测性极限就被低估,而EW越长,其可预测性极限就被高估。最佳EW大约等于系统的去相关时间。基于从初始状态丢失的信息,对此链接进行了初步说明。

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