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1.
混沌系统的局域特征与可预报性 总被引：1，自引：0，他引：1
讨论了混沌系统的时间和空间的局域特征。首先分析了研究时间和空间局域特征的必要性。接着引进了有限时间不稳定和局域时间不稳定的概念，并对有关的计算问题进行了研究。对Ｌｏｒｅｎｚ系统的具体计算表明，随着轨线在混沌吸引子上的演变，局域不稳定特征有很大的变化，相应误差增长也有很大的变化。相应于误差迅速增长的轨线部分局限于很有限的相空间范围内，而且同误差增长缓慢的轨线部分占据的相空间区域截然可分。每一个例的可预报性依赖于轨线在相空间中所处的区域。混沌系统的这种局域特征可以是导致个例业务预报技巧之间有很大差别的主要原因。 相似文献
2.
误差非线性的增长理论及可预报性研究 总被引：2，自引：9，他引：2
对非线性系统的误差发展方程不作线性化近似，直接用原始的误差发展方程来研究初始误差的发展，提出了误差非线性的增长理论。首先，在相空间中定义一个非线性误差传播算子，初始误差在这个算子的作用下，可以非线性发展成任意时刻的误差；然后，在此基础上，引入了非线性局部Lyapunov指数的概念。由平均非线性局部Lyapunov指数可以得到误差平均相对增长随时间的演变情况；对于一个混沌系统，误差平均相对增长被证明将趋于一个饱和值，利用这个饱和值，混沌系统的可预报期限可以被定量地确定。误差非线性的增长理论可以应用于有限尺度大小初始扰动的可预报性研究，较误差的线性增长理论有明显的优越性。 相似文献
3.
Extended range(10–30 d) heavy rain forecasting is difficult but performs an important function in disaster prevention and mitigation. In this paper,a nonlinear cross prediction error(NCPE) algorithm that combines nonlinear dynamics and statistical methods is proposed. The method is based on phase space reconstruction of chaotic single-variable time series of precipitable water and is tested in 100 global cases of heavy rain. First,nonlinear relative dynamic error for local attractor pairs is calculated at different stages of the heavy rain process,after which the local change characteristics of the attractors are analyzed. Second,the eigen-peak is defined as a prediction indicator based on an error threshold of about 1.5,and is then used to analyze the forecasting validity period. The results reveal that the prediction indicator features regarded as eigenpeaks for heavy rain extreme weather are all reflected consistently,without failure,based on the NCPE model; the prediction validity periods for 1–2 d,3–9 d and 10–30 d are 4,22 and 74 cases,respectively,without false alarm or omission. The NCPE model developed allows accurate forecasting of heavy rain over an extended range of 10–30 d and has the potential to be used to explore the mechanisms involved in the development of heavy rain according to a segmentation scale. This novel method provides new insights into extended range forecasting and atmospheric predictability,and also allows the creation of multi-variable chaotic extreme weather prediction models based on high spatiotemporal resolution data. 相似文献
4.
For an n-dimensional chaotic system, we extend the definition of the nonlinear local Lyapunov exponent(NLLE) from one-to n-dimensional spectra, and present a method for computing the NLLE spectrum. The method is tested on three chaotic systems with different complexity. The results indicate that the NLLE spectrum realistically characterizes the growth rates of initial error vectors along different directions from the linear to nonlinear phases of error growth. This represents an improvement over the traditional Lyapunov exponent spectrum, which only characterizes the error growth rates during the linear phase of error growth. In addition, because the NLLE spectrum can effectively separate the slowly and rapidly growing perturbations, it is shown to be more suitable for estimating the predictability of chaotic systems, as compared to the traditional Lyapunov exponent spectrum. 相似文献
5.
The purpose of this paper is to study the dynamical mechanism of error growth in the numerical weather prediction.The error is defined in the sense of generalized energy,simply called energy error.From the spectral form of the primitive equations,we have derived the evolution equations of error in detail.The analyses of these equations have shown that the error growth rate is determined by the tangent linear equations.The nonlinear advection caused by the error perturbation itself contributes nothing to the error growth rate,and only redistributes the error.Furthermore,an approach to calculation of the error growth rate has been developed,which can also be used to study the local instability of time-independent basic state as well as time-dependence basic state.This approach is applied to well-known Lorenz's system,and the results are indicative of the correctness and significance of the theoretical analyses. 相似文献
6.
混沌系统单变量可预报性研究 总被引：5，自引：4，他引：1
对于n维的混沌系统, 不同变量的可预报性是不同的。为了研究混沌系统中单个变量的可预报性, 本文在以前提出的混沌系统整体的非线性局部Lyapunov指数基础上(李建平等, 2006), 引入了单变量的非线性局部Lyapunov指数及其相关统计量, 进一步完善了非线性误差增长理论。通过应用到几个混沌个例, 结果表明单变量的非线性局部Lyapunov指数及其相关统计量可以用来定量地研究多维混沌系统中不同变量的可预报性, 系统不同变量的可预报性之间不是相互独立的, 而是单个变量的可预报期限与系统整体的可预报期限之比都近似保持一个常数, 但各个变量的常数值有所不同。 相似文献
7.
根据非线性局部Lyapunov指数的方法, 以Logistic映射和Lorenz系统的试验数据序列为例, 研究了在初始误差存在的情况下, 随机误差对混沌系统可预报性的影响。结果表明: 初始误差和随机误差对可预报期限影响所起的作用大小主要取决于两者的相对大小。当初始误差远大于随机误差时, 系统的可预报期限主要由初始误差决定, 可以不考虑随机误差对预报模式可预报性的影响; 反之, 当随机误差远大于初始误差时, 系统的可预报期限主要由随机误差决定; 当初始误差和随机误差量级相当时, 两者都对系统的可预报期限起重要作用。在后两种情况下, 在考虑初始误差对可预报性影响的同时还必须考虑随机误差的作用。此外, 我们在已知系统精确的控制方程和误差演化方程的条件下, 研究了随机误差对可预报性的影响, 理论所得结果与试验数据所得结果相似。这表明在随机误差较小的情况下, 对系统可预报期限的估计相对准确, 但在随机误差较大的情况下, 可预报期限的估计误差也较大。本文利用三种不同的滤波方法对序列进行了试验, 结果表明, Lanczos高通滤波得到的高频序列与原始加入的噪声序列无论是在强度上还是在演变趋势上都表现得相当一致, 其能有效地去除高频噪音继而提高对系统的可预报期限的估计, 这对实际气象观测资料如何有效地去除噪音具有一定的启发意义。 相似文献
8.
In this work, two types of predictability are proposed—forward and backward predictability—and then applied in the nonlinear local Lyapunov exponent approach to the Lorenz63 and Lorenz96 models to quantitatively estimate the local forward and backward predictability limits of states in phase space. The forward predictability mainly focuses on the forward evolution of initial errors superposed on the initial state over time, while the backward predictability is mainly concerned with when the given state can be predicted before this state happens. From the results, there is a negative correlation between the local forward and backward predictability limits. That is, the forward predictability limits are higher when the backward predictability limits are lower, and vice versa. We also find that the sum of forward and backward predictability limits of each state tends to fluctuate around the average value of sums of the forward and backward predictability limits of sufficient states.Furthermore, the average value is constant when the states are sufficient. For different chaotic systems, the average value is dependent on the chaotic systems and more complex chaotic systems get a lower average value. For a single chaotic system,the average value depends on the magnitude of initial perturbations. The average values decrease as the magnitudes of initial perturbations increase. 相似文献
9.
Newtonian jerky dynamics is applied to inertial instability analysis to study the nonlinear features of atmospheric motion under the action of variable forces. Theoretical analysis of the Newtonian jerky function is used to clarify the criteria for inertial instability, including the influences of the meridional distributions of absolute vorticity (ζg ) and planetary vorticity (the β effect). The results indicate that the meridional structure of absolute vorticity plays a fundamental role in the dynamic features of inertial motion. Including only the β effect (with the assumption of constant ζg ) does not change the instability criteria or the dynamic features of the flow, but combining the β effect with meridional variations of ζg introduces nonlinearities that significantly influence the instability criteria. Numerical analysis is used to derive time series of position, velocity, and acceleration under different sets of parameters, as well as their trajectories in phase space. The time evolution of kinematic variables indicates that a regular wave-like change in acceleration corresponds to steady wave-like variations in position and velocity, while a rapid growth in acceleration (caused by a rapid intensification in the force acting on the parcel) corresponds to track shifts and abrupt changes in direction. Stable limiting cases under the f-and β-plane approximations yield periodic wave-like solutions, while unstable limiting cases yield exponential growth in all variables. Perturbing the value of absolute vorticity at the initial position (ζ0 ) results in significant changes in the stability and dynamic features of the motion. Enhancement of the nonlinear term may cause chaotic behavior to emerge, suggesting a limit to the predictability of inertial motion. 相似文献
10.
Michael Zulauf John E. Hart Robert Leben Michael Mundt 《Dynamics of Atmospheres and Oceans》1996,25(2):87-107
This paper investigates the dynamics of mesoscale eddy generation by instability of time-varying flows. Laboratory experiments on oscillatory motion over topography in a rapidly rotating cylinder have shown that isolated mesoscale eddies, which form in the sidewall boundary layer during certain phases of the forcing cycle, are associated with the onset of chaotic behavior in this system. This paper explores the origin of these eddies by performing computational simulations of the flow, and then interpreting the results of the calculations using spatially localized and quasi-static linear stability theory. For most of the experimental parameter space the quasi-geostrophic simulations are in excellent agreement with the laboratory observations. The eddies arise as a barotropic shear flow instability in regions of space and at times where the inflection points of the instantaneous large-scale flow are farthest from the sidewall, and where Fjortoft's theorem is strongly satisfied. At finite amplitude, advection of the local wavetrains up the bottom slope strengthens the anticyclonic eddies. These then merge, leading in most circumstances to a single strong anticyclonic vortex that can leave the sidewall and penetrate the interior. When parameters are such that the eddy persists all the way around the basin and back to the local instability region, the flow is observed to become chaotic. 相似文献
11.
用天气变量时间序列估计天气的可预报性 总被引：8，自引：0，他引：8
本文从非线性系统的吸引子概念出发,用单个气象时间序列重构维数较高的相空间并嵌入天气吸引子,根据相轨道上初始时刻紧邻的点随时间的演化来估计吸引子的维数和天气的可预报性。用500hPa亚洲环流指数和北京冬季气温的逐日资料计算表明,天气吸引子的维数分别为3.8和5.4;可预报时间尺度约6—14天,考虑相空间e指数膨胀因素后为4—9天。 相似文献
12.
非线性误差增长理论在大气可预报性中的应用 总被引：10，自引：1，他引：9
为了能从非线性误差增长动力学的角度来研究大气的可预报性问题,在非线性动力系统的理论和方法基础上,文中引入了可预报性研究的新方法--非线性局部Lyapunov指数.非线性局部Lyapunov指数及其相关统计量能够用来定量地确定混沌系统可预报性的大小,真正地实现了对可预报性的定量化研究.首先给出了利用大气单个变量的实际观测资料获得其可预报期限估计的计算方法,因而解决了将非线性误差增长理论应用到大气实际的可预报性研究中的问题.然后,以位势高度场为例,详细讨论了逐日时间尺度上全球可预报性的时空分布,得到的主要结论为:(1)在水平方向上,全球位势高度场可预报性表现为一定的南北纬向带状分布,赤道地区和南极地区的可预报期限最长,可以达到两周左右;北极地区次之,可预报期限大约为9-12 d;北半球中高纬度地区可预报期限相对较短,可预报期限大约为6-9 d;而在南半球的中纬度地区最短,可预报期限仅为4-6 d.此外,500 hPa位势高度场可预报性分市随季节有明显变化,季节不同一些可预报期限的高值区和低值区所在的纬度和经度也会不同,总体来说,全球大部分地区的可预报性冬季都大于夏季,尤其在南极地区、热带印度洋以及北太平洋地区.(2)在垂直方向上,位势高度场可预报期限随高度升商而增加,可预报期限从对流层下层的两周以下增加到平流层下层的1个月左右,对流层和平流层天气尺度运动的可预报期限与其时间尺度是十分一致的. 相似文献
13.
从一般的谱展开方程出发，详细推导了误差增长方程。结果表明误差增长率主要由准确解的切线性方程所决定，扰动非线性平流作用不产生方差意义下的误差增长，而只起分配误差的作用。轨线不稳定是产生误差增长的根本原因。文中提出了计算轨线不稳定增长率的方法。这一方法也适合于时间演变状态不稳定问题的讨论，对Ｌｏｒｅｎｚ系统的轨线不稳定计算表明了理论分析的正确及其意义。 相似文献
14.
Sensitivity simulations are conducted in AREM (Advanced Regional Eta-Coordinate numerical heavy-rain prediction Model) for a torrential precipitation in June 2008 along South China to investigate the effect of initial uncertainty on precipitation predictability. It is found that the strong initial-condition sensitivity for precipitation prediction can be attributed to the upscale evolution of error growth. However, different modality of error growth can be observed in lower and upper layers. Compared with lower-level, significant error growth in the upper-layer appears over both convective area and high jet stream. It thus indicates that the error growth depends on both moist convection due to convective instability and the wind shear associated with dynamic instability. As heavy rainfall process can be described as a series of energy conversion, it reveals that the advection-term and latent heating serve as significant energy sources. Moreover, the dominant source terms of error-energy growth are nonlinearity advection (ADVT) and difference in latent heating (DLHT), with the latter being largely responsible for the rapid error growth in the initial stage. In this sense, the occurrence of precipitation and error-growth share the energy source, which implies the inherent predictability of heavy rainfall. In addition, a decomposition of ADVT further indicates that the flow-dependent error growth is closely related to the atmospheric instability. Thus the system growing from unstable flow regime has its intrinsic predictability. 相似文献
15.
Initial condition and model errors both contribute to the loss of atmospheric predictability. However, it remains debatable which type of error has the larger impact on the prediction lead time of specific states. In this study, we perform a theoretical study to investigate the relative effects of initial condition and model errors on local prediction lead time of given states in the Lorenz model. Using the backward nonlinear local Lyapunov exponent method, the prediction lead time,also called local backward predictability limit(LBPL), of given states induced by the two types of errors can be quantitatively estimated. Results show that the structure of the Lorenz attractor leads to a layered distribution of LBPLs of states. On an individual circular orbit, the LBPLs are roughly the same, whereas they are different on different orbits. The spatial distributions of LBPLs show that the relative effects of initial condition and model errors on local backward predictability depend on the locations of given states on the dynamical trajectory and the error magnitudes. When the error magnitude is fixed, the differences between the LBPLs vary with the locations of given states. The larger differences are mainly located on the inner trajectories of regimes. When the error magnitudes are different, the dissimilarities in LBPLs are diverse for the same given state. 相似文献
16.
J. R. Kulkarni 《大气科学进展》1991,8(3):351-356
For summer monsoon rainfall purpose India is divided into 35 subdivisions. The daily rainfall series of one such subdivision (Konkan) has been analysed using the phase space approach. Fifteen years (1959-1973) of daily rainfall data have been utilised in this study. The analysis shows that the variability is due to the existing of strange attractor of dimension about 3.8. The predictability is estimated by computing the Lyapunov characteristic exponent. The computations show that the predictability is about 8 days. 相似文献
17.
A Case Study of the Error Growth and Predictability of a Meiyu Frontal Heavy Precipitation Event 
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下载免费PDF全文 The Advanced Regional Eta-coordinate Model (AREM) is used to explore the predictability of a heavy rainfall event along the Meiyu front in China during 3-4 July 2003.Based on the sensitivity of precipitation prediction to initial data sources and initial uncertainties in different variables,the evolution of error growth and the associated mechanism are described and discussed in detail in this paper.The results indicate that the smaller-amplitude initial error presents a faster growth rate and its growth is characterized by a transition from localized growth to widespread expansion error.Such modality of the error growth is closely related to the evolvement of the precipitation episode,and consequcntly remarkable forecast divergence is found near the rainband,indicating that the rainfall area is a sensitive region for error growth.The initial error in the rainband contributes significantly to the forecast divergence,and its amplification and propagation are largely determined by the initial moisture distribution.The moisture condition also affects the error growth on smaller scales and the subsequent upscale error cascade.In addition,the error growth defined by an energy norm reveals that large error energy collocates well with the strong latent heating,implying that the occurrence of precipitation and error growth share the same energy source-the latent heat.This may impose an intrinsic predictability limit on the prediction of heavy precipitation. 相似文献
18.
A case study of the error growth and predictability of a Meiyu frontal heavy precipitation event 下载免费PDF全文
下载免费PDF全文 The Advanced Regional Eta-coordinate Model (AREM) is used to explore the predictability of a heavy rainfall event along the Meiyu front in China during 3-4 July 2003. Based on the sensitivity of precipitation prediction to initial data sources and initial uncertainties in different variables, the evolution of error growth and the associated mechanism are described and discussed in detail in this paper. The results indicate that the smaller-amplitude initial error presents a faster growth rate and its growth... 相似文献
19.
In this study, the relationship between the limit of predictability and initial error was investigated using two simple chaotic systems:the Lorenz model, which possesses a single characteristic time scale, and the coupled Lorenz model, which possesses two different characteristic time scales. The limit of predictability is defined here as the time at which the error reaches 95% of its saturation level; nonlinear behaviors of the error growth are therefore involved in the definition of the limit of predictability. Our results show that the logarithmic function performs well in describing the relationship between the limit of predictability and initial error in both models, although the coefficients in the logarithmic function were not constant across the examined range of initial errors. Compared with the Lorenz model, in the coupled Lorenz model-in which the slow dynamics and the fast dynamics interact with each other-there is a more complex relationship between the limit of predictability and initial error. The limit of predictability of the Lorenz model is unbounded as the initial error becomes infinitesimally small; therefore, the limit of predictability of the Lorenz model may be extended by reducing the amplitude of the initial error. In contrast, if there exists a fixed initial error in the fast dynamics of the coupled Lorenz model, the slow dynamics has an intrinsic finite limit of predictability that cannot be extended by reducing the amplitude of the initial error in the slow dynamics, and vice versa. The findings reported here reveal the possible existence of an intrinsic finite limit of predictability in a coupled system that possesses many scales of time or motion. 相似文献
20.
Climate predictability on interannual to decadal time scales: the initial value problem 总被引：1，自引：1，他引：0
M. Collins 《Climate Dynamics》2002,19(8):671-692
Any initial value forecast of climate will be subject to errors originating from poorly known initial conditions, model imperfections, and by "chaos" in the sense that, even if the initial conditions were perfectly known, infinitesimal errors can amplify and spoil the forecast at some lead time. Here the latter source of error is examined using a "perfect model" approach whereby small perturbations are made to a coupled atmosphere-ocean general circulation model and the spread of nearby model trajectories, on time and space scales appropriate to seasonal-decadal climate variability, is measured to assess the lead time at which the error saturates. The study therefore represents an estimate of the upper limit of the predictability of climate (appropriate to the initial value problem) given a perfect model and near perfect knowledge of the initial conditions. It is found that, on average, surface air temperature anomalies are potentially predictable on seasonal to interannual time scales in the tropical regions and are potentially predictable on decadal time scales over the ocean in the North Atlantic. For mid-latitude surface air temperature anomalies over land, model trajectories rapidly diverge and there is little sign of any potential predictability on time scales greater than a season or so. For mean sea level pressure anomalies, there is potential predictability on seasonal time scales in the tropics, and for some global scale annual-decadal anomalies, although not those associated with the North Atlantic Oscillation. For precipitation, the only potential for predictability is for seasonal time anomalies associated with the El-Niño Southern Oscillation. For the majority of the highly populated regions of the world, climate predictability on interannual to decadal time scales based in the initial value approach is likely to be severely limited by chaotic error growth. It is found however that there can be cases in which the potential predictability can be higher than average indicating that there is perhaps some utility in making initial value forecasts of climate in those regions which show low predictability on average. 相似文献