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1.
The breeding method has been widely used to generate ensemble perturbations in ensemble forecasting due to its simple concept and low computational cost. This method produces the fastest growing perturbation modes to catch the growing components in analysis errors. However, the bred vectors(BVs) are evolved on the same dynamical flow, which may increase the dependence of perturbations. In contrast, the nonlinear local Lyapunov vector(NLLV) scheme generates flow-dependent perturbations as in the breeding method, but regularly conducts the Gram–Schmidt reorthonormalization processes on the perturbations. The resulting NLLVs span the fast-growing perturbation subspace efficiently, and thus may grasp more components in analysis errors than the BVs.In this paper, the NLLVs are employed to generate initial ensemble perturbations in a barotropic quasi-geostrophic model.The performances of the ensemble forecasts of the NLLV method are systematically compared to those of the random perturbation(RP) technique, and the BV method, as well as its improved version—the ensemble transform Kalman filter(ETKF)method. The results demonstrate that the RP technique has the worst performance in ensemble forecasts, which indicates the importance of a flow-dependent initialization scheme. The ensemble perturbation subspaces of the NLLV and ETKF methods are preliminarily shown to catch similar components of analysis errors, which exceed that of the BVs. However, the NLLV scheme demonstrates slightly higher ensemble forecast skill than the ETKF scheme. In addition, the NLLV scheme involves a significantly simpler algorithm and less computation time than the ETKF method, and both demonstrate better ensemble forecast skill than the BV scheme. 相似文献
2.
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
3.
集合预报中动态调整的增长模繁殖及其对自由繁殖的改进 总被引：1，自引：0，他引：1
用增长模繁殖（BGM）法产生集合预报初始扰动的过程中，对增长模适时的进行调整是有必要的。介绍了动态调整的方法，利用T63L9全球谱模式，通过数值试验考察了在繁殖过程中采用动态调整时增长模的增长和饱和情况，并与自由繁殖试验作了相应的比较。结果表明:动态调整情况下，各层扰动的增长率可以达到一个比较大的数值；在形态饱和方面，动态调整能在很大程度上克服自由繁殖时低层扰动饱和时间滞后的缺陷；综合考虑，动态调整下扰动饱和时间可比自由繁殖缩短1天以上，且饱和特征更加明显。 相似文献
4.
基于增长模繁殖法的集合预报初始扰动饱和分析 总被引：13，自引：1，他引：12
基于增长模繁殖(BGM)法构造集合预报初始扰动时,繁殖循环中扰动的发展和饱和情况是其关键技术之一.已有的一些研究基本上是以扰动增长率接近某一数值作为繁殖结束的标志.作者认为,初始扰动的饱和不仅仅是扰动增长率的饱和,即繁殖模大小方面的饱和,扰动形态(即误差分布)上的饱和也应当是一个必须考虑的因子.利用T63L9全球谱模式分析了繁殖循环中增长模(扰动)的发展和饱和情况,通过分析扰动大小及形态两方面随繁殖时间的演变,得到以下主要结论:扰动增长模在繁殖3～4天后可呈现明显的饱和特征;不同变量扰动增长模的饱和时间有所差别,同一变量在不同等压面上饱和时间亦不同步;不同的初始模大小也会对扰动饱和过程产生影响. 相似文献
5.
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
6.
Qian ZOU Quanjia ZHONG Jiangyu MAO Ruiqiang DING Deyu LU Jianping LI Xuan LI 《大气科学进展》2023,40(3):501-513
Based on a simple coupled Lorenz model, we investigate how to assess a suitable initial perturbation scheme for ensemble forecasting in a multiscale system involving slow dynamics and fast dynamics. Four initial perturbation approaches are used in the ensemble forecasting experiments: the random perturbation(RP), the bred vector(BV), the ensemble transform Kalman filter(ETKF), and the nonlinear local Lyapunov vector(NLLV) methods. Results show that,regardless of the method used, the ensemble ave... 相似文献
7.
The backward nonlinear local Lyapunov exponent method(BNLLE) is applied to quantify the predictability of warm and cold events in the Lorenz model. Results show that the maximum prediction lead times of warm and cold events present obvious layered structures in phase space. The maximum prediction lead times of each warm(cold) event on individual circles concentric with the distribution of warm(cold) regime events are roughly the same, whereas the maximum prediction lead time of events on other circles are different. Statistical results show that warm events are more predictable than cold events. 相似文献
8.
台风路径集合预报试验 总被引：4，自引：3，他引：1
基于T63L9模式,利用BGM法进行了台风路径的集合预报试验,并对集合预报中的一个关键技术—繁殖长度进行了研究。结果表明:相对于控制预报,利用增长模繁殖法制作的集合预报对台风路径预报的技巧水平有了很大提高。集合预报中采用不同的繁殖长度对台风路径预报效果有一定影响。繁殖长度取2 d和3 d集合预报效果相对于控制预报都有很大提高。繁殖长度取为2 d时,集合离散度较小,取为3 d时较合理,取为4 d时,离散度较大。对台风路径的预报采用集合选择平均后,繁殖2 d和繁殖3 d的集合预报系统的预报效果都优于控制预报。从综合集合预报效果分析,繁殖长度取为3 d更合适。当集合预报中繁殖长度取为3 d时,在预报的前3天,台风路径集合预报误差基本维持在100 km,第4天误差也只接近300 km。相对于控制预报,集合预报的改进率在预报的2～4 d基本超过了60%,甚至可达到70%。 相似文献
9.
Sandipan Mukherjee Peyman Zawar-Reza Andrew Sturman Ashok Kumar Mittal 《Meteorology and Atmospheric Physics》2013,122(3-4):185-197
Nonlinear time series analysis methods are used to investigate the dynamics of mechanical and convective turbulences in the atmospheric surface layer flow. Using dynamical invariant analysis (e.g. correlation dimension, Lyapunov exponent and mutual information) along with recurrence quantification analysis (e.g. recurrent rate, determinism, average diagonal length of recurrence plot, etc.) of the vertical wind component data, it is confirmed that a convective turbulence is a lower order manifold in its phase space exhibiting higher degree of organization than a mechanical turbulence. Applying a quasi-one-dimensional chaotic return map technique, the topological differences between the mechanical and convective turbulences are explored. These quasi-one-dimensional return maps are produced using the local maxima of the first principal component of the reconstructed turbulence data. A comparison of the probability distribution of the local maxima of a forced Lorenz model with the turbulence data indicates the possible existence of a stable fixed point for both type of turbulences. Furthermore, dynamically the mechanical turbulence is found to resemble an unforced Lorenz model whereas the convective turbulence resembles a forced Lorenz model. 相似文献
10.
数值模式初值的敏感性程度对四维同化的影响 总被引：3，自引：0，他引：3
用著名的Ｌｏｒｅｎｚ系统作了共轭变分同化的数值试验。发现随着模式对初值敏感性程度的增加，用这种方法得到和模式相协调的初始场愈来愈困难，直到某些情况下的完全失败。这表明四维同化和可预报期限是联系在一起的。另一方面，随着方程不精确程度的增加，变分同化的效果愈来愈差，直到所做的预报无任何意义可言。如果在做变分同化的同时对模式参数也进行反演，就可使得基于Ｌｏｒｅｎｚ系统所做的预报效果大大提高。 相似文献
11.
利用T63L9全球谱模式和NCEP/NCAR再分析资料, 对BGM方法中增长模的繁殖长度对集合预报效果的影响进行研究。结果表明:与控制预报相比, 不同繁殖长度的集合预报都能使预报效果得到一定程度的改进, 特别是第4天预报以后, 改进程度随预报时效而稳步提高。三组不同繁殖长度的集合预报对控制预报的改进存在差别, 分析结果表明:繁殖长度为2 d的集合预报明显效果最差, 而繁殖3 d和4 d的集合预报差别并不明显。对集合Talagrand分布以及离散度的初步分析表明, 繁殖长度取为3 d似乎最为合理。 相似文献
12.
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
13.
Antonio Algaba Fernando Fernández-Sánchez Manuel Merino Alejandro J. Rodríguez-Luis 《Theoretical and Applied Climatology》2016,126(3-4):797-799
The paper, “Study on the reliable computation time of the numerical model using the sliding temporal correlation method,” was published in Theoretical and Applied Climatology. In that work, the sliding temporal correlation analysis is employed to investigate the predictable time of two typical chaotic numerical models, namely the Lorenz system and the Chen chaotic system. However, it has been recently shown by us when using a linear scaling in time and state variables that generically, the Chen system is only a particular case of the Lorenz system, with time reversion if the parameter c is positive. Consequently, to study the Chen chaotic system is simply to consider the Lorenz system integrated backwards. 相似文献
14.
本文初步探讨了非线性局部Lyapunov指数方法(NLLE)在目标观测中的应用。首先, 在NLLE理论基础上研究了非线性动力系统内局部平均误差相对增长(LAGRE)特征, 证明了在误差发展进入随机状态前, LAGRE与初始误差大小无关而是与初始状态有关;在演化进入随机状态后, LAGRE的饱和值由初始误差大小决定这一特征。同时利用三个变量的常微分方程模型Lorenz63验证了这一结论。其次, 从非线性局部误差增长理论出发, 在局部动力演化相似方法(LDA)的基础上提出向前局部动力演化相似方法(FLDA)的概念, 并通过两个混沌个例来说明LDA和FLDA方法能够有效的利用历史资料还原任意初始状态的LAGRE。这些方法的提出为NLLE理论应用于观测资料研究目标观测问题提供了依据。 相似文献
15.
This paper introduces a new approach for the initialization of ensemble numerical forecasting: Dynamic Analogue Initialization (DAI). DAI assumes that the best model state trajectories for the past provide the initial conditions for the best forecasts in the future. As such, DAI performs the ensemble forecast using the best analogues from a full size ensemble. As a pilot study, the Lorenz63 and Lorenz96 models were used to test DAI’s effectiveness independently. Results showed that DAI can improve the forecast significantly. Especially in lower-dimensional systems, DAI can reduce the forecast RMSE by ～50% compared to the Monte Carlo forecast (MC). This improvement is because DAI is able to recognize the direction of the analysis error through the embedding process and therefore selects those good trajectories with reduced initial error. Meanwhile, a potential improvement of DAI is also proposed, and that is to find the optimal range of embedding time based on the error’s growing speed. 相似文献
16.
An artificial neural network BP model and its revised algorithm are used to approximate quitesuccessfully a Lorenz chaotic dynamic system and the mapping relation is established between theindices of Southern Oscillation and equatorial zonal wind and lagged equatorial eastern Pacific seasurface temperature(SST) in the context of NCEP/NCAR data,and thereby a model is prepared.The constructed net model shows fairly high fit precision and feasible prediction accuracy,thusmaking itself of some usefulness to the prognosis of intricate weather systems. 相似文献
17.
An artificial neural network BP model and its revised algorithm are used to approximate quite successfully a Lorenz chaotic dynamic system and the mapping relation is established between the indices of Southern Oscillation and equatorial zonal wind and lagged equatorial eastern Pacific sea surface temperature(SST) in the context of NCEP/NCAR data,and thereby a model is prepared.The constructed net model shows fairly high fit precision and feasible prediction accuracy,thus making itself of some usefulness to the prognosis of intricate weather systems. 相似文献
18.
The localized features on chaotic attractor in phase space and predictability are investigated in thepresent study.It will be suggested that the localized features in phase space have to be considered indetermining the predictability.The notions of the local instability including the finite-time and local-time instabilities which determine the growth rate of error are introduced,and the calculation methodsare discussed in detail.The results from the calculation of the 3-component Lorenz model show thatsuch instability,correspondingly the growth rate of error,varies dramatically as the trajectoriesevolve on the chaotic attractor.The region in which the growth rate of error is small is localizedconsiderably,and is separable from the region in which the growth rate is large.The localpredictability is of important interest.It is also suggested that such localized features may be the maincause for a great deal of case-to-case variability of the predictive skill in the operational forecasts. 相似文献
19.
The limits of predictability of El Niño and the Southern Oscillation (ENSO) in coupled models are investigated based on retrospective forecasts of sea surface temperature (SST) made with the National Centers for Environmental Prediction (NCEP) coupled forecast system (CFS). The influence of initial uncertainties and model errors associated with coupled ENSO dynamics on forecast error growth are discussed. The total forecast error has maximum values in the equatorial Pacific and its growth is a strong function of season irrespective of lead time. The largest growth of systematic error of SST occurs mainly over the equatorial central and eastern Pacific and near the southeastern coast of the Americas associated with ENSO events. After subtracting the systematic error, the root-mean-square error of the retrospective forecast SST anomaly also shows a clear seasonal dependency associated with what is called spring barrier. The predictability with respect to ENSO phase shows that the phase locking of ENSO to the mean annual cycle has an influence on the seasonal dependence of skill, since the growth phase of ENSO events is more predictable than the decay phase. The overall characteristics of predictability in the coupled system are assessed by comparing the forecast error growth and the error growth between two model forecasts whose initial conditions are 1 month apart. For the ensemble mean, there is fast growth of error associated with initial uncertainties, becoming saturated within 2 months. The subsequent error growth follows the slow coupled mode related the model’s incorrect ENSO dynamics. As a result, the Lorenz curve of the ensemble mean NINO3 index does not grow, because the systematic error is identical to the same target month. In contrast, the errors of individual members grow as fast as forecast error due to the large instability of the coupled system. Because the model errors are so systematic, their influence on the forecast skill is investigated by analyzing the erroneous features in a long simulation. For the ENSO forecasts in CFS, a constant phase shift with respect to lead month is clear, using monthly forecast composite data. This feature is related to the typical ENSO behavior produced by the model that, unlike the observations, has a long life cycle with a JJA peak. Therefore, the systematic errors in the long run are reflected in the forecast skill as a major factor limiting predictability after the impact of initial uncertainties fades out. 相似文献
20.
采用WRF模式对2010年9月发生在河南省附近的一次暴雨过程进行了集合预报试验。用增长模繁殖方法(BGM)制作了集合预报方案1;为了充分利用背景场信息,结合时间滞后法,制定了集合预报方案2:滚动繁殖法;考虑到暴雨过程中天气形势的特殊性,结合区域空间特征,制定了集合预报方案3:区域繁殖法。这3组试验均对变量U、V、T、Q进行了初值扰动,加上控制预报,均产生了9个集合成员。试验结果表明:几种集合预报方法在预报效果上相较于控制预报都具有明显的改善,滚动繁殖法及区域繁殖法对增长模繁殖法都具有一定的改进作用,其中区域繁殖法的预报效果更优,与实况更为接近。 相似文献