Lorenz系统误差方程的吸引子特性研究

将Lorenz方程及其导出的误差方程作为联立方程(即全误差方程)来研究误差的性质,结果表明联立方程可以变换为一个特殊的算子方程,误差轨线将收敛于一个有限的区域;此外联立方程对应的流的散度为负值,因此其在相空间中的体积不断收缩,最终趋向一个低纬曲面;联立方程的这两个性质使得Lorenz系统中初始误差不会无限放大,而是趋于一个吸引子.误差在吸引子上的概率分布是确定的,因此平均的绝对误差趋于常数,这个结果可以用来解释小初始误差经过一段时间的发展之后,趋向饱和的现象.利用稳定性分析方法研究了误差吸引中心的位置和个数,并使用数值试验进行了验证,结果显示误差吸引子的结构与解的吸引子位置、数量和结构均有不同.最后本研究将针对Lorenz方程的误差联立方程方法拓展到一般的常微分动力系统,展示了对一般误差方程的特征矩阵进行分析,研究其特征行列式性质的方法,得到了一般误差系统中稳定点和平衡态性质与原动力系统的稳定点和平衡态性质的关系,这些结果对于认识误差系统长期的动力学行为和性质是有意义的.     

集合平均方法减小混沌系统计算误差的效果研究

研究了Lorenz非线性系统中使用的集合平均方法来减小计算误差的效果,通过检查5组数值试验(每组20个样本)的结果发现:集合平均对计算误差的减小和消除不如高精度算法有效,这主要体现在以下几方面:1)普通的算法和双精度的计算环境中,若截断误差是主导误差(当初值误差很小时),各集合的平均结果并不收敛于真值,而是收敛于含截断误差的数值解;2)若初值误差为主导时,系统受到初值误差增长规律的影响,数值解收敛于由初值误差主导的误差解;3)这两种误差量级接近的时候,两种误差都无法消除掉。对解的统计特征进行研究表明,可信的数值解与含计算误差的数值解有许多相似的地方,但是与集合平均的数值解有很大不同,同样说明了集合平均不适用于减小计算误差这样的问题。此外,试验结果表明即使数值解的概率分布形式基本正确,也不能保证数值解是正确的。     

Lorenz模型中外源强迫强弱对初值可预报性的影响研究

通过调整Lorenz模型中表征外源强迫强弱的参数值r,采用显式四阶龙格-库塔(Runge-Kutta)方法,以探究不同外源强迫下所构建Lorenz系统的初值可预报性。得出了外源强迫增大,初值的可预报性降低,误差增长增大,可预报期限缩短,预报效果变差,系统对初值敏感依赖性增大的结论。初始值与其叠加微小偏差的相关系数随外源强迫增大出现三次骤减,在模拟出的Lorenz系统运动轨迹图中,Lorenz系统的奇异吸引子由一个变为两个,奇异吸引子周围的曲面也由一片演变成两片,混沌效应显现。X、Y、Z值的方差;X值、Y值超出一个标准差的步数随外源强迫增大表现出振荡上升趋势。外源强迫的增大也使得Lorenz系统分异与第一次出现反向所用的积分步数减小,两组数据的并行时间越来越短。统计X、Y、Z值的误差在5%,10%和20%范围内的积分步数发现,系统的误差增长随外源强迫增大而增大,不再处于合理范围内,因此初值可预报性降低,可预报期限也大大缩短。     

变分同化方法在Lorenz系统中的简单应用研究

利用Lorenz模式作变分同化数值试验，通过对一个简单系统的讨论，介绍四维变分同化方法。对初值敏感性和观测点的个数及观测值作了对比试验，发现随着模式对初值敏感性的增加，同化效果会越来越差；观测点越少，观测值误差越大，这些都会影响同化效果，甚至导致同化失败。     

基于Lorenz系统提取数值模式可预报分量的初步试验

针对数值预报模式中存在的非线性混沌特性, 从提取可预报分量的思路出发, 阐述了在数值模式中提取可预报分量的方法, 并利用Lorenz系统进行了相关数值试验。研究发现, Lorenz系统初始误差在相空间中的增长速度是不同的, 某些方向的误差增长速度较慢, 即存在对初值扰动不敏感、相对稳定的可预报分量。根据数值模式切线性误差算子的特征值演化规律, 提取出数值模式的可预报分量, 并将模式变量在其基底上进行投影变换, 建立了可预报分量数值模式。在此基础上, 研究了Lorenz系统的混沌状态、模式参数误差及外部随机噪声对提取可预报分量的影响, 发现基于可预报分量的数值模式, 具有更好的预报技巧。     

数值预报发展的新方向——集合数值预报

数值预报走过了百年的历史(V.Bjerknes,1904)[1],取得了了不起的成就,预报准确率有了很大的提高。但是,考虑到大气的非线性作用以及初值和模式造成的数值预报不确定性,要提高传统的单一确定性预报的技巧越来越难。基于大气初值的敏感性试验,Lorenz提出了数值预报发展的新方向——集合数值预报。通过介绍集合数值预报的基本思想和方法;并针对初值和模式的不确定性,概述现有集合数值预报成员的产生方法及国内外的研究进展;同时解释怎样检验集合预报的结果的论述,如何从众多的集合预报产品中提炼有用的信息及预报产品的释用。     

多精度计算和区间分析方法在科学计算中的应用

介绍了多精度计算和区间分析的概念、方法及应用,使用多精度计算研究Lorenz非线性动力系统计算结果对计算精度、步长的敏感依赖关系和不确定现象,研究Lorenz系统中长时间数值解的计算方法和基于多精度计算的最优步长、最大有效计算时间搜索方法,讨论了区间分析方法在计算机辅助证明Lorenz混沌吸引子存在性问题中的应用。     

湿大气方程组解的渐近性质

研究无穷维Ｈｉｌｂｅｒｔ空间中,湿大气运动系统解的长期行为,在导得了湿大气运动方程是Ｈｉｌｂｅｒｔ空间中一个非常特殊的算子方程之后,利用算子的性质讨论了全局吸收集和全局吸引子的存在性,揭示出系统解的渐近行为表现在吸引子的结构上及系统向非绝热加热的非线性适应过程。最后指出了几个简化方程组与原方程组在解的长期行为上的根本不同,从而给出长期天气或气候研究中简化方程组必须遵循的原则。     

随机强迫对集合预报效果的影响研究

以Lorenz96模式为动力框架,建立了考虑模式随机强迫不确定性的集合预报系统,并选择模式气候态和集合平均预报效果为研究对象,研究随机强迫对集合预报效果的影响.结果表明,在数值模式积分过程中引入恰当的随机强迫构成的新计算范式,较非随机强迫更接近真值的气候平均与气候标准差,对刻画数值模式的气候态也有正效果;且随机强迫的正效果主要体现在长时效阶段.集合平均预报方面,绝大部分白噪声随机强迫对应的集合预报效果优于非随机强迫集合预报,集合预报效果也随白噪声强迫增大非单调变化,并且非线性系统不同,相同比率的白噪声随机强迫产生的效果也不同.同时,绝大部分红噪声随机强迫对应的集合预报效果也优于非随机强迫集合预报,但仅部分φ(表示所引入外强迫的随机性部分和确定性部分相互耦合的一个度量)值对应的红噪声强迫集合预报优于白噪声随机强迫集合预报;而且红噪声随机强迫集合预报改善效果随系数的正负分布非对称且非单调变化.此外,相关系数φ的选择也依赖于模型.     

耦合的八模Lorenz系统的分叉特征

本文对两个不同尺度的Lorenz系统,通过引入一个耦合参数α把它们连接起来,并在二维参数空间α×r(Rayleigh数)中讨论了所建立的耦合系统的解的分叉过程。参数α在[0,1]区间中取值。当α=0时,耦合系统与著名的三模Lorenz系统相对应;当α=1时,则与一个包含两个Lorenz元的系统相对应。文章选取了三个不同的r值,研究了α从0变到1时,从单Lorenz系统的解到双Lorenz系统的解的非线性演化过程。     

The Relationship between Deterministic and Ensemble Mean Forecast Errors Revealed by Global and Local Attractor Radii

It has been demonstrated that ensemble mean forecasts, in the context of the sample mean, have higher forecasting skill than deterministic(or single) forecasts. However, few studies have focused on quantifying the relationship between their forecast errors, especially in individual prediction cases. Clarification of the characteristics of deterministic and ensemble mean forecasts from the perspective of attractors of dynamical systems has also rarely been involved. In this paper, two attractor statistics—namely, the global and local attractor radii(GAR and LAR, respectively)—are applied to reveal the relationship between deterministic and ensemble mean forecast errors. The practical forecast experiments are implemented in a perfect model scenario with the Lorenz96 model as the numerical results for verification. The sample mean errors of deterministic and ensemble mean forecasts can be expressed by GAR and LAR, respectively, and their ratio is found to approach2~(1/2) with lead time. Meanwhile, the LAR can provide the expected ratio of the ensemble mean and deterministic forecast errors in individual cases.     

The statistical structure of Lorenz strange attractors

The statistical characteristic quantities and marginal probability distribution of the Lorenz strange attractors were computed numerically. The results indicate that after a sufficiently long time the statistical characteristic quantities and marginal probability distribution tend to stable states, and the motion on the strange attractor is ergodic.     

Attractor sets and multiple equilibria in the resonance of topographically forced waves

The resonance of topographically forced waves is studied using a quasi-geostrophic spectral model on the rotating sphere. The use of complete spectral expansions without truncation leads to the exact solutions of the nonlinear coupling equations by means of the random phase approximation and the projection operator techniques under the dissipation-vanishing limit. The energy transfer process between topographically forced wave ensemble and zonal mean flow is described.It is shown that the dynamical system loses stability and further bifurcation takes place when the to-pographic force has occurred. There are two sorts of equilibrium point in the resonance system. The unstable equilibrium is an isolated equilibrium point and, therefore, is hardly observed to occur. The stable equilibrium is an attractor set which is related to the phenomenon of blocking.     

基于TIGGE资料的东亚地面气温预报的不一致性研究

基于TIGGE资料中欧洲中期天气预报中心(ECMWF)、美国国家环境预报中心(NCEP)和中国气象局(CMA)3个集合预报系统的地面气温集合预报资料,运用跳跃指数研究了3个集合预报系统中东亚地面气温的控制预报及集合平均预报的不一致性。结果表明,各个集合预报系统地面气温预报的时间平均不一致性指数差异较大。ECM WF时间不一致性指数最小,NCEP次之,CM A最大。另外NCEP的控制预报、ECM WF的控制预报和集合平均预报,这三者的时间平均不一致性指数随预报时效延长而增加,且集合平均预报一致性优于控制预报。而对于CMA预报的不一致性,无论是控制预报还是集合平均预报总体上都稳定地保持在较高的水平。此外,ECMWF的地面气温冬(夏)季预报的不一致性相对较强(弱),且单点跳跃随预报时效延长变化不明显,而控制预报和集合平均预报的异号两点跳跃以及三点跳跃出现的频率总体上随预报时效延长略有增加。     

轨线不稳定与误差增长

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。     

A Time-Averaged Covariance Method in the EnKF for Argo Data Assimilation

In the ensemble Kalman filter (EnKF), ensemble size is one of the key factors that significantly affects the performance of a data assimilation system. A relatively small ensemble size often must be chosen because of the limitations of computational resources, which often biases the estimation of the background error covariance matrix. This is an issue of particular concern in Argo data assimilation, where the most complex state-of-the-art models are often used. In this study, we propose a time-averaged covariance method to estimate the background error covariance matrix. This method assumes that the statistical properties of the background errors do not change significantly at neighbouring analysis steps during a short time window, allowing the ensembles generated at previous steps to be used in present steps. As such, a joint ensemble matrix combining ensembles of previous and present steps can be constructed to form a larger ensemble for estimating the background error covariance. This method can enlarge the ensemble size without increasing the number of model integrations, and this method is equivalent to estimating the background error covariance matrix using the mean ensemble covariance averaged over several assimilation steps. We apply this method to the assimilation of Argo and altimetry datasets with an oceanic general circulation model.

Experiments show that the use of this time-averaged covariance can improve the performance of the EnKF by reducing the root mean square error (RMSE) and improving the estimation of error covariance structure as well as the relationship between ensemble spread and RMSE.

RÉSUMÉ [Traduit par la rédaction] Dans le filtre de Kalman d'ensemble (EnKF), la taille de l'ensemble est l'un des facteurs clés qui ont une influence importante sur la performance d'un système d'assimilation de données. Il faut souvent choisir une taille d'ensemble assez petite à cause des limites des ressources informatiques, ce qui biaise souvent l'estimation de la matrice de covariance de l'erreur de fond. Cette question revêt une importance particulière pour l'assimilation des données Argo, qui fait souvent appel à des modèles de pointe très complexes. Dans cette étude, nous proposons une méthode de covariance moyennée dans le temps pour estimer la matrice de covariance de l'erreur de fond. Cette méthode suppose que les propriétés statistiques des erreurs de fond ne changent pas de façon importante d'une étape d'analyse à la suivante durant un court laps de temps, ce qui permet d'utiliser dans les étapes courantes les ensembles générés aux étapes précédentes. Ainsi, on peut construire une matrice d'ensembles conjoints combinant les ensembles des étapes précédentes et courantes pour former un plus grand ensemble dans le but d'estimer la covariance de l'erreur de fond. Cette méthode peut accroître la taille de l'ensemble sans augmenter le nombre d'intégrations du modèle; elle équivaut à estimer la matrice de covariance de l'erreur de fond en utilisant la covariance moyenne de l'ensemble calculée sur plusieurs étapes d'assimilation. Nous appliquons cette méthode à l'assimilation des ensembles de données Argo et d'altimétrie avec un modèle de circulation océanique générale.

Des essais montrent que l'emploi de cette covariance moyennée dans le temps peut améliorer la performance de l'EnKF en réduisant l’écart-type et en améliorant l'estimation de la structure de la covariance de l'erreur de même que la relation entre l'étalement et l'écart-type l'ensemble.     

Effect of wind vertical shear on diffusion characteristics in the mesoscale range

Using the turbulent statistical form of the vertical vortex diffusion coefficient K, in the planetary boundary layer (PBL) and Ekman spiral wind profile, the three-dimensional diffusion equation is solved by the numeri-cal method. The influences of vertical shear of both wind direction and wind speed on pollution trajectory and horizontal diffusion parameters σy are numerically analysed. The expressions of both pollution trajectory and σy, including the factor of wind shear, are obtained. The results show that the vertical shear of wind is important among all factors affecting the mesoscale dispersion. Specifically, from neutral to stable atmospheric conditions, vertical shear of wind makes greater contribution to σy than turbulence, thus it is the most important factor. In this paper, we have compared horizontal dispersion pattern with both Pasquill's dispersion pattern considering wind direction shear, and experimental data collected at 9 different sites rang-ing from 10 to 100 km, and the results show that our dispersion pattern is closer to the experimental values than Pasquill's results, and his correction to shear of wind direction is too large under the stable conditions.     

Global warming mitigation by sulphur loading in the stratosphere: dependence of required emissions on allowable residual warming rate

An approach to mitigate global warming via sulphur loading in the stratosphere (geoengineering) is studied, employing a large ensemble of numerical experiments with the climate model of intermediate complexity IAP RAS CM. The model is forced by the historical+SRES A1B anthropogenic greenhouse gases+tropospheric sulphates scenario for 1860–2100 with additional sulphur emissions in the stratosphere in the twenty-first century. Different ensemble members are constructed by varying values of the parameters governing mass, horizontal distribution and radiative forcing of the stratospheric sulphates. It is obtained that, given a global loading of the sulphates in the stratosphere, among those studied in this paper latitudinal distributions of geoengineering aerosols, the most efficient one at the global basis is that peaked between 50°N and 70°N and with a somewhat smaller burden in the tropics. Uniform latitudinal distribution of stratospheric sulphates is a little less efficient. Sulphur emissions in the stratosphere required to stop the global temperature at the level corresponding to the mean value for 2000–2010 amount to more than 10 TgS/year in the year 2100. These emissions may be reduced if some warming is allowed to occur in the twenty-first century. For instance, if the global temperature trend S _g in every decade of this century is limited not to exceed 0.10 K/decade (0.15 K/decade), geoengineering emissions of 4–14 TgS/year (2–7 TgS/year) would be sufficient. Even if the global warming is stopped, temperature changes in different regions still occur with a magnitude up to 1 K. Their horizontal pattern depends on implied latitudinal distribution of stratospheric sulphates. In addition, for the stabilised global mean surface air temperature, global precipitation decreases by about 10%. If geoengineering emissions are stopped after several decades of implementation, their climatic effect is removed within a few decades. In this period, surface air temperature may grow with a rate of several Kelvins per decade. The results obtained with the IAP RAS CM are further interpreted employing a globally averaged energy–balance climate model. With the latter model, an analytical estimate for sulphate aerosol emissions in the stratosphere required climate mitigation is obtained. It is shown that effective vertical localisation of the imposed radiative forcing is important for geoengineering efficiency.