Sensitivity analysis of the climate of a chaotic system

This paper addresses some fundamental methodological issues concerning the sensitivity analysis of chaotic geophysical systems. We show, using the Lorenz system as an example, that a naïve approach to variational ("adjoint") sensitivity analysis is of limited utility. Applied to trajectories which are long relative to the predictability time scales of the system, cumulative error growth means that adjoint results diverge exponentially from the "macroscopic climate sensitivity"(that is, the sensitivity of time‐averaged properties of the system to finite‐amplitude perturbations). This problem occurs even for time‐averaged quantities and given infinite computing resources. Alternatively, applied to very short trajectories, the adjoint provides an incorrect estimate of the sensitivity, even if averaged over large numbers of initial conditions, because a finite time scale is required for the model climate to respond fully to certain perturbations. In the Lorenz (1963) system, an intermediate time scale is found on which an ensemble of adjoint gradients can give a reasonably accurate (O(10%)) estimate of the macroscopic climate sensitivity. While this ensemble‐adjoint approach is unlikely to be reliable for more complex systems, it may provide useful guidance in identifying important parameter‐combinations to be explored further through direct finite‐amplitude perturbations.     

解析四维集合变分参数优化方法研究

传统的四维变分数据同化方法在同化观测资料的同时可以对数值模式参数进行优化,然而传统的四维变分方法需要针对不同的数值模式编写特有的伴随模式,因此算法的可移植性差,同时计算时耗费大量资源。本文提出了一种新的基于解析四维集合变分的参数优化方法,该方法以迭代搜索得到的模式参数为基准展开扰动并构建样本集合,由此显式地计算协方差矩阵,并得到代价函数极小值的解析解,从而避免了伴随模式的使用。基于Lorenz-63模型对该方法进行单参数和多参数数值试验和优化效果检验,并在不同的同化时间窗口长度和观测采样间隔情况下,采用传统四维变分方法与之进行对比,结果显示,新方法表现出与传统四维变分相同的优化性能,都能有效收敛到真值,而新方法不需要计算伴随模式,可移植性好。本文还测试了不同的集合成员个数和模式参数真值的情况下新方法的同化效果,结果表明,新方法对集合样本个数及模型参数真值不敏感,采用较少的集合样本即可完成数据同化。     

关于二阶伴随模型的理论研究

Hesse矩阵-目标函数关于控制变量的二阶偏导数形成的矩阵,在变分数据同化过程中以及敏感性分析等方面起着重要的作用;它可以通过建立数学模型的一阶和二阶伴随模型求得.以浅水方程模型为例,利用泛函的Gâteaux微分和Hilbert空间上伴随算子的概念,导出了一阶和二阶伴随模型并由此得到Hesse矩阵.改进了Zhi Wang等(1992)建立的二阶伴随模型理论.     

Assimilation of TOPEX Altimeter Data in a Reduced-Gravity Model of the Northwestern Indian Ocean

This study deals with the assimilation of TOPEX altimeter-derived sea level variability in a reduced-gravity model of the northwestern Indian Ocean. The assimilation has been done using variational assimilation method with adjoint technique. A cost function representing the misfit between the model and the data is minimized with the model equations acting as constraints. The initial conditions of the model are used as control parameters and the best-fit initial conditions are determined as a result of minimization carried out using a variable-storage quasi-Newton method. Experiment has been done with 10 days' cycle-averaged data of TOPEX. Assimilation for 10 days and 20 days has been performed and it has been seen that 20 days' assimilation of satellite data provides better results.     

A reduced-dynamics variational approach for the assimilation of altimeter data into eddy-resolving ocean models

A new method of assimilating sea surface height (SSH) data into ocean models is introduced and tested. Many features observable by satellite altimetry are approximated by the first baroclinic mode over much of the ocean, especially in the lower (but non-equatorial) and mid latitude regions. Based on this dynamical trait, a reduced-dynamics adjoint technique is developed and implemented with a three-dimensional model using vertical normal mode decomposition. To reduce the complexity of the variational data assimilation problem, the adjoint equations are based on a one-active-layer reduced-gravity model, which approximates the first baroclinic mode, as opposed to the full three-dimensional model equations. The reduced dimensionality of the adjoint model leads to lower computational cost than a traditional variational data assimilation algorithm. The technique is applicable to regions of the ocean where the SSH variability is dominated by the first baroclinic mode. The adjustment of the first baroclinic mode model fields dynamically transfers the SSH information to the deep ocean layers. The technique is developed in a modular fashion that can be readily implemented with many three-dimensional ocean models. For this study, the method is tested with the Navy Coastal Ocean Model (NCOM) configured to simulate the Gulf of Mexico.     

杭州湾三维悬浮泥沙输运模型初始场的伴随法反演研究

在悬沙输运的数值模拟中,初始场的准确给定至关重要。目前诸多确定初始场的方案均存在一定的缺陷,初始场的准确性有待进一步提高。本文基于一个三维悬沙输运伴随同化模型,通过孪生实验和实际实验,对模型初始场进行了伴随法反演研究。在孪生实验中,首先验证了初始场的相对重要性;其次,探讨了初始场的反演结果对优化算法、初始猜测值、卫星遥感数据数量、同化时间窗口宽度和背景流场误差的敏感性;最后,比较了伴随法和插值法重构初始场的能力。孪生实验结果表明:最速下降法对初始场的优化反演效果要优于三种共轭梯度法和有限记忆BFGS法;初始场的反演效果对初始猜测值、卫星遥感数据数量和背景流场误差不敏感,而对同化窗口宽度较为敏感;与插值法相比,伴随法是重构模型初始场更有效的手段。实际实验中,在杭州湾海域同化典型的小潮时期和大潮时期的GOCI卫星遥感资料所得表层悬沙浓度数据,优化反演了初始场。实际实验结果表明:数据同化后,得到了更符合实际的最优初始场,表明伴随法是实现初始场优化反演的有效手段。该研究对进一步改进悬沙输运模型的初始化方案具有一定的参考价值,也对其他数值模型的初始化方案具有一定的借鉴价值。     

Combining Argo profiles with a general circulation model in the North Atlantic. Part 2: Realistic transports and improved hydrography,between spring 2002 and spring 2003

A set of Argo profiles collected in the North Atlantic between May 2002 and April 2003 is combined with a low-resolution general circulation model (GCM) using the adjoint method. Fitting the real hydrographic observations leads to vast improvements in the model circulation, including the sea surface height and the meridional heat transport. We find striking differences in basin-scale transports compared with previous assimilation experiments that use the same GCM and a similar spatial resolution. Based on forward modeling studies, it is argued that these differences are due to different assimilation experiment durations. Over 1 year, the hydrography interpolated with the GCM from Argo profiles better represents the contemporary structures than does a long-term averaged climatology. The GCM dynamics are robust enough to distinguish between contemporary hydrography and climatological hydrography.     

变分伴随数据同化方法在断面海温数值计算中的应用研究

以二维断面海温分布模型为例,利用海温实际观测数据,将变分伴随方法应用于断面海温初始场的优化。讨论了变分伴随方法的基本思想,分别从模型方程的连续和离散形式出发推导伴随模型系统,并对这两种途径建立的伴随系统之间的相互关系进行了分析。数值试验的结果表明了变分伴随数据同化方法在海温数值计算和数值预报业务中的良好的应用前景。     

ARGO data assimilation into the ocean dynamics model with high spatial resolution using Ensemble Optimal Interpolation (EnOI)

The article proposes parallel implementation of the Ensemble Optimal Interpolation (EnOI) data assimilation (DA) method in eddy-resolving World Ocean circulation model. The results of DA experiments in North Atlantic with ARGO drifters are compared with the multivariate optimal interpolation (MVOI) DA scheme. The sensitivity of the model error, i.e., the difference between the model and observations depending on the number of ensemble elements, is also assessed and presented. The effectiveness of this method over the MVOI scheme is confirmed. The model outputs with and without assimilation are also compared with independent sea surface temperature data from ARMOR 3d.     

资料同化中的伴随方法及其在海洋中的应用

较系统地综述了资料同化中各种方法的分类,并着重说明了伴随方法的基本原理和具体实现步骤。并总结了伴随方法在海洋中的应用现状,并指出由于观测资料特别是遥感资料的日益丰富,伴随方法将有广泛地应用前景。     

Assimilation of the AVISO Altimetry Data into the Ocean Dynamics Model with a High Spatial Resolution Using Ensemble Optimal Interpolation (EnOI)

A parallel realization of the Ensemble Optimal Interpolation (EnOI) data assimilation (DA) method in conjunction with the eddy-resolving global circulation model is implemented. The results of DA experiments in the North Atlantic with the assimilation of the Archiving, Validation and Interpretation of Satellite Oceanographic (AVISO) data from the Jason-1 satellite are analyzed. The results of simulation are compared with the independent temperature and salinity data from the ARGO drifters.     

Assimilation of simulated altimeter data in a two-layer linear Rossby wave model using the variational method

The variational assimilation method has been examined for ability of reconstructing mesoscale features in altimeter data using a simple dynamic model. A one-dimensional, two-layer Rossby wave model in a cross-track channel has been chosen. The simulated data are constructed from a theoretical solution, which is composed of any combination of two normal vertical (barotropic and baroclinic) modes. The data are collected along tracks and with repeat periods similar to those of the Geosat altimeter. The phase space of control variables is composed of initial and boundary conditions. A cost function is defined to measure differences between the simulated data and the model solution. Regularization (smoothing) terms are also included in the cost function in the form of secon-order spatial and time derivatives of the solution. In this paper, two potential problems existing in the altimeter data assimilation are addressed: one is low cross-track resolution, and the other is vertical projection of the data measured at the sea surface. A succesful metho is developed for reconstructing Rossby waves with wavelengths as short as twice the track intervals for any combination of two vertical modes. A key component to efficient assimilation is a preparation step prior to the actual variational assimilation: a uniform ratio of pressure amplitudes in the two layers is included as an optimization parameter. Starting with the first guess from the preparation step, the variational method is carried out based on adjoint equations without such constraint. Separation of the control variables into the two subsets of the initial and the boundary conditions is found useful. Characteristics of the Hessian matrix are related to the performance of this technique. The method developed for the linear system implies steps to be included in data assimilation for nonlinear meanders and eddies in a major current system as well.     

海浪同化预报模型理论基础

将共轭变分同化方法应用于 LAGFD- WAM海浪数值模式 ,导出了海浪谱能量平衡方程的共轭方程以及风输入、破碎、底摩擦、波波非线性相互作用和波流相互作用的相应共轭源函数 ,建立了海浪同化模型 ,数值计算仍采用特征线嵌入计算格式 ,为合成孔径雷达波谱反演资料和卫星高度计有效波高资料同化奠定理论基础     

数据同化中的伴随方法及其有关问题的研究

论述了数据同化中的伴随方法与泛函分析中的伴随算子的关系，指出经典的拉格朗日乘子法可以作为伴随方法的理论基础。关于伴随方法应用中只能利用模式的伴随观点，作者认为是有疑问的，并提出了新的观点，所作的数值模拟实验表明，方程的伴随有时明显优于模式的伴随，因而说明方程的伴随也应该引起足够的重视。     

Euler–Lagrange equations for the spectral element shallow water system

We present the derivation of the discrete Euler–Lagrange equations for an inverse spectral element ocean model based on the shallow water equations. We show that the discrete Euler–Lagrange equations can be obtained from the continuous Euler–Lagrange equations by using a correct combination of the weak and the strong forms of derivatives in the Galerkin integrals, and by changing the order with which elemental assembly and mass averaging are applied in the forward and in the adjoint systems. Our derivation can be extended to obtain an adjoint for any Galerkin finite element and spectral element system.We begin the derivations using a linear wave equation in one dimension. We then apply our technique to a two-dimensional shallow water ocean model and test it on a classic double-gyre problem. The spectral element forward and adjoint ocean models can be used in a variety of inverse applications, ranging from traditional data assimilation and parameter estimation, to the less traditional model sensitivity and stability analyses, and ensemble prediction. Here the Euler–Lagrange equations are solved by an indirect representer algorithm.     

特征线计算格式下共轭方程两种导出途径的比较

共轭方程的导出是建立资料同化模型的关键，其导出方式有两种途径：AFD形式与FDA形式。在特征线计算格式基础上针对一类较广泛海洋动力控制方程分析了其两种共轭方程（AFD形式与FDA形式）之间的关系，并将理论结果应用于波谱共轭方程的讨论。     

非线性波波相互作用共轭源函数守恒量的分析

海浪组成波中的四波共振时满足谱作用量、谱能量及动量守恒，在变分同化所建立的波谱共轭方程中，对应于非线性波波相互作用源函数Boltzman积分形式，本文建立了其共轭源函数满足的守恒关系；实际海浪计算时广泛采用Hasselmann et al．(1985)的参数化方法，本文给出其综合作用表示式，证明也满足谱作用量、谱能量及动量守恒，并进一步导出了其共轭源函数中存在的守恒量。所有的共轭源函数守恒量只是对共轭算子而言的，对于共轭波谱则不存在相应的守恒关系。     

基于ROMS模式利用集合最优插值同化沿轨海表面高度异常数据的研究

The ensemble optimal interpolation （EnOI） is applied to the regional ocean modeling system （ROMS） with the ability to assimilate the along-track sea level anomaly （TSLA）. This system is tested with an eddy-resolving system of the South China Sea （SCS）. Background errors are derived from a running seasonal ensemble to account for the seasonal variability within the SCS. A fifth-order localization function with a 250 km localization radius is chosen to reduce the negative effects of sampling errors. The data assimilation system is tested from January 2004 to December 2006. The results show that the root mean square deviation （RMSD） of the sea level anomaly decreased from 10.57 to 6.70 cm, which represents a 36.6% reduction of error. The data assimilation reduces error for temperature within the upper 800 m and for salinity within the upper 200 m, although error degrades slightly at deeper depths. Surface currents are in better agreement with trajectories of surface drifters after data assimilation. The variance of sea level improves significantly in terms of both the amplitude and position of the strong and weak variance regions after assimilating TSLA. Results with AGE error （AGE） perform better than no AGE error （NoAGE） when considering the improvements of the temperature and the salinity. Furthermore, reasons for the extremely strong variability in the northern SCS in high resolution models are investigated. The results demonstrate that the strong variability of sea level in the high resolution model is caused by an extremely strong Kuroshio intrusion. Therefore, it is demonstrated that it is necessary to assimilate the TSLA in order to better simulate the SCS with high resolution models.     

A study on theory of second-order adjoint model

The adjoint approach, one of the variational data assimilation (VDA) methods, is now widely used for fitting numerical models of meteorology and oceanography tO the observaions. The fundamental idea is to minimize a cost function, which is sum of Squares in the differences betweenthe data and their model counterparts, by adjllsting the independent model variables such as initialvalue, boundary value and Parameters. The numerical model is an operator maPPing the independent model variables i…