The Regional Ocean Modeling System (ROMS) 4-dimensional variational data assimilation systems: Part II – Performance and application to the California Current System
The Regional Ocean Modeling System (ROMS) 4-dimensional variational data assimilation systems: Part II – Performance and application to the California Current System
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DOI：
10.1016/j.pocean.2011.05.003
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发表时间：
2011-10
影响因子：
4.1
通讯作者：
A. Moore;H. Arango;G. Broquet;Chris Edwards;M. Veneziani;B. Powell;Dave Foley;J. Doyle;Dan Costa;P. Robinson
中科院分区：
文献类型：
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作者：
A. Moore;H. Arango;G. Broquet;Chris Edwards;M. Veneziani;B. Powell;Dave Foley;J. Doyle;Dan Costa;P. Robinson
为了验证区域海洋模拟系统（ROMS）四维变分（4D-Var）资料同化系统各组成部分的性能和实用性，将其系统地应用于加州海流的中尺度环流环境。特别是，我们提出了一个比较的三种方法4D-VAR，即：原始配方的增量强约束方法;双配方“物理空间统计分析系统”;和双配方间接代表的方法。与理论上的考虑一致，当使用相同的观测和先验信息时，所有三种方法都收敛于相同的海洋环流估计。然而，双配方的收敛速度被发现是劣于原始配方。还探讨了与使用多个外环、预处理和弱约束相关的4D-Var性能的其他方面。还提出了对4D-Var控制矢量的各个组成部分（即初始条件、表面强迫和开边界条件）的影响的系统评价。它示出，在模型初始条件的不确定性校正施加的影响最大的模型的能力，以适应现有的观测。各种重要的诊断4D-Var也检查，包括估计的后验误差，观测阵列的信息内容，和创新为基础的一致性检查的先验误差假设。使用这些诊断工具，我们发现，超过90%的观测同化到模型提供冗余信息。这是使用大量卫星数据的一个症状，在某种程度上也是所采用的数据处理的性质。这是描述ROMS 4D-Var系统的三篇系列论文中的第二篇。
The Regional Ocean Modeling System (ROMS) 4-dimensional variational (4D-Var) data assimilation systems have been systematically applied to the mesoscale circulation environment of the California Current to demonstrate the performance and practical utility of the various components of ROMS 4D-Var. In particular, we present a comparison of three approaches to 4D-Var, namely: the primal formulation of the incremental strong constraint approach; the dual formulation “physical-space statistical analysis system”; and the dual formulation indirect representer approach. In agreement with theoretical considerations all three approaches converge to the same ocean circulation estimate when using the same observations and prior information. However, the rate of convergence of the dual formulation was found to be inferior to that of the primal formulation. Other aspects of the 4D-Var performance that relate to the use of multiple outer-loops, preconditioning, and the weak constraint are also explored. A systematic evaluation of the impact of the various components of the 4D-Var control vector (i.e. the initial conditions, surface forcing and open boundary conditions) is also presented. It is shown that correcting for uncertainties in the model initial conditions exerts the largest influence on the ability of the model to fit the available observations. Various important diagnostics of 4D-Var are also examined, including estimates of the posterior error, the information content of the observation array, and innovation-based consistency checks on the prior error assumptions. Using these diagnostic tools, we find that more than 90% of the observations assimilated into the model provide redundant information. This is a symptom of the large percentage of satellite data that are used and to some extent the nature of the data processing employed. This is the second in a series of three papers describing the ROMS 4D-Var systems.