Data assimilation in a sparsely observed one-dimensional modeled MHD system
Data assimilation in a sparsely observed one-dimensional modeled MHD system
复制标题
稀疏观察的一维建模 MHD 系统中的数据同化
DOI：
10.5194/npg-14-181-2007
复制
发表时间：
2007
影响因子：
2.2
通讯作者：
W. Kuang
中科院分区：
文献类型：
--
作者：
Z. Sun;A. Tangborn;W. Kuang
以一维非线性磁流体动力学（MHD）系统为例，对时序最优插值同化技术进行了验证，该技术采用蒙特卡罗方法计算预报误差协方差。采用初始条件为扰动的100个模型集构造协方差，并通过观测模拟实验（OSE’s）对同化算法进行了验证。该系统具有多种观测类型（磁场和/或速度场）和一系列观测密度。通过运行带和不带这些项的同化，研究了速度和磁场之间交叉协方差的影响。组对实验表明，虽然同时观测速度和磁场对系统有最大的正向影响，但单独观测磁场也能有效地约束系统。对速度场的观测作为磁场的约束是无效的，即使在每个点上都进行了观测。讨论了地磁资料同化的意义。
A one dimensional non-linear magneto-hydrodynamic (MHD) system has been introduced to test a sequential optimal interpolation assimilation technique that uses a Monte-Carlo method to calculate the forecast error covariance. An ensemble of 100 model runs with perturbed initial conditions are used to construct the covariance, and the assimilation algorithm is tested using Observation Simulation Experiments (OSE's). The system is run with a variety of observation types (magnetic and/or velocity fields) and a range of observation densities. The impact of cross covariances between velocity and magnetic fields is investigated by running the assimilation with and without these terms. Sets of twin experiments show that while observing both velocity and magnetic fields has the greatest positive impact on the system, observing the magnetic field alone can also effectively constrain the system. Observations of the velocity field are ineffective as a constraint on the magnetic field, even when observations are made at every point. The implications for geomagnetic data assimilation are discussed.