UNIFICATION AND APPLICATIONS OF MODERN OCEANIC/ATMOSPHERIC DATA ASSIMILATION ALGORITHMS
The key mathematics and applications of various modern atmospheric/oceanic data assimilation methods including Optimal Interpolation(OI),4-dimensional variational approach(4D-Var)and filters were systematically reviewed and classified.Based on the data assimilation philosophy,I.e.,using model dynamics to extract the observational information,the common character of the problem,such as the probabilistic nature of the evolution of the atmospheric/oceanic system,noisy and irregularly spaced observations,and the advantages and disadvantages of these data assimilation algorithms,were discussed.In the filtering framework,all modern data assimilation algorithms were unified: OI/3D-Var is a stationary filter,4D-Var is a linear(Kalman)filter and an ensemble of Kalman filters is able to construct a nonlinear filter.The nonlinear filter such as the Ensemble Kalman Filter(ENKF),Ensemble Adjustment Kalman Filter(EAKF)and Ensemble Transformation Kalman Filter(ETKF)can,to some extent,account for the non-Gaussian information of the prior distribution from the model.The flow-dependent covariance estimated by an ensemble filter may be introduced to OI and 4D-Var to improve these traditional algorithms.In practice,the performance of algorithms may depend on the specific numerical model and the choice of algorithm may depend on the specific problem.However,the unification of algorithms allows us to establish a unified test system to evaluate these algorithms,which provides more insights into data assimilation philosophies and helps improve data assimilation techniques.
作 者： QIAO Fang-li Zhang Shao-qing YUAN Ye-li 作者单位： QIAO Fang-li(Institute of Oceanography,Chinese Academy of Sciences,Qingdao 266071,China;Key Laboratory of Marine Science and Numerical Modeling,The First Institute of Oceanography,State Oceanic Administration,Qingdao 266061,China;Graduate School of the Chinese)Zhang Shao-qing(Geophysical Fluid Dynamics Laboratory,Princeton University,Princeton,NJ 08542,USA)
YUAN Ye-li(Key Laboratory of Marine Science and Numerical Modeling,The First Institute of Oceanography,State Oceanic Administration,Qingdao 266061,China)
刊 名： 水动力学研究与进展B辑 ISTIC EI 英文刊名： JOURNAL OF HYDRODYNAMICS 年，卷(期)： 2004 16(5) 分类号： P7 关键词： data assimilation oceanic/atmospheric system filtering Optimal Interpolation (OI) 4-dimensional variational(4D-Var) approach