Review of the development of ocean data assimilation

Zhenchang Zhang, Changying Wang 

College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China

Data assimilation compensates for the deficiency of a numerical model and minimizes the short-term forecasting error by combining observation data and numerical results. Data assimilation has become a popular research topic all over the world in recent years. The development of ocean data assimilation is introduced in this paper. 4D variational and Kalman filter methods are considered the best means of data assimilation. Thus, these two methods are described in detail. Several novel research methods of assimilation, including assimilation with a constraint condition and dimensionality reduction, are discussed.