针对垂向高密度潮流观测数据,利用经验正交函数(EOF,empirical orthogonal functions)分解的方法实现了数据的垂向建模,提取了包括反映潮流垂向变化规律和时域变化规律的两类参数。经对实测数据试验,该建模方法准确可行,且能够在不遗失潮流主要垂向变化信息的前提下,有效实现数据压缩,减少定点潮流表示参数的数量。 According to the vertical high-density tidal current observation data, the vertical modeling of the data is realized by means of the decomposition of empirical orthogonal functions (EOF). Two types of data, including vertical and temporal variations, are extracted parameter. The experimental results show that the modeling method is accurate and feasible, and can effectively compress data and reduce the number of fixed-point tidal current parameters without losing the main vertical information of tidal current.