Ocean data compression based on block SVD

Abstract

Abstract Fast development of ocean observations and numerical modeling increases the need for data transmission, storage and extraction. This paper presented a new data compression method based on Singular Value Decomposition (SVD) with data matrix divided into different sub-matrices with consideration of odevity and remnant. An automatic matrix-dividing method is applied to divide smartly the data matrix into sub-matrices. These sub-matrices are then compressed based on an improved SVD, which enhances the compression performance by utilizing the orthogonal property of vectors generated by SVD. A dynamic optimization method which is capable of determining the proper scale of retained data under the accuracy requirement of ocean data is also established. Two indices are derived mathematically to search the best block pattern quickly. The performance and reliability of the block-based SVD compression is verified with the successful compression and recovery of the Hybrid Coordinate Ocean Model data.