A Lossless Compression Algorithm for Micaps Type 4 Lattice Data

Abstract

The invention relates to a Micaps fourth-class lattice point data lossless compression algorithm which comprises the steps of compressing a head of Micaps fourth-class lattice point data, i.e. redefining a head format of the data, wherein a compressed head file has 47 bits in total; carrying out processing and compression on a data part of the Micaps fourth-class lattice point data, i.e. firstly, multiplying each piece of data by 10, regulating the unit into 0.1 of the original unit, and then according to a level indicating bit corresponding to the head file, removing first two repeated bits of the front part of each piece of data; combining the head file with the compressed data part to obtain a complete compressed data file; and recompressing the data file by adopting libzip, finally generating a '.zim4' file, calculating a HASH value for the recompressed file and storing the HASH value. According to the invention, the storage utilization rate can be effectively improved, and the Micaps fourth-class lattice point data lossless compression algorithm is convenient for the internet and even a Beidou system to carry out transmission.

Description

technical field [0001] The invention relates to a data compression method, in particular to a lossless compression algorithm of Micaps fourth type grid point data. Background technique [0002] At present, Micaps data is developed by the China Meteorological Administration for the convenience of meteorological professionals to browse and transmit data, including a total of 26 total data formats. In the early stage of Micaps data design, the amount of data was small because the meteorological forecast was relatively low in terms of time resolution and spatial resolution. With the improvement of the technical level of weather forecasting, especially the improvement of the computing power of large-scale computers, the temporal and spatial resolution of numerical forecasting has been greatly improved, resulting in a blowout of meteorological data. The previous data format caused the generated files to be too large, which is not conducive to the long-term storage and flow of dat...

AI Technical Summary

Problems solved by technology

The previous data format caused the generated files to be too large, which is not conducive to the long-term storage and flow of data. A large amount of meteorological data had to be abandoned due to insufficient funds to purchase hard drives.

In addition, traditional WinRaR or WinZip compression tools, because of their universality, have a very limited compression ratio for Micaps data and cannot achieve a higher compression ratio

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