Abstract: Among all the factors that cause flight delays, meteorological factors account for a large proportion. Two algorithms for correlation analysis: Apriori algorithm and FP-Growth algorithm are used in this paper to quantify flight and meteorological data and clarify the quantitative relationship between flight delays and meteorological factors. On the basis of two algorithms, the transaction compression, Hash, and data compression method were used to enhance the algorithm efficiency. After that, the generation process of association rules and the execution process of the algorithm were optimized. That was, the association direction of association rules was specified and the parallel mining was used instead of sequential mining to further improve the efficiency of quantitative analysis of the system. We used Web development and big data visualization technology to design the quantitative analysis system of flight delay meteorological factors, and successfully deployed to air traffic management department. The system could quantitatively analyze single meteorological factors and multiple meteorological factors and visually display meteorological conditions affecting flight delays, providing effective decision-making basis for relevant civil aviation departments.