Multi-factor network modeling and simulation analysis of time-series dynamic and static climate

With the development of complex networks and big data disciplines, complex networks and big data are widely used in various fields to reveal the changing characteristics of things. This paper applies the method of complex network to climatology, explores the complex interaction of various climatic factors in China’s regional climate system with the method of complex network, selects the meteorological big data of 288 meteorological stations in China from 1984 to 2016, defines the meteorological stations and connecting network under various climatic factors as a single factor climate network, and adds the connecting edge between meteorological stations with different climatic factors on this basis, Then the multi-factor climate network is constructed by the network characteristic parameters. The analysis of correlation and stability shows that the correlation of climate network from strong to weak is spring, autumn, winter and summer; In the process of 33 years of time series change, the correlation of climate network shows a weak downward trend, with strong stability and good viability.