A directed limited penetrable visibility graph (DLPVG)-based method of analysing sea surface temperature

摘要

The present paper studies the dynamic association among the sea surface temperature (SST) data through directed limited penetrable visibility graph (DLPVG) method. We analyse the fluctuation trend of temperature in different regions by constructing an SST-dynamic association network to explore the topology structure. By analysing the SST data of the East China Sea, we find that there are association patterns among multivariate SST and a few types of patterns play a significant role in the movement of the sea water. Furthermore, the experiments also show that the multivariate SST has a close relationship with El Nino events, which indicates that the network is of great significance to the research and prediction of the El Nino phenomenon.