Analysis of seasonal crustal deformation characteristics in Dali, Yunnan using GPS observations

This paper extracts and separates seasonal term of GPS (Global Positioning System) time series based on empirical mode decomposition and wavelet transformation. Through time series analysis of 9 GPS continuous stations in Dali, Yunnan, it is found that the vertical (U), north–south (N) and east–west (E) components of the relative motion have distinct annual and semi-annual period components. In the vertical direction, the U component has the strongest seasonal deformation characteristics, on the annual period term, between each station the correlation coefficient reaches 0.98, this is consistent with the relevant research results of many researchers; In horizontal direction, seasonal deformation is also more significant, the N component annual and semi-annual period signals are more obvious and the correlation coefficient is high, but the E component 9 stations signal are relatively scattered and poorly correlated. On the semi-annual period, the N and U directions have a very obvious and consistent semi-annual periodicity, and their two correlation coefficient numbers are 0.95 and 0.94 on average, respectively, the N and E are negatively correlated with a correlation coefficient of -0.98. In time series trend term, 9 stations show southeast movement in horizontal direction, but have great differences in vertical movement trend. Among them, YNLJ, YNYS, YNSD and YNLC are linear uplift movement with good consistency. YNYA, YNCX and YNJD show overall uplift movement, but with subsidence fluctuation, the trend of the three stations is very similar, with an average correlation coefficient reaches 0.8; XIAG station shows uplift movement as a whole, the relative motion trend in the E direction is very different from other stations in phase and amplitude, probably because it is closer to the Erhai lake and more susceptible to the influence of water level changes; YNYL also has different motion changes at different times, but the overall performance is subsidence motion. The analysis suggests that the GPS time series contains rich information on the seasonal deformation of the Earth’s crust, and precipitation has an important role in influencing the seasonal deformation of continuous stations.