Abstract:In this paper, we use empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) to analyze BJFS height time series, spanning from 2000 to 2015. Results show that not only the signals at well-known periods (annual, semi-annual, 3-month, 2-month and 1 month), but also quasi-biennial signals, which were difficult to detect previously, are found. Compared with EMD, it is proven that the EEMD approach can weaken the mode mixing phenomenon significantly. The decomposed intrinsic mode function (IMF) is transformed with a Hilbert algorithm, from which we observe that the annual and quasi-biennial oscillations are the major contributors to the height variations. Compared with wavelet analysis, the RMS of the difference between EEMD reconstruction signal and elevation sequence is smaller, showing the effectiveness of the HHT-EEMD method in data analysis. The annual and semi-annual variations in the height are mainly attributed to the surface mass loading by integrating geophysical models, and the existence of the quasi-biennial signals are verified by GRACE data.