Analysis of mass flux variations in the southern Tibetan Plateau based on an improved spatial domain filtering approach for GRACE/GRACE-FO solutions

Abstract

ABSTRACT Limited by the north-south stripes and noise, it is challenging to estimate mass flux variations with high-precision from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) solutions. To extract more geophysical signals from the GRACE/GRACE-FO spherical harmonic coefficients (SHCs), we developed an improved spatial domain filtering (ISDF) approach based on terrain constraints to obtain the mass flux variations in the southern Tibetan Plateau. From the results of simulated data, compared with the actual signal, the Nash – Sutcliffe efficiency (NSE) calculated using the ISDF method (more than 0.86) is much higher than the traditional filtering result. Compared with the traditional filtering method (i.e. unconstrained Gaussian Filtering), the root mean squared error (RMSE) is reduced by about 27.7% of that calculated using the ISDF method from the simulated data with north-south stripes and noise. Moreover, the signal-to-noise ratio (SNR) calculated using the ISDF method has also been significantly improved. In the GRACE/GRACE-FO SHCs experiments, we compared the results calculated using the ISDF method with the mascon solutions of the three official centres, i.e. Center for Space Research (CSR), Jet Propulsion Laboratory (JPL), and Goddard Space Flight Center (GSFC). The results of time series decomposition show that the signals calculated using the ISDF method agree well with the mean-mascon solution and the annual amplitude and semi-annual amplitude differences between the two data are 0.01 cm and −0.61 cm, respectively. Our results underline that the ISDF is an efficient approach for estimating mass flux variations in the southern Tibetan Plateau from GRACE/GRACE-FO SHCs. Finally, we analysed the mass attenuation rates in three periods and the possible reasons in the southern Tibetan Plateau based on the different hydrological models.