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Objectives: The gravity variation caused by hydrometeorological factors is an important factor affecting the interpretation of seismic gravity variation results. However, quantitative analysis of gravity field changes caused by hydrometeorological factors is rarely carried out. Methods: This paper takes the northern Xinjiang, China as the research area and uses the global hydrological model data of global land data assimilation system (GLDAS) and an atmospheric model to calculate the gravity influence of hydrometeorological factors on the research area from January 2016 to December 2017. Results: The results show that the annual change of terrestrial water influence is 1.3 μGal, and the difference in spatial distribution of terrestrial water influence between two adjacent periods is lower than 1 μGal. The annual change of atmospheric influence is as high as 8 μGal, and the difference in spatial distribution of atmospheric influence between two adjacent periods is up to 6 μGal. Conclusions: The gravity variations before and after deducting hydrometeorological factors were compared using the mobile gravity measurement data of three periods, i. e., April 2016, August 2016 and June 2017. The comparison results show that in the processing of mobile gravity data in the northern Xinjiang, the large⁃scale hydrological factor can be ignored and the meteorological factor should be taken into account. Meanwhile, for a better analysis of the mobile gravity variation, soil moisture and atmospheric pressure near the measuring point should be observed during the mobile gravity measurement. [ABSTRACT FROM AUTHOR]

The water resources in the Tibetan Plateau have a profound impact on China’ s economic, social development and climate change. Based on gravity data from gravity recovery and climate experiment (GRACE) satellite , considering its filtering leakage error, this paper proposes the Forward ‐ Modeling method for quantitative estimation. In view of the glocial isostatic adjustment(GIA) effect, we first infer terrestrial water storage (TWS) changes in the Tibetan Plateau, and compare the results with the water‐global assessment and prognosis hydrology model(WGHM). Then we extract the time‐frequency spectrum of timeseries signals using short‐time Fourier transformation algorithm. In addition, we discuss the relationship between TWS and precipitation by combining with precipitation data from Global Presipitation Climatology Centre. The study finds that: (1) TWS shows obvious spatial differences after recovering leakage signal. In most of the period, TWS in the north and southeast is in large surplus, and TWS in the south and southwest is rapidly depleted. The spatial characteristics are basically consistent with the WGHM results. (2) The time‐frequency spectrum distribution of TWS is dominated by low‐frequency signals, and time‐series dynamic changes have obvious seasonal and periodic changes, with an annual amplitude of 7.5 cm. The increase rate of water storage in 2003―2004 was 3.89 cm/a. The loss rate in 2005―2010 was -0.31 cm/a. The rate of increase in 2011―2014 was 0.22 cm/a. (3) Precipitation is the main factor affecting the variation of TWS. In 2006 and 2009, precipitation was significantly lower, the water storage all decreased significantly. In 2010, there was heavy rainfall, the water storage increased significantly. The leakage error correction method and research results in this paper have important reference value for quantitative research on regional TWS varition. [ABSTRACT FROM AUTHOR]