The mass changes in the Earth’s surface internally derived from the Gravity Recovery and Climate Experiment (GRACE) and the GRACE Follow-On (GRACE-FO) missions have played an important role in the research of various geophysical phenomena. However, the one-year data gap between these two missions has broken the continuity of this geophysical research. In order to assess the feasibility of using the Swarm time-variable gravity field (TVGF) to bridge the data gap, we compared Swarm with the GRACE/GRACE-FO models in terms of model accuracy, observation noise and inverted terrestrial water storage change (TWSC). The results of the comparison showed that the difference between the degree-error root mean square (RMS) of the two models is small, within degree 10. The correlation between the spherical harmonic coefficients of the two models is also relatively high, below degree 17. The observation noise values of GRACE/GRACE-FO are smaller than those of Swarm. Therefore, the latter model requires a larger filter radius to lower these noise levels. According to the correlation coefficients and the time series map of TWSC in the Amazon River basin, the results of GRACE and Swarm are similar. In addition, the TWSC signals were further analyzed. The long-term trend changes of TWSC derived from GRACE/GRACE-FO and the International Combination Service for Time-variable Gravity Fields (COST-G)-Swarm over the period from December 2013 to May 2020 were −0.72 and −1.05 cm/year, respectively. The annual amplitudes of two models are 15.65 and 15.39 cm, respectively. The corresponding annual phases are −1.36 and −1.33 rad, respectively. Our results verified that the Swarm TVGF has the potential to extract TWSC signals in the Amazon River basin and can serve as a complement to GRACE/GRACE-FO data for detecting TWSC in local areas.

Yunnan province in China has rich forest resources but high forest fire frequency. Therefore, a better understanding of the relationship between climate change and forest fires in this region is important for forest fire prevention. This study used the Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage change (TWSC) data to analyze the influence of climate change on forest fires in the region during 2003–2016. To improve the accuracy and reliability of GRACE TWSC data, we used the generalized three-cornered hat (GTCH) and the least square method to fuse TWSC data from six GRACE solutions. The spatiotemporal variation of forest fires during 2003–2016 was investigated using burned area data. Then, the relationship between burned area and hydrological and climatic factors was analyzed. The results indicate that more than 90% of burned areas are located in northwestern and southern Yunnan (NW and S). On the seasonal scale, forest fires are mainly concentrated in January–April (dry season) and the burned area is negatively correlated with precipitation (correlation coefficient r = −0.83 (NW) and −0.51 (S)), relative humidity (r = −0.79 (NW) and −0.92 (S)), GRACE TWSC (r = −0.57 (NW) and −0.73 (S)) and evapotranspiration (r = −0.90 (NW) and −0.35 (S)). However, the burned area has no significant correlations with the above four factors on the interannual scale. The composite analysis suggests that the extreme climate affects precipitation, evapotranspiration and TWSC in this region, thereby changing water storage of the air in this region, leading to the formation of an environment prone to forest fires. Such conditions have led to an increase in the burned area in the above region. We also found that the difference between TWSC in high- and low-fire years is much greater than the precipitation in the same period. The above results show that GRACE satellites can detect the influence of climate change on forest fires in Yunnan province.

In recent decades, extreme floods and droughts have occurred frequently around the world, which seriously threatens the social and economic development and the safety of people’s lives and properties. Therefore, it is of great scientific significance to discuss the causes and characteristic quantization of extreme floods and droughts. Here, the terrestrial water storage change (TWSC) derived from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) data was used to characterize the floods and droughts in the Yangtze River basin (YRB) during 2003 and 2020. To reduce the uncertainty of TWSC results, the generalized three-cornered hat and least square methods were used to fuse TWSC results from six GRACE solutions. Then combining precipitation (PPT), evapotranspiration, soil moisture (SM), runoff, and extreme climate index data, the influence of climate change on floods and droughts in the YRB was discussed and analyzed. The results show that the fused method can effectively improve the uncertainty of TWSC results. And seven droughts and seven floods occurred in the upper of YRB (UY) and nine droughts and six floods appeared in the middle and lower of YRB (MLY) during the study period. The correlation between TWSC and PPT (0.33) is the strongest in the UY, and the response time between the two is 1 month, while TWSC and SM (0.67) are strongly correlated with no delay in the MLY. The reason for this difference is mainly due to the large-scale hydropower development in the UY. Floods and droughts in the UY and MLY are more influenced by the El Niño-Southern Oscillation (ENSO) (correlation coefficients are 0.39 and 0.50, respectively) than the Indian Ocean Dipole (IOD) (correlation coefficients are 0.19 and 0.09, respectively). The IOD event is usually accompanied by the ENSO event (the probability is 80%), and the hydrological hazards caused by independent ENSO events are less severe than those caused by these two extreme climate events in the YRB. Our results provide a reference for the study on the formation, development, and recovery mechanism of regional floods and droughts on a global scale.

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