The gap between the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on mission (GRACE-FO) is a crucial problem, leading to discontinuous global mass change information from time-variable gravity field solutions. We aim to use the improved Multichannel Singular Spectrum Analysis (MSSA) to fill the gap and reconstruct the continual global mass change signals in this study. The one-year gravity field gap is filled with improved MSSA based on the Release 06 (RL06) monthly gravity field models provided by Center for Space Research (CSR) truncated to d/o 60 and further compared with Swarm monthly solutions (d/o 40). The results show that the infilled gravity field models agree with the Swarm solutions, indicating that improved MSSA can reliably bridge the gap between GRACE and GRACE-FO missions. Moreover, relative to the Global Land Data Assimilation System (GLDAS) Noah model, the infilled gravity field models have higher correlation coefficients and smaller root mean squared errors than Swarm solutions for the mass change signals over Congo, Lena and Fraser river basins. According to the simulation results using the same gap as GRACE and GRACE-FO, improved MSSA can fill the gap very efficiently and reliably in 25 major river basins over the World.

重力恢复和气候实验（GRACE）与GRACE后续任务（GRACE-FO）之间的差距是一个关键问题，导致时变重力场解决方案产生的全球质量变化信息不连续。我们的目的是使用改进的多通道奇异频谱分析（MSSA）填补空白，并在本研究中重建连续的全局质量变化信号。根据太空研究中心（CSR）提供的06版（RL06）月度重力场模型，将一年的引力场填补为改进的MSSA，该模型被缩短至d / o 60，并进一步与Swarm月度解决方案（d / o）进行了比较40）。结果表明，填充的重力场模型与Swarm解决方案一致，表明改进的MSSA可以可靠地弥合GRACE和GRACE-FO任务之间的差距。此外，相对于全球土地数据同化系统（GLDAS）Noah模型，对于刚果，Lena和Fraser流域的质量变化信号，填充的重力场模型具有比Swarm解更高的相关系数和更小的均方根误差。根据使用与GRACE和GRACE-FO相同的差距的模拟结果，改进的MSSA可以非常有效，可靠地填补世界上25个主要流域的差距。