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Abstract

After a weak decreasing trend from 2000 to 2013, the water levels of the Laurentide Great Lakes increased by about 0.9-1.9 m from 2013 to 2020. Apart from such long-term change, water levels of the Great Lakes also exhibit significant annual and interannual variabilities. Investigating such multitemporal signals is pivotal to improve our understanding of the continental-scale water cycle and provides insights for elucidating short-term climate variations. Here, we use the variational mode decomposition (VMD) method to study the multitemporal water level variations of the Great Lakes. Specifically, the VMD method is applied to twenty water level gauges, and then the decomposed signals with the identical temporal resolution are averaged to obtain corresponding water level changes. Changes in water levels results in a variation in terrestrial water storage (TWS) and causes elastic loading deformation. Here, the GRACE/GRACE-FO gravimetry Level 2 data are used to reveal the TWS change, which is computed using the Slepian basis function which mitigates the signal leakage effect. The loading-induced deformation is calculated with a forward model and validated with GNSS coordinate time series. In addition, to further explore the climatologic mechanism for water level change, precipitation data from National Weather Service is also used. All of the geodetic observations mentioned are processed with the VMD method to acquire resolutions suitable to model multitemporal water levels, and the joint analysis aims to improve our knowledge of the causes and extent of water level change of the Great Lakes during the recent decades.