Dear Colleagues,

Since the launch of the Gravity Recovery and Climate Experiment (GRACE) satellite mission in 2002, satellite gravimetry has become the primary tool to use in studying mass transport in the Earth’s system at the global and regional scales. Data from GRACE and its successor, GRACE Follow-On (GFO) mission, have substantially contributed to the quantification of various mass transport processes at the Earth’s surface and in the Earth’s interior. An asset of the GRACE/GFO missions is their ability to provide accurate estimates of mass anomalies, with errors being almost uncorrelated in the time domain. However, the spatial and temporal resolution of GRACE-/GFO-based estimates is limited. On the other hand, geophysical models of various processes in the Earth’s system may offer a much higher spatial and temporal resolution, but typically suffer from systematic errors in the obtained estimates. These errors may be caused, among other issues, by the imperfect calibration of the model parameters and an accumulation of noise in the course of the integration of fluxes into the time domain. Thus, the assimilation of GRACE/GFO data into a geophysical model can be considered a powerful tool for maximizing the synergy of these two sources of information.

Authors may submit both full-length papers and shorter notes. The manuscripts may focus on any GRACE/GFO applications area, such as hydrology, oceanography, atmosphere, cryosphere and solid Earth studies. Manuscripts addressing theoretical aspects of GRACE/GFO data assimilation are welcome as well. Any types of GRACE-/GFO-based input data may be exploited, such as mass anomalies, spherical harmonic coefficients or inter-satellite ranging data. Simultaneous assimilation of GRACE/GFO and other data in a joint or multivariate data assimilation framework is encouraged. The goals of the data assimilation can also be diverse, e.g., an improvement of model parameters (model calibration), improved model forcing, an improvement of model states, as well as a combination of them. Both hindcast and forecast applications are of interest. A clear demonstration of the added value of a GRACE/GFO data assimilation will be particularly appreciated.

Dr. Natthachet Tangdamrongsub
Dr. Pavel G. Ditmar
Prof. Dr. Ehsan Forootan
Guest Editors

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