Optimization and assessment of high-resolution regression mascons for multiple time intervals within the GRACE/GRACE-FO record

The benefit of combining long spans of GRACE data for enhancing the spatial resolution of the mean field and regression model parameters (e.g., trend and annual) has been demonstrated for years with the series of GOCO spherical harmonic gravity models (and others). More recently, our group has been applying the same general approach to the estimation of regularized regression mascons, with a particular focus on enhancing the spatial resolution of the recovered mass trends. Initial studies estimated the global trends over the full span of GRACE and GRACE-FO data, but recently we have been working to exploit the same approach over multiple time intervals within the data record, to capture mass change information over shorter intervals while also leveraging the higher spatial resolution afforded by the stacking of normal equations over many months. This approach was recently applied towards the quantification and classification of terrestrial water storage changes in the Great Basin in the Western U.S. (Hall et al., 2024). In this presentation, we provide a summary of this recent study, and discuss the challenges associated with estimating, comparing, and assessing uncertainties for high-resolution regression mascons over multiple time intervals.