Impact of hydrological de-aliasing on monthly GRACE gravity field solutions

The use of background model information in GRACE/-FO gravity data processing is essential to mitigate temporal aliasing errors arising from mass variations in the Earth System that occur on time periods shorter than one month. Currently, tidal and non-tidal mass variations in atmosphere and ocean are considered in the official GRACE/-FO monthly gravity field products provided by JPL, CSR and GFZ. However, also sub-monthly continental water storage variations might propagate as aliasing errors into the monthly solutions.

In this contribution, we investigate the impact of introducing hydrological background model data into GRACE processing on the quality of the resulting monthly solutions. For the hydrological mass signal, we use sub-monthly terrestrial water storage output from the open-source global hydrological model OS LISFLOOD (Jensen et al., 2025) forced with meteorological data from the ERA5 atmospheric reanalysis, which we include into the ITSG-Grace2018 (Kvas et al., 2019) processing scheme. Furthermore, we assess if the additional consideration of background model uncertainty information is advantageous for the quality of monthly solutions. To derive consistent hydrological error information, we perform a small ensemble of three OS LISFLOOD runs under different atmospheric forcings, from which we infer both error time series as well as a variance-covariance matrix that are also tested in the ITSG-Grace2018 processing scheme.