Deriving daily snapshots of the Earth's gravity field from GRACE L1B data using Kalman filtering

Different GRACE data analysis centers provide temporal variations of the Earth's gravity field as monthly, 10-daily or weekly mean fields. These solutions are derived independently for each time span, i.e., no correlation between the analyzed batches is considered. Following this procedure, an increase in temporal resolution is accompanied by a loss in accuracy. To avoid this problem, a new approach is followed, which takes into account the temporal correlations of the gravity field variations thus enabling the enhancement of the temporal resolution up to daily snapshots. The GRACE Level-IB (LIB) instrument data processing is performed within the framework of a Kalman filter estimation procedure, where the information about the temporal correlation patterns can be derived from geophysical models. The WaterGAP hydrological model was analyzed to derive the required information in terms of an empirical auto-covariance function. First results are presented and compared to GFZ-RL04 monthly and weekly gravity field solutions.