The Gravity Recovery and Climate Experiment (GRACE) provides estimates of the earthÕs static and time-variant gravity field. Solutions from various processing centers (GFZ, CSR, JPL etc.) enable us to determine water mass redistributions on the globe. Given that land signals are generally large compared to anomalies over the ocean; an assessment of the latter requires a particularly careful filtering of the data. We utilized the Finite Element Sea-Ice Ocean Model (FESOM) to develop a filtering algorithm which relies on the spatial coherency of ocean bottom pressure (OBP) anomalies. For every position in the ocean, OBP anomalies are coherent over a considerable area. Thus, this pattern can be used to determine time series of GRACE-derived OBP anomalies at any position by weighting the time series in the vicinity with the correlation to the original time series. A global validation with in situ OBP data from a global database which has been compiled at the AWI shows that the correlation between in situ and GRACE data is improved by using the new filter in comparison to Gauss filtering.In this study we use GRACE solutions from JPL, CSR and GFZ where the correlated errors in the spherical harmonic solutions have been removed. These so-called destriped solutions are available processed with a 300 km, 500 km, and 750 km radius Gauss filter. The best correlations to the in-situ data are obtained using the 750-km Gauss filtered data. Correlation to the in-situ data can be even further improved for a combination of destriping and pattern filtering.