Issues in the Comparison of Ground Gravity with GRACE Data David Crossley, Saint Louis U., Dept. Earth & Atmospheric Science, 3507 Laclede Ave., St. Louis MO 63104, Jacques Hinderer, EOST, 5 rue Descartes, Strasbourg 67084, France, Jurgen Neumeyer, Dept. Geodesy and Remote Sensing, GFZ Potsdam, Germany, G31C Figure 2. Individual station gravity residuals after correcting for local tides, nominal atmospheric pressure loading, and IERS polar motion. Amplitudes are in  Gal, with time in days since 1 Jan Vertical grid marks are semi-annual. Offsets are critical to long period SG observations and are removed with care. The two series from dual sphere instruments (MO, WE) are treated separately and combined only after all corrections. The linear trend contains secular gravity changes seen by AG instruments and the SG instrument drift. ACKNOWLEDGEMENTS The ground gravity data is from the ICET database, with other data supplied by: Bernd Richter, Herbert Wilmes, Peter Wolf, Michel van Camp, and Corinna Kroner. Bernard Ducarme assisted in tidal processing. Jean-Paul Boy provided the hydrology loading. For access to the JPL GRACE data and processing, we thank Frank Lemoine (NASA), and C. K. Shum and S. C. Han (Ohio State). This research is supported by NSF EAR # and CNRS. AGU Session ED03 … "The availability of sophisticated large-format printers has created a terrible temptation for scientists to present papers with linear storylines inherited from printed publications. Attending the average poster session becomes the daunting equivalent of reading 10 or 20 papers in less than an hour.“ GGP stations Stations BE and PO have stopped, and we did not use ME in this study GRACE gravity field, truncation n =  Gal to  Gal Comparison of the first principal eigenvectors and time components that account for 80% variance reduction of the GRACE data and 60% of the SG variability ABSTRACT AND PROCEDURE We processed 2 years of SG data from 6 stations in central Europe (Fig. 1) and did an EOF (Empirical Orthogonal Function) analysis to determine the principal components (PCs) and eigenvectors. We took GRACE Level 2 monthly satellite solutions, and extracted a portion of the gravity field over the same area as the SG stations. We also did an EOF analysis of this data. We compared both gravity field to the predictions of loading from a comprehensive hydrological model. We computed 3-D atmospheric attraction and deformation as an improvement to our previous empirical admittance -0.3  Gal / hPa (results for only 3 stations were completed, we do not show them) OBJECTIVE – TO EXAMINE 3 ISSUES Is it possible to compare ground and satellite gravity fields at the precision (  Gal) and resolution ( km) of hydrology? This we have done here. What is the effect of improving the atmospheric attraction to due a 3-D realistic atmospheric model? This we have done partly. How should one correct for SG stations that have mass above the gravimeters – thus contributing an additional upwards seasonal effect from soil moisture and snow not seen by the satellite. This we have yet to do. StationSensor Offsets removed (  Gal)Trend (  Gal yr -1 ) MBSingle sphere 6, from –3.1 to 1.9  Gal 3.86 MCSingle sphere 1, at 45.0  Gal 2.31 MO_LDual sphere, lower 2, from –8.7 to 5.7  Gal 4.83 MO_UDual sphere, upper 2, from –8.5 to 4.8  Gal 1.95 STSingle spherenone2.94 VISingle sphere 3, from –1.5 to 4.0  Gal 1.45 WE_LDual sphere, lower 6, from –41.1 to 5.1  Gal WE_UDual sphere, upper 6, from –43.0 to 7.5  Gal LOCAL HYDROLOGY The SG data are not corrected for hydrology, which is part of the target signal for GRACE comparisons. Local hydrology affects SG stations, but if the mass is below the station the local effects should be smoothed by spatial averaging (lots of instruments). Comparison between hydrology (soil moisture and snow) loading in gravity and SG gravity residuals. Snapshots of SG gravity field, minimum curvature surface  Gal to  Gal