We report the detection of an earthquake by a space-based measurement. The Gravity Recovery and Climate Experiment (GRACE) satellites observed a +/-15-microgalileo gravity change induced by the great December 2004 Sumatra-Andaman earthquake. Coseismic deformation produces sudden changes in the gravity field by vertical displacement of Earth's layered density structure and by changing the densities of the crust and mantle. GRACE's sensitivity to the long spatial wavelength of gravity changes resulted in roughly equal contributions of vertical displacement and dilatation effects in the gravity measurements. The GRACE observations provide evidence of crustal dilatation resulting from an undersea earthquake.

[1] We quantify gravity changes after great earthquakes present within the 10 year long time series of monthly Gravity Recovery and Climate Experiment (GRACE) gravity fields. Using spherical harmonic normal-mode formulation, the respective source parameters of moment tensor and double-couple were estimated. For the 2004 Sumatra-Andaman earthquake, the gravity data indicate a composite moment of 1.2 Â 10 23 N m with a dip of 10 , in agreement with the estimate obtained at ultralong seismic periods. For the 2010 Maule earthquake, the GRACE solutions range from 2.0 to 2.7 Â 10 22 N m for dips of 12 -24 and centroid depths within the lower crust. For the 2011 Tohoku-Oki earthquake, the estimated scalar moments range from 4.1 to 6.1 Â 10 22 N m, with dips of 9 -19 and centroid depths within the lower crust. For the 2012 Indian Ocean strike-slip earthquakes, the gravity data delineate a composite moment of 1.9 Â 10 22 N m regardless of the centroid depth, comparing favorably with the total moment of the main ruptures and aftershocks. The smallest event we successfully analyzed with GRACE was the 2007 Bengkulu earthquake with M 0~5 .0 Â 10 21 N m. We found that the gravity data constrain the focal mechanism with the centroid only within the upper and lower crustal layers for thrust events. Deeper sources (i.e., in the upper mantle) could not reproduce the gravity observation as the larger rigidity and bulk modulus at mantle depths inhibit the interior from changing its volume, thus reducing the negative gravity component. Focal mechanisms and seismic moments obtained in this study represent the behavior of the sources on temporal and spatial scales exceeding the seismic and geodetic spectrum.Citation: Han, S.-C., R. Riva, J. Sauber, and E. Okal (2013), Source parameter inversion for recent great earthquakes from a decade-long observation of global gravity fields,

S U M M A R YMonthly mass variations within the Earth system produce temporal gravity changes, which are observable by the NASA/GFZ Gravity Recovery and Climate Experiment (GRACE) twinsatellite system. Mass load changes with spatial scales larger than 1000 km have been observed using conventional filters based on a Gaussian smoother, which applies a weight to GRACE spherical harmonic (SH) coefficients depending only on SH degree. This practice is consistent with a degree-dependent error model for GRACE monthly geopotential solutions. The Gaussian filters effectively dampen all power of ill-determined higher-degree components in the estimates. However, the spatial sampling provided by GRACE yields errors that vary with both SH degree and order. The consequence is that maps of spatial loads shall not be smoothed with an isotropic (degree-only) filter, but shall be constructed using anisotropic smoothing thus also yielding better spatial resolution in latitude. We have developed a non-isotropic filter to optimize the smoothing of GRACE temporal gravity observations by considering the degreeand order-dependent quality of GRACE estimates, the latter analysed from the correlation with the predicted signals of hydrologic and ocean models. In order to retain GRACE coefficients in the filtering process that show reasonable correlation with the geophysical (hydrology and ocean) models, we applied Gaussian-type smoothing but with averaging radius depending on the order of the geopotential coefficient estimates. Applied to 2 yr of GRACE data, we showed that the resulting non-isotropic filter yields enhanced GRACE signals with significantly higher resolution in latitude and the same resolution in longitude without reducing the accuracy as compared to the conventional Gaussian smoother.Climate-related mass redistribution on the Earth has been observed in the time-varying gravity components derived from the NASA/GFZ Gravity Recovery and Climate Experiment (GRACE) satellite mission at monthly temporal scales and spatial scales of 1000 km or greater (Tapley et al. 2004a;Wahr et al. 2004). The GRACE twin co-orbiting satellites were launched in 2002 and are in near-circular orbits of 89 • mean inclination and 500 km mean altitude. Monthly time-series of geopotential spherical harmonic (SH) coefficients constitute the GRACE Level-2 (L2) science data product (Tapley et al. 2004b). To obtain reasonable estimates of time-varying gravity signals and related surface load changes due to air and water, L2 coefficients should be filtered because high spatial-frequency (high SH degree) components are poorly determined. The current approach uses degree-dependent filters such as Gaussian filters (Tapley et al. 2004a;Wahr et al. 2004). These produce spatially isotropic smoothing of surface load maps as a function of time. The spatial radius of the smoothing filter is empirically selected by considering the magnitude of the a priori temporal gravity signal (e.g. from hydrological or ocean circulation models) and the GRACE error power spectrum. H...

[1] We explore the mechanisms whereby groundwater influences terrestrial water storage (TWS) in the Amazon using GRACE observations and two contrasting versions of the LEAF-Hydro-Flood hydrological model: one with and the other without an interactive groundwater. We find that, first, where the water table is shallow as in northwestern Amazonia and floodplains elsewhere, subsurface stores (vadose zone and groundwater) are nearly saturated year-round, hence river and flooding dominate TWS variation; where the water table is deep as in southeastern Amazonia, the large subsurface storage capacity holds the infiltrated water longer before releasing it to streams, hence the subsurface storage dominates TWS variation. Second, over the whole Amazon, the subsurface water contribution far exceeds surface water contribution to total TWS variations. Based on LEAF-Hydro-Flood simulations, 71% of TWS change is from subsurface water, 24% from flood water, and 5% from water in river channels. Third, the subsurface store includes two competing terms, soil water in the vadose zone and groundwater below the water table. As the water table rises, the length of vadose zone is shortened and hence the change in groundwater store is accompanied by an opposite change in soil water store resulting in their opposite phase and contributions to total TWS. We conclude that the inclusion of a prognostic groundwater store and its interactions with the vadose zone, rivers, and floodplains in hydrological simulations enhances seasonal amplitudes and delays seasonal peaks of TWS anomaly, leading to an improved agreement with GRACE observations.