G31A-01 INVITED
Global Surface Mass Variations From GRACE, GPS, and Geophysical Models
Non-steric sea-level change, Greenland, Antarctica and mountain glacial mass fluctuations and land hydrological cycles are all important parts of the global surface mass variation process with significant societal impact. Currently, no single geodetic technique or system can monitor these changes with complete spatiotemporal coverage. Studies of present-day surface mass trends are further frustrated by the duality of signatures of these trends and Glacial Isostatic Adjustment (GIA). Lack of reliable geocenter velocity estimate presents another serious problem. However, multi-satellite data from different geodetic techniques contain complementary spatiotemporal information. Also, the present-day surface mass trends and historical mass variations produce distinct signatures in different data types. Therefore, combination of multi-satellite geodetic and interdisciplinary data offers the best chance to separately determine the present-day mass trends, ice-water history, and Earth rheology with less ambiguity, better resolution and accuracy. We conduct global inversions for present-day surface mass variations in spherical harmonic domain using combinations of GRACE, GPS, a TOPEX/Poseidon/Jason-1 data-assimilated ocean bottom pressure model, and models of atmosphere, hydrology and GIA. The resulting coefficients with a complete spectrum up to degree and order 50 are then used to study global patterns and regional averages. Strategies and significance of further data combinations in the future will also be discussed.
G31A-02
Analysis of the GRACE Gravity Sensor System
The quality, strength and homogeneity of global gravity field models from the US-German gravity mission GRACE (Gravity Recovery and Climate Experiment, launched in 2002) is unprecedented and the derived models are superior to any previous satellite-only gravity field model. However, the predicted accuracy of these GRACE-only models (so-called GRACE baseline) has not yet been completely reached, thus still limiting a full geophysical exploitation of the GRACE mission data. Among others, the cause could lie in a degraded performance or interaction of elements of the gravity field sensor system. Another possible reason is that suboptimal signal processing methods have been applied. The gravity field sensor system consists of the K-Band distance measurements, the star sensor data for the orientation in inertial space, the accelerometer data and the GPS phase and code data. This investigation focuses on the analysis of the raw star sensor data and the related signal processing applied to generate higher level (so-called L1B) star sensor data which are used in the gravity recovery process. First, the performance of the raw star sensor data is discussed. Then the related signal processing is analyzed: In particular we investigate 1) the combination of star sensor data from the two available sensor heads aboard each GRACE satellite and 2) the combination of the star sensor and the angular acceleration data to derive improved(?) L1B star sensor data. The results are discussed and the expected impact on the gravity field recovery is evaluated.
G31A-03
El Niño and La Niña Signals in Sea Level, Hydrological Mass Redistribution, and Degree- Two Geoid Coefficients
We assess El Niño-Southern Oscillation (ENSO) related variability of steric and eustatic sea level, hydrological mass redistribution in the atmosphere and on the continents, and the corresponding signals in the degree-two geoid coefficients. The analysis utilizes 200 years of simulated monthly data from the ECHAM5/MPI-OM coupled atmosphere-ocean general circulation model, which includes a land-surface and runoff scheme. In the model, eustatic sea level anomalies are mostly balanced by continental water storage. Large eustatic sea level changes (up to 7 mm over 3 years) and continental water storage occur concurrently with some of the simulated ENSO events, but sign and amplitude vary. Therefore, we find no systematic, linear response of eustatic sea level to ENSO events. Steric sea level, on the other hand, varies significantly in phase with ENSO, but there is considerable decadal variability that cannot be linked to ENSO. Atmospheric water vapor content is strongly correlated with ENSO variability, and continental water storage is weakly correlated with ENSO. Based on the geographical pattern of hydrological surface mass load anomalies, we find significant ENSO related variability in the S21 and C20 geoid coefficients, but not in C21. The largest contributions to the S21 component come from mass redistribution within the oceans, and from continental water storage loading anomalies. For the C20 component, the largest ENSO-related contribution comes from continental water storage loading anomalies, whereas the contribution from mass redistribution within the oceans is not significantly correlated with ENSO. Therefore, we suggest that ocean mass redistribution associated with the observed 1997/1998 C20 (or J2) anomaly (Dickey et al., 2002) was most likely not dynamically linked to ENSO.
G31A-04 INVITED
Assimilation of GRACE Derived Terrestrial Water Storage Data into a Hydrological Model
GRACE has great potential to benefit hydrology, because no other observation system, ground- or space-based, has ever mapped variations in terrestrial water storage (TWS; the sum of groundwater, soil moisture, surface water, and snow). However, because its spatial and temporal resolutions are low relative to other hydrological observing systems and because total terrestrial water storage is a variable unfamiliar to hydrologists, GRACE has yet to become a standard tool for hydrology. Land surface models (LSMs) simulate the redistribution of water and energy incident on the land surface, but their accuracy is limited by the quality of the input data used to parameterize and force the models, the model developers' understanding of the physics involved, and the simplifications necessary to depict the Earth system economically. The advantages of GRACE and LSMs can be harnessed by data assimilation, which synthesizes discontinuous and imperfect observations with our knowledge of physical processes, as represented in a LSM. The model fills observational gaps, provides quality control, and enables data from disparate measurement systems to be merged, while the observations anchor the results in reality. We have assimilated TWS anomalies derived from GRACE into the Catchment LSM. The experimental domain was the Mississippi River Basin. Monthly GRACE estimates were derived for each of the four major sub-basins. Assimilation was performed using an Ensemble Kalman smoother. In addition to simulating soil and snow water storages, the Catchment LSM accounts for variations in the elevation of the water table, making it appropriate for total terrestrial water storage applications. The assimilated results produced groundwater storage time series which more closely resembled piezometer based estimates, relative to the open loop (non-assimilating) simulations. These results emphasize the potential for GRACE to improve the accuracy of hydrologic model output, which will benefit water cycle science and water resources applications. Furthermore, data assimilation enables coarse resolution, vertically integrated terrestrial water storage anomalies from GRACE to be spatially and temporally disaggregated and attributed to different levels of the snow-soil-aquifer column in a physically meaningful way.
G31A-05
Are superconducting gravimeters expensive soil moisture probes?
This paper investigates hydrological processes and their influence on gravity at the underground geodynamic Membach station (eastern Belgium), where absolute (AG) and superconducting (SG) gravity measurements have been performed since 1996. Seasonal and short term effects are observed. A comprehensive hydrogeological investigation regarding the influence of variations in local and regional water mass on gravity measurements is presented for observations taken near the station. Applying a regional water storage model, the gravity contribution due to the elastic deformation of the Earth is derived. In addition, the Newtonian gravity effect induced by the local water mass variations is calculated, using soil moisture observations taken at the ground surface (about 48 m above the gravimeters). The computation of this gravimetric effect is based on a digital elevation model with spatially discretized rectangular prisms. The obtained results are compared with the observations of gravity. We find that the seasonal variations and shorter period effects depend on the local changes (about 100 m around the gravimeter) in hydrology. This result shows the sensitivity of SG observations to very local water storage changes. This may be useful e.g. to constrain the water budget in local systems like karst aquifers.
G31A-06
Towards physical modeling of hydrological contribution in Strasbourg observatory
Environmental forcings may influence geodetic measurements on a broad band of frequencies, ranging from long-term and annual variations to short-period disturbances of a few hours, possibly hiding internal processes. Hydrology, in particular, is pointed out to have a 100 nm.s-2 contribution. Two main difficulties arise: i) all environmental signals are correlated, especially on annual time scale and ii) gravimeters are sensitive to both local scale hydrology (water masses closer than 1km) and global scale hydrology (mass redistribution on the entire earth). As a consequence, fitting estimated corrections on geodetic data could lead to an incomplete correction of the environmental contribution and an incorrect evaluation of other environmental contributions (ocean especially). The hydrological contribution on gravimetric measurements is explored using physical modeling, and applied to the superconducting gravimeter in Strasbourg observatory. If global hydrological models may be used to model global scale contribution (e.g. LadWorld, GLDAS), local scale hydrology need a little more attention, both amount and position of water masses should be modelled. To this purpose, two multi-depth frequency-domain reflectometer (FDR) probes have been installed. They are monitoring the variation of the water content of the entire soil thickness with a 5-minute sampling since August 2005. A precise local DEM has been established using dGPS, the geometry and heterogeneity of the soil layer have been evaluated thanks to geophysical and geomecanical prospections. We show the great importance of the top soil layer in Strasbourg, since a one-meter thick soil may store an amount of 200 mm of a full layer of water (equivalent to a 80 nm.s-2 variation). This methodology also enable us to answer the question whether ground geodetic measurements may be used as tools for hydrologists.
G31A-07
The DNSC07A ocean-wide altimetry-derived gravity anomaly field
DNSC07A is a new ocean-wide altimetry-derived gravity anomaly field computed at the Danish National Space Center with a spatial resolution of 1 arc-minute by 1 arc-minute covering all marine regions of the world including the Arctic Ocean up to the North Pole. DNSC07A was derived using satellite altimetry from the ERS-1 and GEOSAT geodetic missions, retracked using a highly advanced expert based system of multiple retrackers. This enables accurate ranging to both the open ocean surface and to all ice-covered regions within the +/- 82º of latitude coverage of the ERS satellites. Augmenting these data with ICESat data and with gravity anomalies from the Arctic Gravity Project (ArcGP) enables the continuation of the gravity anomaly field all the way up to the North Pole. The DNSC07A altimetry-derived gravity anomaly field was derived with respect to a very high degree (2160) Earth Gravitational Model designated PGM07B and a consistent mean Dynamic Ocean Topography model designated DOT07A, derived jointly by NGA and its contractor SGT, Inc.. Compared to other pre-existing altimetry-derived gravity anomaly fields like KMS02, DNSC07A is significantly improved, especially over short spatial wavelengths, which can also be seen from comparisons to independent marine gravity data. http://www.spacecenter.dk
G31A-08
Retrieving Earthquake Signature in GRACE Data
The GRACE mission is now orbiting the Earth for several years, monitoring the time variable gravity field. Some of the observed fluctuations are due to geodynamic causes, but they are often hidden in the complex signal, composed of hydrology, ocean, atmosphere, and geodynamics, the signal of geodynamic origin being usually the smallest. In addition, dealiasing residuals and noise make the separation of the signal from the different causes more difficult. We propose a Empirical Orthogonal Function (EOF) based method to extract the signal of physical origin, under the hypothesis that the physical signal is spatially more consistent than the noise and aliasing incomplete correction. We used synthetic earthquake geoid variations located at nearly 2000 positions at the Earth surface, based on several examples of large actual subduction events. We show that we can retrieve the gravity signal caused by vertical displacement and dilatation associated with more than 98% of the earthquakes of magnitude 9 or above (Chile [1960] and Sumatra [2004]), around 60% for magnitude 8.8 (Ecuador [1906]), 40% for magnitude 8.6 (Nias [2006]), and 33% for magnitude 8.3 (Kuril [2005]). Some events, with the right properties and location, can be detected with magnitude as low as 8. We then applied the method to the GRACE data, and showed that only the Sumatra event (2004), can be retrieved at the present data quality. Those results are in agreement with the retrieval rates mentioned here above.