MEASURE, REPRESENTATION AND MODELING OF THE GRAVITY FIELD GRAVITY FIELD

In the recent years, our knowledge of the Earth gravity field has dramatically increased thanks to improvements in ground (land and sea) data acquisition using new measuring systems (new relative and absolute instruments, full tensor gradiometry measuring devices, airborne surveys, etc…) and to the new available satellite gravity data as the ones provided by the GRACE mission. This called for improvement and new development in data acquisition, data processing and interpretation methods as much as in the gravity field representation.

New methodologies were studied in order to create high-resolution gravity maps in oceanic areas. In the oceans, different types of data (satellite altimetric data and marine gravity data for example) can be used and merged to preserve their

specific information content. Nevertheless, the results of such data mixing are usually not optimal in precision and resolution. In some geodynamical areas the bathymetry can be taken as a “data interpolator” by the use of neuronal methods, improving the quality of the gravity mapping [Lequentrec-Lalancette et al., 2006].

Concerning the airborne gravimetry, several studies were devoted to the improvement of the measuring devices [Verdun et al., 2005] or on data processing [Abbassi, 2006]. These studies often used the French-Swiss Alps survey [Verdun et al., 2003] as a test area. A specific instrumental development had been carried out at the Laboratoire de Recherche en Géodésie (IGN) and the École Supérieure des Géomètres et Topographes with a view to perform

gravity measurements on vehicles [de Saint-Jean et al., 2005a and b, 2006].

The rebirth of gravity gradiometry some decades after the extinction of torsion balance surveys thanks to the development of full tensor gradiometry (FTG) measurements led to an increasing use of these data in geophysical prospecting. In addition, the European space gravity mission GOCE, to be launched in 2007, should also provide

gravity gradients measurements. As a consequence several studies aimed at improving or developing dedicated methods for gradiometry data denoising and interpretation [Mikhailov and Diament, 2006; Pajot et al., 2006; Guillen et al., 2006]. The collocation method was studied and the planar covariance functions were explored to compute the geoid parameters [Moreaux et al., 2004 and 2005].

Figure 1: free-air anomalies over the Marquesas archipelago obtained by merging GRACE, satellite altimetry and sea-surface data. After [Panet, 2005].

One of the major questions we will have to face due to the availability of new global satellite gravity data will be to compare and merge satellite data with ground and airborne ones. Comparison is a

mandatory task in order to calibrate and validate the satellite data. Merging is also a mandatory task in order to be able to extend towards the high frequencies the information provided by satellite data.

Indeed, merging allows taking full advantage of both satellite and ground/airborne data in order to provide a complete and accurate picture of the gravity field. This is a key question both for carrying geodynamic studies at various scales and for geoid computations. A significant advance was obtained by the development and implementation of a wavelet based representation of the gravity field [Panet et al., 2004; Chambodut et al., 2005; Panet, 2005; Panet et al., 2006].

Figure 1 shows the free-air anomalies over the Marquesas archipelago obtained by merging GRACE, satellite altimetry and sea-surface data. Its resolution is 35 km and precision about 1 mGal; furthermore only 9500 wavelets were used instead of nearly 300 000 spherical harmonics required in the classical spherical harmonics representation.

The analysis in terms of density inhomogeneities of these gravity models using a continuous wavelet analysis was also developed [Panet et al., 2006]. It allowed providing significant results as to the origin of intraplate volcanism in French Polynesia, a question that has been intriguing for decades. Indeed, [Panet et al., 2006] evidenced a plume beneath Society Islands and on the contrary suggested that no deep structure was associated to the Marquesas Chain. One can note that this new method of analysis

of gravity models confirms the efficiency of the wavelet based potential field interpretation approaches previously (before 2003) published by teams in Rennes University, IPGP and EOST.

In the meantime, improvement of more traditional methods for identifying causative bodies was realized. For instance [Mikhailov et al., 2003] proposed to use some artificial intelligence technique to select and cluster the Euler solutions whereas [Debeglia et al., 2006] proposed a semi-automatic method for structural and depth to sources analysis of potential field data.

The characterization of the crustal structure in areas of geodynamic interest by combining gravity with seismological information also attracted the interest of several groups. For instance [Tiberi et al., 2003] developed a joint inversion of seismic tomography and gravity anomalies and applied it to the Baikal rift area while other groups favored sequential inversion.

Whatever the chosen approach is, it must be noted that taking into account both gravity anomalies and seismic tomography yields to a much more realistic modeling of the inner Earth than using gravity or tomography data only.

In the field of computing software, a new version of the processing package CG3TOOL developed by [Gabalda et al., 2003] for processing Scintrex microgravity

data has been updated on PC environment [Beilin, 2005].

The dramatic improvement of geodetic and gravimetric measurements accuracy calls also for a new theoretical development in reference Earth model.

Indeed, till these studies, in order to model the elasto-gravitationnal deformation, only a simple spherical (at better ellipsoidal) radially stratified Earth was considered.

[Métivier, 2004], [Metivier et al., 2005, 2006] and [Greff-Lefftz, 2005] developed a new reference model which takes into account lateral density and rheology variations within the mantle. This model was later applied to predict tides and loading perturbations due to super-plumes and other large wavelength geodynamic features.