Localized spectral analysis of global satellite gravity fields for recovering time-variable mass redistributions

Abstract

A spatiospectral localization method is discussed for processing the global geopotential coefficients from satellite mission data to investigate time-variable gravity. The time-variable mass variation signal usually appears associated with a particular geographical area yielding inherently regional structure, while the dependence of the satellite gravity errors on a geographical region is not so evident. The proposed localization amplifies the signal-to-noise ratio of the (non-stationary) time-variable signals in the geopotential coefficient estimates by localizing the global coefficients to the area where the signal is expected to be largest. The results based on localization of the global satellite gravity coefficients such as Gravity Recovery And Climate Experiment (GRACE) and Gravity and Ocean Circulation Explorer (GOCE) indicate that the coseismic deformation caused by great earthquakes such as the 2004 Sumatra-Andaman earthquake can be detected by the low-low tracking and the gradiometer data within the bandwidths of spherical degrees 15-30 and 25-100, respectively. However, the detection of terrestrial water storage variation by GOCE gradiometer is equivocal even after localization.

Satellite gravity gradiometry: Secular gravity field change over polar regions

“…A complementary measure is the degree variance of the gravity field solution in the presence of realistic noise. As the signals originate from a relatively small geographical region it is necessary to localise the signal and noise (Han and Simons, 2008;Han and Ditmar, 2008). In the terminology of Han and Ditmar (2008) the signal is non-stationary while the noise is more likely to be stationary.…”

“…As the signals originate from a relatively small geographical region it is necessary to localise the signal and noise (Han and Simons, 2008;Han and Ditmar, 2008). In the terminology of Han and Ditmar (2008) the signal is non-stationary while the noise is more likely to be stationary. Techniques of spatiospectral localization (Wieczorek and Simons, 2005) can enhance the signal as the effect decays rapidly outside the region of interest while the measurement errors are relatively uniform over the Earth.…”

“…(8) of Wieczorek and Simons, 2005) of spherical cap size  0 and expanded up to degree L h = 2 / 0 − 1 the SNR of the degree variances of the global gravity field solution and the localized solution are presented in Eqs. (3)-(8) of Han and Ditmar (2008). In this study we utilise both the SNR of the signal, where both measurement noise and signal are expanded in spherical harmonics, and the SNR on using a localized window centred on the source of the signal.…”

“…By utilising the distinct spatiotemporal spectra of the signal and error (e.g. Han and Simons, 2008;Han and Ditmar, 2008;Migliaccio et al, 2008) the signal-to-noise ratio over the polar regions can be enhanced. In this study we follow the approach of Han and Simons (2008) and Han and Ditmar (2008) where spatiospectral localization around the epicentre of the 2004 Sumatra-Andaman earthquake facilitated recovery of the geophysical signal even though the signature was unobservable in the original GRACE fields.…”

On the integral inversion of satellite-to-satellite velocity differences for local gravity field recovery: a theoretical study

“…Other authors have focused on improved analysis of available time-variable gravity field models, e.g. by mascon approach (Rowlands et al 2005), wavelets , spatiospectral localisation (Han and Ditmar 2008) or empirical orthogonal functions (Schmeer et al 2012). Note also that lots of studies have been done for regional gravity field recovery by inverting the satellite gradiometry data (see e.g.…”