Modeling spatial correlations in surface mass variations for terrestrial reference frame estimation
Abstract
In recent realizations of terrestrial reference frame (TRF), such as ITRF2014 and JTRF2014, non-tidal ground deformation parameters are co-estimated to improve the accuracy of the frame estimate. The traditional linear motion model for TRF is enhanced by additional ground motion models including post-seismic displacements as well as annual, semi-annual, and random ground deformations due to atmospheric, oceanic, and ground water storage loading. Although such motions are often regionally correlated, the ground deformation models used so far for TRF realizations are formulated to be strictly local in space. Here, we investigate application of the GRACE data to improve the TRF stochastic models by determining spatial statistics of the deformation of the Earth's surface caused by mass loading. The Kalman filter and smoother used to compute the JTRF2014 solution have been updated to incorporate the GRACE-based correlation data. The new filter/smoother realization, based on a square-root infromation filter (SRIF) algorithm, is also able to (1) avoid specification of fictitious covariance matrix to initialize the filter and (2) handle cross-temporal EOP data such as the week-long segments reported by the SLR and DORIS networks.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.G51B0585C
- Keywords:
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- 1217 Time variable gravity;
- GEODESY AND GRAVITY;
- 1218 Mass balance;
- GEODESY AND GRAVITY;
- 1225 Global change from geodesy;
- GEODESY AND GRAVITY;
- 1240 Satellite geodesy: results;
- GEODESY AND GRAVITY