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Correction of Hydrological and Oceanic Effects from GRACE Data by Combination of the Steric Sea Level, Altimetry Data and GLDAS Model
In this study, a scheme to estimate oceanic and hydrological effects in the GRACE (Gravity Recovery and Climate Experiment) data is presented. The aim is to reveal tectonic signals for the case of the Sumatra earthquake on 26 December 2004. The variations of hydrological and oceanic effects are esti...
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Published in: | Acta geophysica 2016-08, Vol.64 (4), p.1193-1210 |
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creator | Fatolazadeh, Farzam Voosoghi, Behzad Raoofian Naeeni, Mehdi |
description | In this study, a scheme to estimate oceanic and hydrological effects in the GRACE (Gravity Recovery and Climate Experiment) data is presented. The aim is to reveal tectonic signals for the case of the Sumatra earthquake on 26 December 2004. The variations of hydrological and oceanic effects are estimated with the aid of data set of GRACE, altimetry, World Ocean Atlas, and the GLDAS model for a period of January 2003 to December 2006. The time series of computed gravity changes over Sumatra region show some correlations to the deformation resulting from the earthquake occurred in December 2004. The maximum and minimum impacts of hydrological and oceanic effects on gravity changes are about 3 μGal in radial direction and–5 μGal in northward direction. The maximum and minimum amounts of gravitational gradient changes after the correction are 0.2 and–0.25 mE, which indicates the significant influences of hydrological and oceanic sources on the desired signal. |
doi_str_mv | 10.1515/acgeo-2016-0034 |
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subjects | Altimetry Earth and Environmental Science Earth Sciences Earthquakes Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences GLDAS model GRACE data gravitational gradient changes Gravity hydrological and oceanic effects Plate tectonics Seismic activity Seismology Structural Geology World Ocean Atlas |
title | Correction of Hydrological and Oceanic Effects from GRACE Data by Combination of the Steric Sea Level, Altimetry Data and GLDAS Model |
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