Status of the IGS-TIGA Tide Gauge Data Reprocessing at GFZ
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The International GNSS Service (IGS) Tide Gauge Benchmark Monitoring Working Group (TIGA-WG) is responsible for analyzing GNSS data from stations at or near tide gauges (TG) on a preferably continuous basis and to provide information specifically for the vertical rates. The position and vertical velocity results of the stations can be applied in several geodetic and geophysical applications, such as global and regional sea-level change, calibration of satellite altimeters and the unification of height systems. As one of the TIGA Analysis Centers the German Research Centre for Geosciences (GFZ) is contributing to the IGS TIGA Reprocessing Campaign (TIGA REPRO2). The solutions of the GFZ TIGA REPRO2 will also contribute to IGS second Data Reprocessing Campaign (IGS REPRO2) with the GFZ IGS REPRO2 solution. Following the first IGS reprocessing finished in 2010 some improvements were implemented into the latest GFZ software version EPOS.P8: reference frame IGb08 based on ITRF2008, antenna calibration igs08.atx, geopotential model (EGM2008), higher-order ionospheric effects, new a priori meteorological model (GPT2), VMF mapping function, and other minor improvements. GNSS data of the globally distributed tracking network of 794 stations for the time span from 1994 until end of 2012 are used for the GFZ TIGA REPRO2. To handle such large networks a new processing strategy is developed and described in detail. In the GFZ TIGA REPRO2 the GNSS@TG data are processed in precise point positioning (PPP) mode to clean data using the GFZ IGS REPRO2 orbit and clock products. To validate the quality of the PPP coordinate results the rates of 80 GNSS@TG station vertical movement are estimated from the PPP results using Maximum Likelihood Estimation (MLE) method. The rates are compared with the solution of University of La Rochelle Consortium (ULR) (named ULR5). 56 of the 80 stations have a difference of the vertical velocities below 1 mm/year. The error bars of PPP rates are significantly larger than those of ULR5, which indicates large time correlated noise in the PPP solutions.
KeywordsPPP Reprocessing TIGA
We would like to thank the IGS and the SONEL data center (www.sonel.org) for providing GNSS observation data.
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