Title
Validation of the EGSIEM GRACE Gravity Fields Using GNSS Coordinate Timeseries and In-Situ Ocean Bottom Pressure Records.
Abstract
Over the 15 years of the Gravity Recovery and Climate Experiment (GRACE) mission, various data processing approaches were developed to derive time-series of global gravity fields based on sensor observations acquired from the two spacecrafts. In this paper, we compare GRACE-based mass anomalies provided by various processing groups against Global Navigation Satellite System (GNSS) station coordinate time-series and in-situ observations of ocean bottom pressure. In addition to the conventional GRACE-based global geopotential models from the main processing centers, we focus particularly on combined gravity field solutions generated within the Horizon2020 project European Gravity Service for Improved Emergency Management (EGSIEM). Although two validation techniques are fully independent from each other, it is demonstrated that they confirm each other to a large extent. Through the validation, we show that the EGSIEM combined long-term monthly solutions are comparable to CSR RL05 and ITSG2016, and better than the other three considered GRACE monthly solutions AIUB RL02, GFZ RL05a, and JPL RL05.1. Depending on the GNSS products, up to 25.6% mean Weighted Root-Mean-Square (WRMS) reduction is obtained when comparing GRACE to the ITRF2014 residuals over 236 GNSS stations. In addition, we also observe remarkable agreement at the annual period between GNSS and GRACE with up to 73% median WRMS reduction when comparing GRACE to the 312 EGSIEM-reprocessed GNSS time series. While the correspondence between GRACE and ocean bottom pressure data is overall much smaller due to lower signal to noise ratio over the oceans than over the continents, up to 50% agreement is found between them in some regions. The results fully confirm the conclusions found using GNSS.
Year
DOI
Venue
2018
10.3390/rs10121976
REMOTE SENSING
Keywords
Field
DocType
EGSIEM,GRACE,combined solutions,validation,GNSS time series,in-situ OBP records
Time series,Remote sensing,Signal-to-noise ratio,Ocean bottom,Global Positioning System,GNSS applications,Geology,Group method of data handling
Journal
Volume
Issue
ISSN
10
12
2072-4292
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Qiang Chen111.38
Lea Poropat200.34
Liangjing Zhang300.34
Henryk Dobslaw4172.44
Matthias Weigelt500.68
Tonie van Dam610.70