Validation of the EGSIEM GRACE gravity fields using GNSS coordinate timeseries and in-situ ocean bottom pressure records

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dc.identifier.uri http://dx.doi.org/10.15488/4301
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/4335
dc.contributor.author Chen, Qiang
dc.contributor.author Poropat, Lea
dc.contributor.author Zhang, Liangjing
dc.contributor.author Dobslaw, Henryk
dc.contributor.author Weigelt, Matthias
dc.contributor.author van Dam, Tonie
dc.date.accessioned 2019-01-11T08:57:41Z
dc.date.available 2019-01-11T08:57:41Z
dc.date.issued 2018
dc.identifier.citation Chen, Q.; Poropat, L.; Zhang, L.; Dobslaw, H.; Weigelt, M. et al.: Validation of the EGSIEM GRACE gravity fields using GNSS coordinate timeseries and in-situ ocean bottom pressure records. In: Remote Sensing 10 (2018), Nr. 12, 1976. DOI: https://doi.org/10.3390/rs10121976
dc.description.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. eng
dc.language.iso eng
dc.publisher Basel : MDPI AG
dc.relation.ispartofseries Remote Sensing 10 (2018), Nr. 12
dc.rights CC BY 4.0
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject Combined solutions eng
dc.subject EGSIEM eng
dc.subject GNSS time series eng
dc.subject GRACE eng
dc.subject In-situ OBP records eng
dc.subject Validation eng
dc.subject Data handling eng
dc.subject Geodetic satellites eng
dc.subject Global positioning system eng
dc.subject Indium compounds eng
dc.subject Oceanography eng
dc.subject Risk management eng
dc.subject Signal to noise ratio eng
dc.subject Time series eng
dc.subject Combined solution eng
dc.subject Coordinate time series eng
dc.subject EGSIEM eng
dc.subject Global geopotential models eng
dc.subject Global Navigation Satellite Systems eng
dc.subject GRACE eng
dc.subject Gravity Recovery and Climate Experiment missions eng
dc.subject Validation eng
dc.subject In situ processing eng
dc.subject.ddc 620 | Ingenieurwissenschaften und Maschinenbau ger
dc.title Validation of the EGSIEM GRACE gravity fields using GNSS coordinate timeseries and in-situ ocean bottom pressure records
dc.type article
dc.type Text
dc.relation.issn 2072-4292
dc.relation.doi https://doi.org/10.3390/rs10121976
dc.bibliographicCitation.issue 12
dc.bibliographicCitation.volume 10
dc.bibliographicCitation.firstPage 1976
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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