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Satellite Gravity Field Recovery Using Variance-Covariance Information From Ocean Tide Models

Hauk, Markus and Wilms, Josefine and Sulzbach, Roman and Panafidina, Natalia and Hart-Davis, Michael and Dahle, Christoph and Müller, Vitali and Murböck, Michael and Flechtner, Frank (2023) Satellite Gravity Field Recovery Using Variance-Covariance Information From Ocean Tide Models. Earth and Space Science, 10 (10). American Geophysical Union (AGU). doi: 10.1029/2023EA003098. ISSN 2333-5084.

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Official URL: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023EA003098

Abstract

Monthly gravity field recovery using data from the GRACE and GRACE Follow-On missions includes errors limiting the spatial and temporal resolution of the estimated gravity fields. The major error contributions, besides the noise of the accelerometer instruments, arise from temporal aliasing errors due to imperfections in the non-tidal atmospheric and oceanic de-aliasing models and ocean tide models. We derive uncertainty information for the eight major tidal constituents from five different ocean tide models and introduce it into the gravity field recovery process in terms of a constrained normal equation system while expanding the parameter space by additional tidal parameters to be adjusted. We prove the effectiveness of the ocean tide variance-covariance information through realistic simulations and we assess its potential based on microwave and laser interferometer observations from the GRACE Follow-On mission. We show that errors are reduced by more than 20% ocean wRMS for a Gaussian filter radius of 300 km if uncertainty information for ocean tides is considered and stochastic modeling of instrument errors is applied, compared to the latest GFZ release 6.1. Our results also show the limited visibility of the effectiveness of the ocean tide variance-covariance information due to the dominating error contribution of non-tidal atmospheric and oceanic mass variations. Additionally, we investigate the option of estimating ocean tide parameters over a 1-year period while including ocean tide uncertainty information in order to improve ocean tide background modeling.

Item URL in elib:https://elib.dlr.de/200746/
Document Type:Article
Title:Satellite Gravity Field Recovery Using Variance-Covariance Information From Ocean Tide Models
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Hauk, MarkusGFZ Potsdam, Max-Planck-Institut für Gravitationsphysik, Hannover, DLR Institut für Satellitengeodäsie und InertialsensorikUNSPECIFIEDUNSPECIFIED
Wilms, JosefineGFZ PotsdamUNSPECIFIEDUNSPECIFIED
Sulzbach, RomanGFZ Potsdam, FU BerlinUNSPECIFIEDUNSPECIFIED
Panafidina, NataliaGFZ PotsdamUNSPECIFIEDUNSPECIFIED
Hart-Davis, MichaelDGFI-TUM München und TUMUNSPECIFIEDUNSPECIFIED
Dahle, ChristophGFZ PotsdamUNSPECIFIEDUNSPECIFIED
Müller, VitaliMax-Planck-Institut für Gravitationsphysik, HannoverUNSPECIFIEDUNSPECIFIED
Murböck, MichaelGFZ Potsdam, TU BerlinUNSPECIFIEDUNSPECIFIED
Flechtner, FrankGFZ Potsdam, TU BerlinUNSPECIFIEDUNSPECIFIED
Date:12 October 2023
Journal or Publication Title:Earth and Space Science
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:10
DOI:10.1029/2023EA003098
Publisher:American Geophysical Union (AGU)
ISSN:2333-5084
Status:Published
Keywords:Application of variance-covariance information from ocean tide models in Level-2 satellite gravity field processing Reduction of temporal aliasing errors due to ocean tides in time-varying gravity field solutions Estimation of ocean tide parameters for an improved ocean tide background modeling
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Communication, Navigation, Quantum Technology
DLR - Research area:Raumfahrt
DLR - Program:R KNQ - Communication, Navigation, Quantum Technology
DLR - Research theme (Project):R - Data analysis, instrument characterization GRACE-FO
Location: Hannover
Institutes and Institutions:Institute for Satellite Geodesy and Inertial Sensing > Quantum Optical Sensing
Deposited By: Koch, Alexander
Deposited On:11 Dec 2023 15:44
Last Modified:29 Jan 2024 12:52

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