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Data-driven multi-step self-de-aliasing approach for GRACE and GRACE-FO data processing

Abrykosov, Petro und Murböck, Michael und Hauk, Markus und Pail, Roland und Flechtner, Frank (2022) Data-driven multi-step self-de-aliasing approach for GRACE and GRACE-FO data processing. Geophysical Journal International, 232 (2), Seiten 1006-1030. Oxford University Press. doi: 10.1093/gji/ggac340. ISSN 0956-540X.

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Offizielle URL: https://academic.oup.com/gji/article/232/2/1006/6677395

Kurzfassung

Temporal aliasing errors resulting from the undersampling of non-tidal atmospheric as well as oceanic mass variations constitute the largest limitation towards the retrieval of monthly gravity solutions based on GRACE and GRACE-FO satellite gravity missions. Their mitigation is thus a primary goal of current research. Unfortunately, the two-step co-parametrization approach proposed for application in Bender-type gravity retrieval scenario in Wiese et al. yields no added value for a single satellite pair. A detailed study of this parametrization strategy is carried out and it is shown that the reason for this is the flawed central assumption of the proposed method, that is that signals of different spatial wavelengths can be perfectly captured and separated with respect to their temporal extent. Based on this finding, we derive a multi-step self-de-aliasing approach (DMD) which aims to rectify the shortcoming of the Wiese et al. method specifically for the single-pair case while retaining its independence from background-model-based de-aliasing of non-tidal atmosphere and ocean (AO) signal components. The functionality and added value of this novel approach is validated within a set of numerical closed-loop simulations as well as in real GRACE and GRACE-FO data processing. The simulation results show that the DMD may improve the gravity retrieval performance in the high-degree spectrum by more than one order of magnitude if one aims to retrieve the full AOHIS (i.e. atmosphere, ocean, hydrology, ice, solid earth) signal, and by at least a factor 5 if a priori AO de-aliasing is applied. Simultaneously, the DMD is shown to degrade the retrieval of the low degrees, but it is also demonstrated that this issue can be mitigated by introducing a constraint into the processing scheme. The simulation results are widely confirmed by results obtained from applying the DMD to real GRACE/GRACE-FO data of the test years 2007, 2014 and 2019. The applicability of the DMD is further shown for Bender-type gravity retrieval. It is demonstrated that in case of a double-pair-based gravity retrieval this approach is at least equivalent to the Wiese et al. method.

elib-URL des Eintrags:https://elib.dlr.de/188924/
Dokumentart:Zeitschriftenbeitrag
Titel:Data-driven multi-step self-de-aliasing approach for GRACE and GRACE-FO data processing
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Abrykosov, PetroTUMNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Murböck, MichaelTU BerlinNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Hauk, MarkusDLR Institut für Satellitengeodäsie und InertialsensorikNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Pail, RolandTUMNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Flechtner, FrankGFZ PotsdamNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:26 August 2022
Erschienen in:Geophysical Journal International
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:232
DOI:10.1093/gji/ggac340
Seitenbereich:Seiten 1006-1030
Verlag:Oxford University Press
ISSN:0956-540X
Status:veröffentlicht
Stichwörter:Satellite gravity, Time variable gravity
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Kommunikation, Navigation, Quantentechnologien
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R KNQ - Kommunikation, Navigation, Quantentechnologie
DLR - Teilgebiet (Projekt, Vorhaben):R - Data analysis, instrument characterization GRACE-FO
Standort: Hannover
Institute & Einrichtungen:Institut für Satellitengeodäsie und Inertialsensorik > Quantenoptische Sensorik
Hinterlegt von: Koch, Alexander
Hinterlegt am:15 Dez 2022 09:37
Letzte Änderung:09 Feb 2024 08:06

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