Deutsch
 
Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Konferenzbeitrag

De-Leakaging and De-Striping of GRACE-based Surface Mass Distributions by Regularization Methods

Urheber*innen

Graf,  Matthias
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Schlaak,  Marius
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Pail,  Roland
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Externe Ressourcen
Es sind keine externen Ressourcen hinterlegt
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte in GFZpublic verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Graf, M., Schlaak, M., Pail, R. (2023): De-Leakaging and De-Striping of GRACE-based Surface Mass Distributions by Regularization Methods, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-1470


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017128
Zusammenfassung
Temporal aliasing and leakage effects limit the resolution of satellite gravity solutions. On the one hand the limited temporal sampling and the anisotropic observation geometry causes temporal aliasing, which manifests in a typical stripping pattern. On the other hand, the truncation of spherical harmonic series, which corresponds to a limited spatial resolution, causes mass changes to be falsely assigned to nearby regions. These assignments are partly physically unreasonable. In this study, we develop a method that allows to reduce the leakage effect in GRACE gravity fields. In our method, we separate the entire Earth’s surface according to their surface type as e.g. sea and land surface. Across these regions, we apply individual basis functions applied. In a constrained least squares adjustment, a priori surface mass trends are rearranged to the respective regions while we constrain the basis functions’ coefficients differently according to their surface type. Therefore, we assume different variabilities. With the inclusion of a filter matrix, the resulting field of redistributed mass changes is linked to the a priori distribution which results directly from the input gravity field. First, we use an iterative search for optimal regularization and filter parameters while we simulate GRACE-like gravity fields from Earth System Models. The original model serves as a truth, which the redistributed mass is compared to. Since we assume a sufficient similarity between our simulated and real GRACE gravity fields, we apply the optimal set of parameters in order to de-leakage and to de-alias those gravity fields.