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Discriminating between tectonic transients and processing artifacts in GNSS displacement time series: A case study from the Cascadia subduction margin

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/persons/resource/garcia

Garcia,  Cristian
1.1 Space Geodetic Techniques, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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

/persons/resource/maennelb

Männel,  B.
1.1 Space Geodetic Techniques, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

/persons/resource/sglaser

Glaser,  S.
1.1 Space Geodetic Techniques, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

/persons/resource/schuh

Schuh,  H.
1.1 Space Geodetic Techniques, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Zitation

Garcia, C., Bedford, J., Männel, B., Glaser, S., Schuh, H. (2023): Discriminating between tectonic transients and processing artifacts in GNSS displacement time series: A case study from the Cascadia subduction margin, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-3634


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5020908
Zusammenfassung
Throughout the earthquake cycle at fault zones, Earth's crust undergoes deformations. GNSS coordinate time series reveals tectonic motion, seismic displacements, and periodic signatures. Additional motion patterns are usually summarized as transient tectonic signals, i.e., unexpected accelerations with respect to standard trajectory models. As the number of permanent stations increases and as time series grow, we are increasingly able to recognize transient tectonic signals. Since some of these suspected tectonic transients have subtle magnitudes or sometimes unusual spatiotemporal features, we need to develop methods for determining which transients are artifacts and which are of a tectonic origin.Here, we investigate the impact of certain GNSS processing choices and how they affect the appearance of transients in the GNSS displacement time series solutions. In our study, we choose data from Cascadia, a region for which the occurrence of transients in the GNSS time series is well known. To control our database, we processed data based on network solutions from 150 carefully selected GNSS stations for the time between 2015 and 2020. Then, we have an opportunity to discriminate between tectonic transients and processing artifacts in the GNSS displacement time series. We will discuss the detected transients against selected GNSS-related indicators (data quality, observation residuals, troposphere delays, etc.) to identify potential GNSS artifacts aliasing into the transient signals.