Dispersion curves, phase velocity maps and shear-wave velocity model for Scandinavia based on teleseismic Rayleigh surface waves and ambient noise

DOI

The data set consists of dispersion curves and the corresponding 2D phase velocity maps based on earthquake generated Rayleigh surface waves and ambient noise, as well as the resultant shear-wave velocity model for entire Scandinavia (Norway, Sweden and Finland). We resolved the crust and mantle to 250 km depth to provide new insight into the maintenance of the Paleozoic Scandes mountain range and the lithospheric architecture of the Precambrian Baltic Shield (Mauerberger et al., in review). For this study, we use the virtual ScanArray network which consists of more than 220 seismic stations of the following contributing networks: The ScanArray Core (1G network, Thybo et al., 2012) consists of 72 broadband instruments which were operated by the ScanArray consortium (Thybo et al., 2021) between 2013-2017. We also used 28 stations from the NEONOR2 (2D network), 20 stations from the SCANLIPS3D (ZR network; England et al., 2015), 72 permanent stations from the Swedish National Seismic Network (SNSN; UP network; SNSN 1904) as well as further 35 permanent stations from the Finnish (HE and FN networks), Danish (DK network), Norwegian (NO network (NORSAR, 1971); NS (University of Bergen, 1982)) and international IU network (ALS/USGS, 1988). Since the exact operation times of the different temporary networks differ, we analyse data between 2014 and 2016, when most of the stations were operational. The pre-processing of the data involved the removal of a linear trend, application of a band-pass filter between 0.5 s and 200 s, downsampling to 5 Hz and deconvolution of the instrument response to obtain velocity seismograms. We also corrected for the misorientations stated in Grund et al., 2017.

Identifier
DOI https://doi.org/10.5880/GFZ.2.4.2022.001
Related Identifier https://doi.org/10.7914/SN/II
Related Identifier https://doi.org/10.1111/j.1365-246X.2007.03374.x
Related Identifier https://doi.org/10.5880/GFZ.2.4.2019.001
Related Identifier https://doi.org/10.1029/157GM06
Related Identifier https://doi.org/10.2312/GFZ.b103-17029
Related Identifier https://doi.org/10.14470/UR044600
Related Identifier https://doi.org/10.1111/j.1365-246X.2012.05698.x
Related Identifier https://doi.org/10.1093/gji/ggv297
Related Identifier https://doi.org/10.21348/d.no.0001
Related Identifier https://doi.org/10.1016/j.cageo.2017.09.006
Related Identifier https://doi.org/10.18159/SNSN
Related Identifier https://doi.org/10.1093/gji/ggaa168
Related Identifier https://doi.org/10.14470/6T569239
Related Identifier https://doi.org/10.1785/0220210015
Related Identifier https://doi.org/10.7914/SN/NS
Metadata Access http://doidb.wdc-terra.org/oaip/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:doidb.wdc-terra.org:7595
Provenance
Creator Mauerberger, Alexandra (ORCID: 0000-0002-4866-993X); Sadeghisorkhani, Hamzeh ORCID logo; Valérie, Maupin ORCID logo; Olafur, Gudmundsson ORCID logo; Frederik, Tilmann ORCID logo
Publisher GFZ Data Services
Contributor Mauerberger, Alexandra
Publication Year 2022
Funding Reference Deutsche Forschungsgemeinschaft, LITHOS CAPP DFG Gz TI 316 3 1 and 2
Rights CC BY 4.0; http://creativecommons.org/licenses/by/4.0/
OpenAccess true
Contact Mauerberger, Alexandra (GFZ German Research Centre for Geosciences, Potsdam, Germany)
Representation
Resource Type Model
Discipline Geosciences
Spatial Coverage (3.000W, 54.000S, 38.000E, 71.000N); Norway, Sweden, Finland