Calculation of Station-Representative Isotropic Receiver Functions

  • Seongryong Kim
  • Junkee RhieEmail author


The estimation of one-dimensional (1-D) isotropic structures is routine work in most receiver function (RF) analyses that generally use a reference radial RF (RRF) for each station. However, the assumption of negligible back-azimuthal dependencies in a set of RRFs for a station may not be valid because of anisotropic layering, dipping structures, or incorrect sensor orientations. This work presents a comprehensive procedure to obtain a station-representative isotropic RRF, which can be applied automatically to prepare RRF data. The method incorporates a harmonic stripping method with a grid-search for sensor orientations. An optimum angle for the sensor orientation is determined by searching for the angle that minimizes the energy in the tangential component RF (TRF). For each searched angle, possible effects by anisotropy and dipping structures are iteratively suppressed by an inversion process to exclude two- and four-robe back-azimuthal patterns. The performance of the method was first confirmed with a test using a set of highly noisy composite RRFs and TRFs. The method was then applied to RF data from the southern Korean Peninsula and southwestern Japan. Obtained isotropic RRFs and measured station orientations were found to be reliable in comparisons with results from neighboring stations and previous studies. As an automatized routine pre-process, the obtained isotropic RRF data are particularly useful for estimating 1-D isotropic structures in migration or inversion studies, which are potentially affected by back-azimuthal dependencies in RF data calculated through conventional averaging methods.


Isotropic receiver function harmonic stripping station orientation Korean Peninsula F-net 



The authors are appreciative of Benoit Tauzin and Jung-Ung Woo for valuable discussions about the method. This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea (No. 20132510100060). We used data from broadband stations operated by the Korea Institute of Geoscience and Mineral Resources, Korea Meteorological Administration, and F-net.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Earth and Environmental SciencesSeoul National UniversitySeoulRepublic of Korea
  2. 2.Department of Geology and Earth Environmental SciencesChungnam National UniversityDaejeonRepublic of Korea

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