@misc{ZaliReinKruegeretal.2023,
  author    = {Zali, Zahra and Rein, Teresa and Kr{\"u}ger, Frank and Ohrnberger, Matthias and Scherbaum, Frank},
  title     = {Ocean bottom seismometer (OBS) noise reduction from horizontal and vertical components using harmonic-percussive separation algorithms},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1320},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-58882},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-588828},
  pages     = {15},
  year      = {2023},
  abstract  = {Records from ocean bottom seismometers (OBSs) are highly contaminated by noise, which is much stronger compared to data from most land stations, especially on the horizontal components. As a consequence, the high energy of the oceanic noise at frequencies below 1 Hz considerably complicates the analysis of the teleseismic earthquake signals recorded by OBSs. Previous studies suggested different approaches to remove low-frequency noises from OBS recordings but mainly focused on the vertical component. The records of horizontal components, which are crucial for the application of many methods in passive seismological analysis of body and surface waves, could not be much improved in the teleseismic frequency band. Here we introduce a noise reduction method, which is derived from the harmonic-percussive separation algorithms used in Zali et al. (2021), in order to separate long-lasting narrowband signals from broadband transients in the OBS signal. This leads to significant noise reduction of OBS records on both the vertical and horizontal components and increases the earthquake signal-to-noise ratio (SNR) without distortion of the broadband earthquake waveforms. This is demonstrated through tests with synthetic data. Both SNR and cross-correlation coefficients showed significant improvements for different realistic noise realizations. The application of denoised signals in surface wave analysis and receiver functions is discussed through tests with synthetic and real data.},
  language  = {en}
}