Estimation of background noise level on seismic station using statistical analysis for improved analysis accuracy

Abstract:

We evaluated the background noise level of seismic stations in order to collect the observation data of high quality and produce accurate seismic information. Determining of the background noise level was used PSD (Power Spectral Density) method by McNamara and Buland (2004) in this study. This method that used long-term data is influenced by not only innate electronic noise of sensor and a pulse wave resulting from stabilizing but also missing data and controlled by the specified frequency which is affected by the irregular signals without site characteristics. It is hard and inefficient to implement process that filters out the abnormal signal within the automated system. To solve these problems, we devised a method for extracting the data which normally distributed with 90 to 99% confidence intervals at each period. The availability of the method was verified using 62-seismic stations with broadband and short-period sensors operated by the KMA (Korea Meteorological Administration). Evaluation standards were NHNM (New High Noise Model) and NLNM (New Low Noise Model) published by the USGS (United States Geological Survey). It was designed based on the western United States. However, Korean Peninsula surrounded by the ocean on three sides has a complicated geological structure and a high population density. So, we re-designed an appropriate model in Korean peninsula by statistically combined result. The important feature is that secondary-microseism peak appeared at a higher frequency band.

Acknowledgements:

This research was carried out as a part of "Research for the Meteorological and Earthquake Observation Technology and Its Application" supported by the 2015 National Institute of Meteorological Research (NIMR) in the Korea Meteorological Administration.