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Summary

The IRIS DMC Noise Toolkit Microseism Energy (ME) bundle is a collection of 3 Python scripts that are configurable and allow users to conveniently calculate and plot microseism energy temporal variations in the period band of interest using the available PSD values. By default, the bundle is configured to to calculate ME over 1-5 s band, targeting smaller local storms for coastal stations, 5-10 s for the secondary microseisms, 11-30 s for the primary microseisms and the 50-200 s band for the Earth hum using PSDs of three-component broadband seismic data (BH channels). The stored microseism energy values will be smoothed using a median sliding time window (e.g. 6 hours, 12 hours, 1 day, 4 days, and 16 days, etc.).

Figure below is a sample of 6-hour median microseism energy temporal variations plot of the BHZ channel at GSN stations IU.GUMO for the secondary microseism period band of 5 to 10 seconds as affected by the passage of Typhoon Vongfong (formed on October 2, 2014 and dissipated on October 18, 2014). For more examples, visit Microseism Energy Quick Look (MEQL) highlights.

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The scripts included in this bundle are:

  1. ntk_computePower.py – a Python script to calculate power of each PSD window (by default 1 hour) over selected bin period bands
  2. ntk_medianPower.py – a Python script to calculates median power from the PSD powers (by default hourly PSD power) using a sliding window of a given length (e.g., 12 hours)
  3. ntk_plotPower.py – a Python script to plot median powers computed from a series of PSD powers

PSDs of seismic station waveform data needed for computation of the microseism energy are available from IRIS DMC via:

  • Noise Toolkit PDF-PSD bundle — an open-source Python script bundle to compute PSDs
  • PSDs computed by IRIS’s automated Quality Analysis Control Kit (QUACK) system

Contributions

We welcome patches and enhancements to this software. When developing patches, please pay particular attention to ease of use and maintenance and also keep dependencies to a minimum (contact the project).

Credits

  • RIS DMC Products Team
  • Rob Anthony and Rick Aster (New Mexico Tech and Colorado State University)

Metadata

  • Category: Data Processing
  • Language: Python
  • Keywords:

    noise-toolkit, psd, microseism-energy

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Manager: Manochehr Bahavar