Help: noise-psd v.1


The noise-psd web service returns Power Spectral Density estimates for seismic channels.


As the first of a two-step process for generating probability density function (PDF) plots of power spectral density for comparison with the Peterson (1993) noise models, these power spectral densities describe time series prior to instrument response removal. This intermediate storage step was introduced to minimize recalculation whenever instrument responses change. Power is in units of decibels (dB).

Peterson, J, 1993, Observations and Modeling of Seismic Background Noise, U.S.G.S. OFR-93-322


  1. Dividing the window into 13 segments having 75% overlap
  2. For each segment
    1. Removing the trend and mean
    2. Apply a 10% sine taper
    3. FFT
    4. Calculate the normalized PSD
  3. Average the 13 PSDs & scale to compensate for tapering
  4. Frequency-smooth the averaged PSD over 1-octave intervals at 1/8-octave increments
  5. Convert power to decibels


All formulae are described in
McNamara, D.E and Boaz, R.I., 2005, Seismic Noise Analysis System Using Power Spectral Density Probability Density Functions – A Stand-Alone Software Package, U.S.G.S. OFR 2005-1428.


  1. Channel constraints = currently {BH}H?, in future {LMBSEH}{HNL}? and {LB}G?
  2. Restricted data being accessed = No – Pending

Target Domain

One channel per measurement.

Data Preparation

  1. Data is provided by web services.
  2. Data is stamped quality ‘M’, meaning that overlapping segments are merged.
  3. Merged data segments have the highest SEED quality factor available.
  4. Data provided has not been corrected for instrument response; power is in units of decibels (dB).


  1. start = start time of averaged PSD window
  2. end = end time of the averaged PSD window
  3. f = frequency in Hz
  4. a = power in dB
  5. p = phase set to zero (PSDs are real-valued only)


The primary purpose of storing PSDs in this form is so that PDF generation can be performed using the latest metadata with a minimum amount of recalculation. The PDFs, in turn, can be used to evaluate the general noise characteristics of a channel, providing data quality information as a function of frequency.

Individual PSDs can be used to examine the spectral behavior of signal or noise within the PSD window. Keeping in mind that PDF plots represent multiple PSDs, a more detailed guide to interpreting features in PSDs and PDFs is available here:

Ambient Noise Probability Density Functions by Dan McNamara