SAGE Facility MUSTANG metrics Web Service Documentation

RETIRED as of 01/01/2019. New values are not being calculated and the metric itself will be removed in the near future.

The dead_channel_exp metric is calculated by fitting the PSD mean curve for the current day to an exponential curve and calculating the standard deviation of the residuals. The mean of a healthy set of broadband PSDs will have a very non-exponential shape with large residuals near the microseism peaks, while a “dead channel” will typically mimic an exponential decay curve as a function of log(period). Before fitting the exponential decay curve, the dead_channel_exp metric trims a few frequency bins from either end of the PSD mean curve to eliminate the effects of sparse sampling at the channel’s shortest and longest periods.

Healthy channels are characterized by large measurements, whereas dead channels are characterized by small standard deviations. A value < 0.3 typically indicates a dead broadband channel.

Small values for this metric can flag dead (or otherwise unhealthy) channels caused by offline sensors, sensor malfunction, datalogger malfunction and pegged sensor masses.

Traces – one N.S.L.C (Network.Station.Location.Channel) per measurement
Window – up to 24 hours depending on the completeness of data
Data Source – IRIS SEED archive

SEED Channel Types – [BCDFH]H? | High Gain

• Retrieve the PSD mean as a function of period for the current day.
• Trim the period range to span (4/sample rate) to 100 seconds.
• Convert the PSD mean to positive, non-zero values and take the base 10 log.
• Fit the base 10 [log(PSD mean) ~ log(period)] curve to a line.
• Calculate the standard deviation of the residuals of the log(PSD mean) vs. log(period) linear fit:
  

  value = sqrt [ average( BestFitLine(Ti) - log(PSDmean(Ti)) ) ]  for i = 1,…,N
  

value – the standard deviation of the residuals of the log(PSD mean) vs. log(period) fit
target – the trace analyzed, labeled as N.S.L.C.Q (Network.Station.Location.Channel.Quality)
start – time of the first sample of time series data for that day in UTC
end – time of the last sample of time series data for that day in UTC
lddate – date/time the measurement was made and loaded into the MUSTANG database (UTC)