Thread: Three new MUSTANG metrics are now available: max_range, sample_rate_channel, and sample_rate_resp

Started: 2020-06-19 08:24:30
Last activity: 2020-06-19 08:24:30
Topics: MUSTANG QA
Dear Mustang Users,

We are pleased to announce the addition of three new metrics to MUSTANG: max_range, sample_rate_channel, and sample_rate_resp. We are now computing these metrics for incoming data and have begun the process of calculating values back through the data archive. We will send out another announcement when we have completed coverage of the entire archive. You can request values for these metrics through the MUSTANG measurements web service at http://service.iris.edu/mustang/measurements/1/.

1. max_range

The max_range metric computes the difference between the minimum and maximum sample value (range) in a rolling 300-second window, reporting the largest range value in counts found in a daily 24-hour period.

This metric can help characterize the largest seismic or noise-related signal over the course of a day, excluding extremely long period signals. This may be useful for identifying stations that have large sensor pings, spikes, or other recurrent signals that, e.g., may potentially cause false STA/LTA triggers in an earthquake early warning system.

2. sample_rate_channel

The sample_rate_channel metric is a Boolean indicator that compares the sample rate recorded in the miniSEED fixed header to the channel metadata sample rate. If the sample rates disagree by more than 1%, sample_rate_channel is 1 (TRUE). Otherwise it is 0 (FALSE). It is computed daily. This metric checks whether a channel’s metadata correctly describes its sample rate.

3. sample_rate_resp

The sample_rate_resp metric is a Boolean indicator that compares the sample rate recorded in the miniSEED fixed header to the sample rate estimated from the high-frequency rolloff of the metadata amplitude-frequency response curve. If the sample rates disagree by more than 15%, sample_rate_resp is 1 (TRUE). Otherwise it is 0 (FALSE). It is computed daily.

This metric checks whether a channel’s instrument response correctly describes its sample rate. FIR filtering produces a high-frequency corner near 0.85*Nyquist. Not only will sample_rate_resp catch responses that describe a different sample rate, but it will also flag responses that omit FIR filter stages.

Best regards,
Gillian Sharer
IRIS Quality Assurance



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