Seismic Network Operations


Raoul, Kermadec Islands

IU RAO commences operations on: 2004,200

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Host: Institute of Geological and Nuclear Sciences
Latitude: -29.245
Longitude: -177.929
Elevation: 60
Datalogger: Q680
Broadband: STS-1V/VBB
Accelerometer: FBA-23
Telemetry Status at the NEIC: Last Data In Less Than 10 Minutes
Station Photo Station Photo Station Photo Station Photo 

Site Description: Station is located on a 100m bluff on the small volcanic island.

Vault Condition: STS-2, STS-1 vertical and FBA-23 are located in a very shallow concrete vault.

Location CodeChannel CodeInstrumentFlagsSample RateDipAzimuthDepth
BC1STS-2 High-gainTG40.
00VK1Quanterra DA temperature monitorCW0.
00VE1Quanterra DA voltage monitorCW0.
10VHZSTS-2 High-gainCG0.10-
10VHNSTS-2 High-gainCG0.
10VHESTS-2 High-gainCG0.100.0090.000.50
10LHZSTS-2 High-gainCG1.00-
10LHNSTS-2 High-gainCG1.
10LHESTS-2 High-gainCG1.000.0090.000.50
10HHZSTS-2 High-gainTG80.00-
10HHNSTS-2 High-gainTG80.
10HHESTS-2 High-gainTG80.000.0090.000.50
10BHZSTS-2 High-gainCG40.00-
10BHNSTS-2 High-gainCG40.
10BHESTS-2 High-gainCG40.000.0090.000.50
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As part of the annual calibration process, the USGS runs a sequence that includes a random, a step, and several sine wave calibrations.  The USGS analyzes the random binary calibration signal in order to estimate the instrument response.  The figures below show the results from the analysis of the most recent processed calibration at the station.

We use an iterative three-step method to estimate instrument response parameters (poles, zeros, sensitivity and gain) and their associated errors using random calibration signals. First, we solve a coarse non-linear inverse problem using a least squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a non-linear parameter estimation problem to obtain the least squares best-fit Laplace pole/zero/gain model. Third, by applying the central limit theorem we estimate the errors in this pole/zero model by solving the inverse problem at each frequency in a 2/3rds-octave band centered at each best-fit pole/zero frequency. This procedure yields error estimates of the 99% confidence interval.

LocChanCal DateEpoch-SpanGradeAmp Nominal Error (dB)Amp Best Fit Error (dB)Phase Nominal Error (degree)Phase Best Fit Error (degree)SensorCal Type
10BHZ2006:111 2004:235 to 2009,221 A0.0155790.0149540.115330.12983 STS-2-HGRandom
00BHZ2006:110 2004:235 to 2009,221 B0.862160.0744712.76764.7495 STS1VVBBRandom
  1. 2013-05-17
    Upgraded to Q330 with STS-2 as primary and Trillium 240 as secondary. The STS-1 Z channel had not functioned since August 2009.