Seismic Network Operations


Riachuelo, Brazil

IU RCBR commences operations on: 1999,060

Country Flag
Host: University of Rio Grande do Norte
Latitude: -5.827
Longitude: -35.901
Elevation: 400
Datalogger: Q330
Broadband: KS-54000
Accelerometer: FBA_ES-T_EpiSensor_Accelerometer
Telemetry Status at the NEIC: Last Data In Less Than 10 Minutes
Station Photo Station Photo Station Photo 

Vault Condition: N/A, KS54000 borehole depth is -109.0m. CMG depth is -37m.

Location CodeChannel CodeInstrumentFlagsSample RateDipAzimuthDepth
20LNZFBA ES-T EpiSensor AccelerometerCG1.00-
20LN2FBA ES-T EpiSensor AccelerometerCG1.000.0090.000.00
20LN1FBA ES-T EpiSensor AccelerometerCG1.
10VHZSTS-2 High-gainCG0.10-
10VH2STS-2 High-gainCG0.100.0090.000.00
10VH1STS-2 High-gainCG0.
10LHZSTS-2 High-gainCG1.00-
10LH2STS-2 High-gainCG1.000.0090.000.00
10LH1STS-2 High-gainCG1.
10BHZSTS-2 High-gainCG40.00-
10BH2STS-2 High-gainCG40.000.0090.000.00
10BH1STS-2 High-gainCG40.
20HNZFBA ES-T EpiSensor AccelerometerTG100.00-
20HN2FBA ES-T EpiSensor AccelerometerTG100.000.0090.000.00
20HN1FBA ES-T EpiSensor AccelerometerTG100.
10HHZSTS-2 High-gainTG100.00-
10HH2STS-2 High-gainTG100.000.0090.000.00
10HH1STS-2 High-gainTG100.
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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
00BH12011:068 2009:210 to No Ending TA0.0537680.0276310.928120.85453 54000Random
00BH22011:068 2009:210 to No Ending TA0.0371660.0223870.864610.8137 54000Random
00BHZ2011:068 2009:210 to No Ending TA0.0462610.0264180.93040.86735 54000Random
10BHZ2011:069 2009:210 to No Ending TA0.0226860.0132730.139310.085953 STS-2-HGRandom
  1. Current Issues
    LNZ channel appears to be bad. The STS-2 continues to exhibit high noise levels. The KS54000 has become excessively noisy as of Feb. 2012.
  2. 2009-08-03
    Upgraded to Q330 digitizer.