Seismic Network Operations


Tsumeb, Namibia

IU TSUM commences operations on: 1994,231

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Host: Ministry of Mines and Energy
Latitude: -19.202
Longitude: 17.584
Elevation: 1260
Datalogger: Q330
Broadband: STS-1H/VBB
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: The vault is located above ground, constructed of concrete. The concrete pier is semi-isolated. Background noise, some caused by winds interacting with local towers, may be high occasionally.

Site Geology: Limestone

Location CodeChannel CodeInstrumentFlagsSample RateDipAzimuthDepth
30LDOIU Paroscientific MicrobarographCW1.
20LNZFBA ES-T EpiSensor AccelerometerCG1.00-
20LN2FBA ES-T EpiSensor AccelerometerCG1.000.0090.000.00
20LN1FBA ES-T EpiSensor AccelerometerCG1.
20HNZFBA ES-T EpiSensor AccelerometerTG100.00-
20HN2FBA ES-T EpiSensor AccelerometerTG100.000.0090.000.00
20HN1FBA ES-T EpiSensor AccelerometerTG100.
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.
10HHZSTS-2 High-gainTG100.00-
10HH2STS-2 High-gainTG100.000.0090.000.00
10HH1STS-2 High-gainTG100.
10BHZSTS-2 High-gainCG40.00-
10BH2STS-2 High-gainCG40.000.0090.000.00
10BH1STS-2 High-gainCG40.
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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
00BHZ2011:220 2010:203 to No Ending TiA0.0125380.0091220.0915790.11005 STS1HVBBRandom
00BH22011:220 2009:343 to No Ending TiA0.0172540.00937350.09910.11505 STS1HVBBRandom
00BH12011:220 2009:343 to No Ending TiA0.0228870.00936380.119590.14338 STS1HVBBRandom
10BHZ2011:221 2008:260 to No Ending TiA0.014570.0142020.101870.094578 STS-2-HGRandom
  1. 2008-09-16
    Upgraded to Q330 digitizer.