Seismic Network Operations

IU ULN

Ulaanbaatar, Mongolia

IU ULN commences operations on: 1994,304

Country Flag
Host: Mongolia Academy of Science
Latitude: 47.865
Longitude: 107.053
Elevation: 1610
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 

Vault Condition: The vault is located inside a concrete basement of a building. The pier rests on the basement floor.

Site Geology: Paleozoic schist and Mesozoic granite.

Location CodeChannel CodeInstrumentFlagsSample RateDipAzimuthDepth
00VHZSTS-1V/VBBCG0.10-90.000.000.00
00VHNSTS-1H/VBBCG0.100.000.000.00
00VHESTS-1H/VBBCG0.100.0090.000.00
10SHZGS-13CG40.00-90.000.000.00
10SHNGS-13CG40.000.000.000.00
10SHEGS-13CG40.000.0090.000.00
20LNZFBA-23CG1.00-90.000.000.00
20LNNFBA-23CG1.000.000.000.00
20LNEFBA-23CG1.000.0090.000.00
00LHZSTS-1V/VBBCG1.00-90.000.000.00
00LHNSTS-1H/VBBCG1.000.000.000.00
00LHESTS-1H/VBBCG1.000.0090.000.00
20HNZFBA-23TG80.00-90.000.000.00
20HNNFBA-23TG80.000.000.000.00
20HNEFBA-23TG80.000.0090.000.00
10EHZGS-13TG80.00-90.000.000.00
10EHNGS-13TG80.000.000.000.00
10EHEGS-13TG80.000.0090.000.00
00BHZSTS-1V/VBBCG20.00-90.000.000.00
00BHNSTS-1H/VBBCG20.000.000.000.00
00BHESTS-1H/VBBCG20.000.0090.000.00
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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
00BHZ2012:058 2009:261 to No Ending TB0.0370650.0370650.341340.34132 STS1VVBBRandom
00BHN2012:058 2009:261 to No Ending TB0.0382450.0367830.343230.3401 STS1HVBBRandom
00BHE2012:058 2009:261 to No Ending TB0.0399040.0369980.345310.34471 STS1HVBBRandom
  1. 2013-09-29
    Upgraded to Q330 digitizer. STS-1 seismometers rebuilt to correct previously lowered response at long periods (greater than 50s).