Seismic Network Operations


Midway Island, USA

IU MIDW commences operations on: 1999,296

Country Flag
Host: US Fish and Wildlife Service
Latitude: 28.216
Longitude: -177.37
Elevation: 20
Datalogger: Q330
Broadband: STS-2_High-gain
Accelerometer: none
Telemetry Status at the NEIC: Last Data In Less Than 10 Minutes
Station Photo Station Photo Station Photo Station Photo 

Vault Condition: STS-2 is in a shallow vault (1.0M)

Location CodeChannel CodeInstrumentFlagsSample RateDipAzimuthDepth
00BHZStreckeisen STS-2 High-gainCG40.00-
00BH2Streckeisen STS-2 High-gainCG40.000.0090.001.00
00BH1Streckeisen STS-2 High-gainCG40.
00HHZStreckeisen STS-2 High-gainTG100.00-
00HH2Streckeisen STS-2 High-gainTG100.000.0090.001.00
00HH1Streckeisen STS-2 High-gainTG100.
31LDOCI/PAS pressure sensorCW1.
30LDOlower quality chip sensor in Setra boxCW1.
00LHZStreckeisen STS-2 High-gainCG1.00-
00LH2Streckeisen STS-2 High-gainCG1.000.0090.001.00
00LH1Streckeisen STS-2 High-gainCG1.
00VMWStreckeisen STS-2 High-gainCH0.
00VMVStreckeisen STS-2 High-gainCH0.
00VMUStreckeisen STS-2 High-gainCH0.
00VHZStreckeisen STS-2 High-gainCG0.10-
00VH2Streckeisen STS-2 High-gainCG0.100.0090.001.00
00VH1Streckeisen STS-2 High-gainCG0.
PDF, All
Image Unavailable

PDF, Last Month
Image Unavailable

PDF, Month
Image Unavailable

PDF, Current Week
Image Unavailable

PDF, Year
Image Unavailable

Image Unavailable
Image Unavailable

Availability, Year
Image Unavailable

Availability, Since 1972
Image Unavailable

Availability, 2 Month
Image Unavailable

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
00BHZ2011:005 2009:211 to No Ending TB0.0616490.0613570.327760.33749 STS-2-HGRandom
  1. 2013-07-28
    Upgraded to Q330 digitizer.