Seismic Network Operations
College Outpost, Alaska, USA
IU COLA commences operations on: 1996,166
|Host:||University of Alaska|
|Telemetry Status at the NEIC:||Last Data In Less Than 10 Minutes|
Vault Condition: The surface vault is climate controlled. The concrete pier is isolated from the floor of the vault.
Site Geology: The borehole is drilled into approximately 50 meters of various types of silt and loess. A colluvium layer exists between approximately 55 and 61 meters. Beneath the colluvium to 102 meters there are various types of granitic rocks, from felsic granitic finely grained rock to, at deeper sections, a highly altered granite. From 103 meters to 122 meters lithologies range from phyllite to calc phillite to quartzite at the bottom of the borehole. The surface vault sits atop the silt and loess deposits.
|Location Code||Channel Code||Instrument||Flags||Sample Rate||Dip||Azimuth||Depth|
|20||LN2||FBA ES-T EpiSensor Accelerometer||CG||1.00||0.00||90.00||0.00|
|20||HN2||FBA ES-T EpiSensor Accelerometer||TG||100.00||0.00||90.00||0.00|
|20||LNZ||FBA ES-T EpiSensor Accelerometer||CG||1.00||-90.00||0.00||0.00|
|20||LN1||FBA ES-T EpiSensor Accelerometer||CG||1.00||0.00||0.00||0.00|
|20||HNZ||FBA ES-T EpiSensor Accelerometer||TG||100.00||-90.00||0.00||0.00|
|20||HN1||FBA ES-T EpiSensor Accelerometer||TG||100.00||0.00||0.00||0.00|
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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.
|Loc||Chan||Cal Date||Epoch-Span||Grade||Amp Nominal Error (dB)||Amp Best Fit Error (dB)||Phase Nominal Error (degree)||Phase Best Fit Error (degree)||Sensor||Cal Type|
|00||BHZ||2012:032||2011:026 to No Ending Ti||A||0.027734||0.0066069||0.080347||0.11102||54000||Random|
|00||BH2||2012:032||2011:026 to No Ending Ti||A||0.058429||0.01167||0.13489||0.26067||54000||Random|
|00||BH1||2012:032||2011:026 to No Ending Ti||A||0.0074055||0.0049954||0.059153||0.050355||54000||Random|
|10||BHZ||2012:033||2011:027 to No Ending Ti||A||0.01545||0.014218||0.12242||0.11671||STS-2-HG||Random|
2012-09-24The KS54000 was replaced due to failure of multiple components.
2012-04-10Episensor replaced due to noise issues.
2009-07-09Upgraded to Q330 digitizer.