Power Spectral Density (PSD)

Probability Density Functions (PDF)Seismic Data QC,

Network Design Tool and Capability Modeling

Developers:

Dan McNamara, Ray Buland @ ANSS NOC

Richard Boaz @ Boaz Consultancy

Others involved:

Harold Bolton, Jerry Mayer @ ANSS IDCC

Paul Earle, Harley Benz, Rob Wesson @ ANSS NEIC

Tim Ahern , Bruce Weertman @ IRIS DMC

Individual histograms for each period

are converted to PDFs by normalizing

each

power bin by total number of

observations.

Total distribution of powers plotted.

Not simply minimum powers.

PSD Probability Density Function for ISCO

BHZ

Method: Power Spectral Density Probability Density Functions

Raw waveforms continuously extracted from waveserver

In 1 hour segments, overlapping by 50%.

PSD pre-processing:

trend and mean removal

10% cos taper applied

No screening for earthquakes, or transients and

instrumental glitches such as data gaps, clipping, spikes,

mass re-centers or calibration pulses

PSD calculated for each 1 hour segment

With ASL algorithm for direct comparison

to NLNM.

PSD is smoothed by averaging powers over

full octaves in 1/8 octave intervals.

Points reduced from 16,385 to 93.

Center points of octave averages shown.

Power Frequency Distribution Histograms

PSDs are accumulated in 1dB power

bins

from -200 to -50dB.

Distributions are generated for each

period

in 1/8 octave period intervals.

Histograms vary significantly by period.

- 1s has strong peak and a narrow

range of powers.

- bimodal distributions at 10, 100s

-All have sharp low-power floor with

higher power tails

Next step:

Convert histograms to

Probability Density Functions

QuickTime™ and a

TIFF (Uncompressed) decompressor

are needed to see this picture.

HLID - automobile traffic along

a dirt road only 20 meters from

station HLID creates a 20-30dB

increase in power at about 0.1

sec period (10Hz). This type of

cultural noise is observable in

the PDFs as a region of low

probability at high frequencies

(1-10Hz, 0.1-1s).

Body waves occur as low

probabily signal in the 1sec

range while surface waves are

generally higher power at

longer periods.

Automatic mass re-centering

and calibration pulses show up

as low probability occurrences

in the PDF.

Artifacts in the Noise Field

Current Noise PDF Uses

Network SOH monitoring

Dead station

Detection Modeling

Design Planning

Station Quality

Site quality

Current stations

future backbone

ANSS Rankings

Noise Research

sources

hurricanes

ambient noise model

Hailey, ID 08/2001-05/2002

McNamara and Buland (2004) BSSA

Realistic view of noise conditions at a station. Not simply lowest levels experienced.

Current Noise PDF Uses

Network SOH monitoring

Dead station

Detection Modeling

Design Planning

Station Quality

Site quality

Current stations

future backbone

ANSS Rankings

Noise Research

sources

hurricanes

ambient noise model

GOTO:

ANSS QC

http://gldqc/cgi-bin/pdf

IRIS DMC

http://www.iris.washington.edu/servlet/quackqu

ery/

Lightning strike hours after

Station began operation

Current Noise PDF Uses

Network SOH monitoring

Dead station

Detection Modeling

Design Planning

Station Quality

Site quality

Current stations

future backbone

ANSS Rankings

Noise Research

sources

hurricanes

ambient noise model

Current Noise PDF Uses

Network SOH monitoring

Dead station

Detection Modeling

Design Planning

Station Quality

Site quality

Current stations

future backbone

ANSS Rankings

Noise Research

sources

hurricanes

ambient noise model

Brune minimum Mw Mw

Regional Network Simulation6 stations from NM regional network with

well established noise baselines.

Detection threshold lowered in

New Madrid region by 0.1-0.3 units

with addition of NM network.

Regional Station Limitations:

- high noise in Cultural noise band (1-10Hz)

- PVMO instrumented with Guralp CMG-

3esp seismometer (50Hz) and Quanterra Q-

380 digitizer at 20sps. Power rolloff at

Nyquist~10Hz.

PVMO

Mw

Backbone Stations on Satellite GR4

Backbone stations on Satellite SM5

Detection Maps Used for Prioritization of Maintenance Issues

Mw

ANSS backbone distributed

over 2 satellites to protect

against total network

outage.

Simulations demonstrate

detection in the event of a

satellite failure.

Maintenance decisions

could be made based on

real-time changes in

detection thresholds.

GR4 expected to die within

3 years.

QuickTime™ and a

TIFF (Uncompressed) decompressor

are needed to see this picture.

QuickTime™ and a

TIFF (Uncompressed) decompressor

are needed to see this picture.

3km from train 20km from train

Current Noise PDF Uses

Network SOH monitoring

Dead station

Detection Modeling

Design Planning

Station Quality

Site quality

Current stations

future backbone

ANSS Rankings

Noise Research

sources

hurricanes

ambient noise model

Meremonte, M., D. McNamara, A. Leeds, D. Overturf, J. McMillian,

and J. Allen, ANSS backbone station installation and site

characterization, EOS Trans. AGU, 85(47), 2004.

Current Noise PDF Uses

Network SOH monitoring

Dead station

Detection Modeling

Design Planning

Station Quality

Site quality

Current station

future backbone

ANSS Rankings

Noise Research

sources

hurricanes

ambient noise model

GSN Standing Committee Report:

An Assessment of Seismic Noise

Characteristics for the ANSS Backbone

and Selected Regional Broadband Stations

By D. McNamara, Harley M. Benz and W.

Leith

Also

McNamara, D.E., H.M. Benz and W. Leith,

USGS Open-File Report, in press, 2005.

Current Noise PDF Uses

Network SOH monitoring

Dead station

Detection Modeling

Design Planning

Station Quality

Site quality

Current station

future backbone

ANSS Rankings

Noise Research

sources

hurricanes

ambient noise models

McNamara, D.E., R.P. Buland, R.I. Boaz, B. Weertman, and T. Ahern, Ambient

seismic noise, Seis. Res. Lett., in press, 2005.

Plans for future development: QDAT

Database hourly PSDs to allow:

creative selection of data for PDF generation

Playback as a movie (i.e. graphic equalizer)

Additional types of visualizations

Regional noise trends

diurnal and seasonal variations

Research

noise sources

baselines

auto ID of problem artifacts

Operations

vault design

telemetry performance

automated problem reporting and

notification

QuickTime™ and a

TIFF (Uncompressed) decompressor

are needed to see this picture.

Hurricanes

QuickTime™ and a

TIFF (Uncompressed) decompressor

are needed to see this picture.

Seismometer casing differential motion

Plans for future development: QDAT

Database hourly PSDs to allow:

creative selection of data for PDF generation

Playback as a movie (i.e. graphic equalizer)

Additional types of visualizations

Regional noise trends

diurnal and seasonal variations

spectograms

Research

noise sources

baselines

auto ID of problem artifacts

Operations

vault design

telemetry performance

automated problem reporting and

notification

Plans for future development: QDAT

Database hourly PSDs to allow:

creative selection of data for PDF generation

Playback as a movie (i.e. graphic equalizer)

Additional types of visualizations

Regional noise trends

diurnal and seasonal variations

spectograms

Research

noise sources

baselines

auto ID of problem artifacts

Operations

vault design

telemetry performance

automated problem reporting and

notification

QuickTime™ and a

TIFF (Uncompressed) decompressor

are needed to see this picture.

Regional Noise Characteristics

Plans for future development: QDAT

Database hourly PSDs to allow:

creative selection of data for PDF generation

Playback as a movie (i.e. graphic equalizer)

Additional types of visualizations

Regional noise trends

diurnal and seasonal variations

spectograms

Research

noise sources

baselines

auto ID of problem artifacts

Operations

vault design

telemetry performance

automated problem reporting and

notification

6am local time

Noise across all periods increases 10-15dB during the working day

with the exception of the microseism band (~7-8s).

Constructed from

90th percentile

computed from

PDFs binned for

each hour of the

day.

Data from

Sept 2001 to

Oct 2004

Short period noise increases during the summer months.

Microseism band (~7-8s) noise increases during the fall and winter.

Constructed from

90th percentile

computed from

PDFs binned for

each month of

the year.

Data from

Sept 2001 to

Oct 2004

School begins

Plans for future development: QDAT

Database hourly PSDs to allow:

creative selection of data for PDF generation

Playback as a movie (i.e. graphic equalizer)

Additional types of visualizations

Regional noise trends

diurnal and seasonal variations

spectograms

Research

noise sources

baselines

auto ID of problem artifacts

Operations

vault design

telemetry performance

automated problem reporting and

notification

Noise Baselines: Which Statistic?

Mode, Average or Median

Plans for future development: QDAT

Database hourly PSDs to allow:

creative selection of data for PDF generation

Playback as a movie (i.e. graphic equalizer)

Additional types of visualizations

Regional noise trends

diurnal and seasonal variations

spectragrams

Research

noise sources

baselines

auto ID of problem artifacts

Operations

vault design

telemetry performance

automated problem reporting and notification