Description
The noise-pdf web service returns Probability Density Functions (PDFs) for seismic channels.
Help Contents
- Summary
- Algorithm
- Plot Options
- Noise Profile Options
- Understanding Query Latency
- Notes on PSDs
- See Also
- Citations and DOIs
- Contact
Summary
Probability Density Functions (PDFs) can be useful for visualizing the characteristic noise levels of seismic data. The noise-pdf web service uses the Power Spectral Density (PSD) results from the noise-psd web service to construct PDFs. This service can return two formats:
- text or xml tabulating frequency/power bins and the count of PSD occurrences within those bins (“frequency, power, hits”), suitable for creating a histogram.
- PDF plot as described in McNamara and Buland (2004).
Algorithm
- Gather PSDs for requested station(s)-channel(s) and time period.
- Remove instrument transfer function from each PSD.
- Tabulate number of PSDs that fall into each combination of period (1/8 octave intervals) and power (1 dB intervals) bins. This information is stored in the database as described in the section Understanding Query Latency below.
- If text or xml output is requested, return tabulated values as “frequency, power, hits”.
- If plot output is requested, calculate the probability distribution and return a PDF plot.
Plot Options
There are many options available to customize the PDF plot output:
- New High and Low Noise Models (default = yes)
- Minimum, maximum, mode curves (default = yes)
- Legend for noise models, min/mode/max curves (default = yes)
- Legend for power color scale (default = no)
- Interpolation type (bicubic, bilinear, or none)
- Plot size in pixels
- Custom Title, subtitle, axis label
- Axes limits for frequency/period and power
- Choice of frequency or period x-axis labels (default=both)
- Font size for title, subtitle, or axes labels
Plot Examples
Basic Time Ranged Plot
../query?target=IU.ANMO.00.BHZ.M&starttime=2013-12-01&endtime=2013-12-31&format=plot
Basic Plot all time
../query?target=IU.ANMO.00.BHZ.M&format=plot
Basic Plot With Color Scale
../query?target=IU.ANMO.00.BHZ.M&starttime=2013-12-01&endtime=2013-12-31&format=plot&plot.scale.display=show
Multiple Channel Plot
../query?target=IU.ANMO.00.BH*.M…
Plot with Options
- Custom Size 1000 × 700 …plot.width=1000&plot.height=700…
- Custom Title …plot.title=Data+From+Station+ANMO+Channel+BHZ…
- Custom Size (1000×700) and font sizes …plot.titlefont.size=18&plot.subtitlefont.size=20&plot.labelfont.size=16
- No Subtitle …plot.subtitle=hide…
- Hide All Labels …plot.frequency.label=hide&plot.period.label=hide&plot.scale.label=hide&plot.power.label=hide…
- Hide All Axis …plot.frequency.axis=hide&plot.period.axis=hide&plot.scale.axis=hide&plot.power.axis=hide…
- Hide Frequency Axis …plot.frequency.axis=hide…
- Hide Legend …plot.legend=hide…
- Hide Model …plot.model=hide…
- Hide Min, Mode, Max …plot.minmodemax=hide…
- Hide Model and min, mode, max …plot.model=hide&plot.minmodemax=hide…
- 200 × 150 Thumbnail
- No Histogram Interpolation ..plot.interpolation=none…
- Hide the histogram ..plot.histogram=hide…
- Custom Axis Labels: …plot.power.label=dB&plot.frequency.label=Hertz&plot.period.label=Seconds&plot.scale.label=Percent…
- Custom Label Font Size …plot.labelfont.size=20…
- Custom Axis Font Size …plot.axisfont.size=20…
- Custom Title Font Size …plot.titlefont.size=30…
- Custom SubTitle Font Size …plot.subtitlefont.size=30…
Noise Profile Options
The format options format=noiseprofile_csvpipe
, format=noiseprofile_text
and format=noiseprofile_xml
output noise levels as a function of frequency (hertz) for various statistics.
Statistics are selected with the noiseprofile.type
parameter as a comma separated list.
Noise Profile Statistics.
Available noiseprofile.type
statistics are:
min |
minimum power | Equivalent to noiseprofile.type=0 |
max |
maximum power | Equivalent to noiseprofile.type=100 |
median |
median power | Equivalent to noiseprofile.type=50 |
mode |
most commonly occurring power | |
mean |
average mean power value | |
<0-100> |
percentile values. Must be integer from 0 to 100 |
Multiple statistics can be selected. For example: noiseprofile.type=5,95,mode
.
Noise Profile Formats
Three formats are available for output noise profiles
noiseprofile_csvpipe |
outputs a list of frequency-value comma (, ) separated tuples separated by pipe characters (| ). |
noiseprofile_text |
outputs a list of frequency-value comma (, ) separated tuples separated by newline characters. |
noiseprofile_xml |
outputs a list of frequency-value tuples separated in XML format |
Noise Profile Sample Queries
These queries are for IU.ANMO.00.BHZ
all time.
format=noiseprofile_csvpipe
…noiseprofile.type=mode&format=noiseprofile_csvpipe…
…noiseprofile.type=5,95&format=noiseprofile_csvpipe…
format=noiseprofile_text
…noiseprofile.type=mode&format=noiseprofile_text…
…noiseprofile.type=5,95&format=noiseprofile_text…
…noiseprofile.type=mean,mode,median,5,95&format=noiseprofile_text…
format=noiseprofile_xml
…noiseprofile.type=mode&format=noiseprofile_xml…
…noiseprofile.type=5,95&format=noiseprofile_xml…
…noiseprofile.type=mean,mode,median,5,95&format=noiseprofile_text…
Using Noise Profiles in the noise-mode-timeseries
service
The output generated by format=noiseprofile_csvpipe
can be fed to the noise-mode-timeseries webservice for comparing noise level variations over time and channels via the noise-mode-timeseries noisemodel.byfrequency
. Details of this feature are available HERE
Please note: the noise models input via the noisemodel.byfrequency
to the noise-mode-timeseries webservice, may only have one or two variables (types). If one variable is used, noise levels are differenced to this variable. If two variable are used, noise levels are differenced to the upper and lower values when above or below the variables and set to zero when in between. The following examples illustrate this behavior. These examples utilize the UNIX wget
command.
Example 1: Compare IU.ANMO.00.BHZ
noise levels to mean IU
BHZ
channel noise levels
1: Fetch the profile of mean values for all IU BHZ channels and save in file mean.txt
wget -O mean.txt "http://service.iris.edu/mustang/noise-pdf/1/query?target=IU.*.*.BHZ.M&format=noiseprofile_csvpipe&noiseprofile.type=mean&starttime=2010-01-01&endtime=2014-01-01"
2: Copy contents of file mean.txt
in unix-shell environment variable named MODEL
MODEL=`cat mean.txt`
3: Finally, call noise-mode-timeseries webservice with output=powerdnm
and noisemodel.byfrequency=${MODEL}
and save plot image in file anmo_delta_mean.png
wget -O anmo_delta_mean.png "http://service.iris.edu/mustang/noise-mode-timeseries/1/query?output=powerdnm&noisemodel.byfrequency=${MODEL}&plot.title=relative%20to%20mean&target=IU.ANMO.00.BHZ.M&starttime=2010-01-01&endtime=2014-01-01&format=plot"
Example 2: Compare IU.ANMO.00.BHZ
noise levels to 5% and 95% IU
BHZ
channel noise levels
1: Fetch the profile of 5% and 95% values for all IU BHZ channels and save in file model_5_95_percentile.txt
wget -O model_5_95_percentile.txt "http://service.iris.edu/mustang/noise-pdf/1/query?target=IU.*.*.BHZ.M&&format=noiseprofile_csvpipe&noiseprofile.type=5,95&starttime=2010-01-01&endtime=2014-01-01"
2: Copy contents of file model_5_95_percentile.txt
in unix-shell environment variable named MODEL
MODEL=`cat model_5_95_percentile.txt`
3: Finally, call noise-mode-timeseries webservice with output=powerdnm
and noisemodel.byfrequency=${MODEL}
and save plot image in file anmo_delta_5_95_percentile.png
wget -O anmo_delta_5_95_percentile.png "http://service.iris.edu/mustang/noise-mode-timeseries/1/query?output=powerdnm&noisemodel.byfrequency=${MODEL}&plot.title=relative%20to%20mean&target=IU.ANMO.00.BHZ.M&starttime=2010-01-01&endtime=2014-01-01&format=plot"
Understanding Query Latency
When a request is made to the web-service, the web service sends a series of queries to a backend SQL database. The results of those queries is compiled into a histogram which is returned as a plot, xml document or text document. The amount of time that a query takes is roughly proportional to the number of rows of data that must be returned from the database. There are two factors that determine the number of database rows that must be processed:
- The number of “targets” selected
- The time interval selected.
The number of targets selected is determined by what target
query option is and what targets have actually been measured in the given time range. Asking for targets that do not have measurements does not incur a significant penalty. For example, if a query had the target selection target=AA.*.*.*.M
and the AA network had many different channel codes, but only BHZ
, BH1
, BH2
were measured by the mustang system, only these channels would be processed by web-service. Requesting target=AA.*.*.BH*.M
would result in the same number of rows being processed and would take the same amount of time for the webservice to process.
Understanding how the data is stored in the database helps to make sense of the effect of the selected time interval (starttime
and endtime
). The data is stored in 5 date range tiers:
- Day
- Week
- Month
- Year
- All-time
When an arbitrary time interval is selected, rows are retrieved from these 5 tiers to fill the selected time range in the most efficient manner possible. For example consider the request:
starttime=2013-11-29&endtime=2015-02-07
Assuming data is available to completely cover this time interval, this request would be filled by retrieving rows for the following dates:
Interval | Dates | Rows |
---|---|---|
Day | 2013-11-29, 2013-11-30 | 2 |
Week | 2015-02-01 | 1 |
Month | 2013-12, 2015-01 | 2 |
Year | 2014 | 1 |
total rows: | 6 |
If the selected time interval was:
starttime=2013-01-01&endtime=2015-01-01
Only 2 rows would need to be processed: 2013, 2014
If no time interval is selected or if the time interval is wider than the available measurements, only the all-time interval row needs to be processed.
The actual total number of rows processed will be the product of date range row count and effective targets selected count.
Notes on PSDs
Detailed information about the PSD estimates used by noise-pdf can be found at http://service.iris.edu/mustang/noise-psd/docs/1/help/. The algorithm for these PSD estimates follows NcNamara and Boaz (2005).
These PSDs were smoothed to reduce variance. During smoothing, there is a tradeoff between enhancing frequency resolution and reducing variance of the PSDs (i.e. increasing repeatability). This choice gives a clearer general picture of station noise by reducing power smear, it is consistent with steps used to generate the Peterson new high and low noise models to which they are being compared, and it optimizes data storage. Consequently, narrow-bandwidth features will appear smeared across frequencies in these PSDs.
While the smoothing applied to the MUSTANG PSDs is appropriate for quality assurance purposes, it may not meet the needs of other objectives. In particular, Anthony et al. (2020) addresses the effects of various processing methodologies for PSDs and their usage.
See Also
dead_channel_lin,
pct_above_nhnm, pct_below_nlnm,
noise-psd
Citations and DOIs
To cite the MUSTANG system or reference the use of MUSTANG metrics:
- Assuring the Quality of IRIS Data with MUSTANG
Robert Casey, Mary E. Templeton, Gillian Sharer, Laura Keyson, Bruce R. Weertman, Tim Ahern
Seismological Research Letters (2018) 89 (2A): 630-639.
DOI:10.1785/0220170191
The following links describe the use of Probability Density Function (PDF) plots.
- Ambient Noise levels in the Continental United States
Daniel E. McNamara and Raymond P. Buland
Bulletin of the Seismological Society of America (2004) 94 (4): 1517-1527.
DOI:10.1785/012003001
Contact
Problems with this service?
Please send an email report of which service you were using, your URL query, and any error feedback to:
data-help@earthscope.org
We will address your issue as soon as possible.