Microseism Variation with Pelagic Storms

I have been curious about the source of microseisms on my seismograph since I completed it in 2004. I initially dismissed the explanation that they originated from intense ocean storms but after watching those storms online and comparing to my seismograph traces there is convincing qualitative evidence for that explanation. This past winter I decided to try to collect some data for a closer look. I began collecting data on January 08, 2020 at 12:00 UTC. I have a continuous record of the significant wave height in the Atlantic Basin and a fairly complete record of the microseism record as described below through the end of April and will continue to collect data going forward. This post will describe what I am doing and will introduce the results obtained in January through a short video. I am working on merging datasets and starting a statistical evaluation of the data so I hope some interesting things will come out of it.

An article in Geophysical Research Letters titled ‘Stormquakes’ pointed me to the portal to NOAA’s WaveWatch III gridded ocean surfce model results. Information on the NOAA website showed how to access and use data from the model. I modified the example Python script to access and map the significant wave height data in the North Atlantic Ocean Basin. This runs every six hours as cron job, automatically acquiring, mapping, and filing this information.

I also wrote a small Python script to calculate the standard deviation of 30 minute segments of the seismic trace from the previous 24 hours. I use the trace standard deviation to characterize the amplitude of the microseisms.  The chart below shows the trace standard deviation changes, plotted in blue, for the month of January 2020.   Several earthquakes occurred which appear as the larger narrow spikes in the data.  The shorter spikes are due to foot traffic in the house.

Those spikes are of no interest in the present study.  What is really of interest is the envelope of the underside of this graph described by the minimum values.  Because I only have the ocean surface information at six hour intervals I evaluate the minimum value of the trace standard deviation on the eleven 30 minute trace segments centered on each of the hours 00, 06, 12, and 18 UTC.  These values are plotted as the red line in the graph.

A very near minimum and the maximum value of the red line occur only three days apart, on January 15 and January 18, respectively.  Here are the 24 hour helicorder charts for the two days.

 

And the Significant Wave Height during the same days:

 

The Geophysics Research Letters paper referenced earlier specifically associate The Grand Banks off the coast of Newfoundland with stormquakes.  This particular example seems to support that association.  I hope that my long term study will give a little more structure to what we see here.  In the meantime here is a short video showing the progression of January’s winter storms across the North Atlantic.

 

Whence Microseisms?

 

8_11_2016

Normal Seismogram

10_8_2016

Noisy Seismogram showing Microseisms

 

 

 

 

 

 

 

In the twelve years or so that I have been observing earth motions on my home built seismograph I have been puzzled by the occasional appearance of noisiness in the seismometer trace. I have read about these microseisms and tried unsuccessfully to identify a source of them. The literature always identifies storms at sea as the main cause but I discounted that explanation because of my location in Ohio and the fact that I don’t have a professional, broadband seismometer. So I looked at local wind speeds and wind gusts buffeting the house or moving the trees so much that their roots move. I have looked at local barometric pressure and temperature changes even monitoring the temperature inside the enclosure which contains my seismometer. I have wondered whether there is something in my amplifier electronics that might explain these tiny signals. Nothing worked out.

Earlier this month, I noticed that they were back and that they were growing quite strong. Then it occurred to me that Hurricane Matthew was approaching the east coast of Florida at the same time. Maybe the microseisms I see can be attributed to storms at sea!

I began a closer look at this by downloading time series data about the hurricane from the National Hurricane Center ftp site.  I wrote a python script to load the data from the downloaded file and plot the track of Hurricane Matthew and other information I thought might be important such as the maximum sustained wind, central pressure, and the distance of the eye from my home in Millersburg, Ohio which I calculated from the location data.

matthew_track

Note that P0 marks the location of the seismograph in Millersburg, Ohio.

I also downloaded a bundle of specialized microseism analysis tools from the IRIS (Incorporated Research Institutes for Seismology) software site.  This software is designed for advanced study using professional grade, broadband, multi-channel seismographs.  As such, I have most likely not applied it correctly, in fact bypassed important calculations, etc.  Having said that I hope that the “relative” analysis I did shows some direction toward a qualitative relationships between storms at sea and the microseisms I see recorded on my seismograph.  Here is what I found.

microseis_plot1

This data includes Local, Secondary, and Primary Microseism energy.  I chose to use the Primary band data since they all show similar qualitative response.  Hurricane Matthew dissipated  on Oct 10 and the NHC data file was closed and no more data was added.  More on that later.  I snipped the microseism graph off at Oct 10 and compared to the Hurricane central pressure and distance to the eye:

matthew_actualdata

Actual (non-inverted) data

This is a little hard to visualize in part because one would think that the microseism energy might be inversely related to both the distance and the central pressure.  We can look at the same information taking this into account by plotting the reciprocal of both quantities:

matthew_inverted

Inverted data (see text)

The last chart is the closest to correlated data that I have seen in twelve years or so of trying to figure this out.  Not perfect due to many known and unknown reasons but something for me now to be aware of when I see this noisiness show up.

The proximity of the storm seems predominant.  The central pressure seems to lead the microseism energy.  And finally, the original microseism graphs that went out to Oct 13 showed the noise staying high long after the NHC downgraded the storm.  Presumably, the ocean does not calm immediately after the storm dissipates.  An unmentioned complication in this study is that Hurricane Nicole was also present and strengthening during this time period further out in the Atlantic.

Magnitude 4.0 – YOUNGSTOWN-WARREN URBAN AREA, OHIO

A Magnitude 4.0 earthquake was reported this afternoon at 20:04:58 UTC in northeastern Ohio.  This is in the same area as a sequence of earthquakes thought to be associated with injection wells used to dispose of oil drilling waste fluids.  The injection wells operations were suspended yesterday by the state of Ohio and the operator of the well.

Even though my seismograph in Millersburg, OH  is not well suited to picking up local earthquakes and the display has been quite noisy the last few days, with a small amount of processing I did pick up a signal that appears to be caused by the earthquake in question.

The USGS arrival time information is shown:

DATE-(UTC)-TIME    LAT    LON     DEPTH MAG   Q   COMMENTS
2011/12/31 20:04:58  41.16N  80.73W   2.2 4.0      us: YOUNGSTOWN-WARREN AREA,

delta   azimuth (degrees clockwise from north)
(deg)      eq-to-station     station-to-eq
1.06          236.2              55.4

travel   arrival time
#  code      time(s)  dy hr mn sec
1  Pg          20.39   0 20  5 18
2  sPg         20.92   0 20  5 18
3  Pb          21.09   0 20  5 19
4  pPb         21.44   0 20  5 19
5  sPb         21.83   0 20  5 19
6  Pn          21.88   0 20  5 19
7  pPn         22.41   0 20  5 20
8  sPn         22.74   0 20  5 20
9  Sg          35.19   0 20  5 33
10  Sb          36.46   0 20  5 34
11  sSb         37.05   0 20  5 35
12  Sn          38.13   0 20  5 36
13  sSn         39.00   0 20  5 37
14  PcP        510.96   0 20 13 28
15  ScP        722.84   0 20 17  0
16  PcS        723.12   0 20 17  1
17  ScS        935.02   0 20 20 33
18  PKiKP      994.23   0 20 21 32
19  pPKiKP     994.99   0 20 21 32
20  sPKiKP     995.27   0 20 21 33
21  SKiKP     1206.10   0 20 25  4
22  PKKPdf    1917.27   0 20 36 55
23  SKKPdf    2129.14   0 20 40 27
24  PKKSdf    2129.42   0 20 40 27
25  SKKSdf    2341.29   0 20 43 59
26  P'P'df    2428.55   0 20 45 26
27  S'S'df    3276.86   0 20 59 34

Postscript:

Several people have asked me about the triggering of earthquakes by hydraulic fracturing and waste injection wells.  The USGS has a FAQ page on the subject.

Magnitude 6.6 – QUEEN CHARLOTTE ISLANDS REGION

A strong Magnitude 6.6 earthquake struck the Queen Charolette Islands region off the west coast of Canada at 15:30:46 UTC on November 17, 2009.  Because it was shallow, the surface waves were quite strong and were clipped on my seismograph here in northeatern Ohio.  The two types of surface waves, the Love and Rayleigh waves, are also very well delineated in their arrivals, which is often not the case.

The arrival time information from the USGS is included below:

  DATE-(UTC)-TIME    LAT    LON     DEPTH MAG   Q   COMMENTS
  2009/11/17 15:30:46  52.15N 131.38W  11.6 6.6      US: QUEEN CHARLOTTE ISLANDS
   Expected 20s period surface wave amplitude [  1.07E+02 µm]  [  3.36E+01 µm/s]
   Expected 1s period body wave amplitude     [  8.99E-01 µm]  [  5.65E+00 µm/s]

delta   azimuth (degrees clockwise from north)
(deg)      eq-to-station     station-to-eq
35.41           89.1             306.0

                 travel   arrival time
    #  code      time(s)  dy hr mn sec
    1  P          415.68   0 15 37 41
    2  pP         419.26   0 15 37 45
    3  sP         420.80   0 15 37 46
    4  PnPn       494.28   0 15 39  0
    5  PP         496.11   0 15 39  2
    6  PnPn       498.58   0 15 39  4
    7  PnPn       498.59   0 15 39  4
    8  PP         514.92   0 15 39 20
    9  PcP        565.21   0 15 40 11
   10  S          751.10   0 15 43 17
   11  pS         755.35   0 15 43 21
   12  sS         757.22   0 15 43 23
   13  ScP        790.89   0 15 43 56
   14  PcS        792.36   0 15 43 58
   15  SnSn       891.40   0 15 45 37
   16  SS         906.01   0 15 45 52
   17  SS         939.25   0 15 46 25
   18  PKiKP     1006.43   0 15 47 32
   19  pPKiKP    1010.42   0 15 47 36
   20  sPKiKP    1011.88   0 15 47 37
   21  ScS       1035.38   0 15 48  1
   22  SKiKP     1217.87   0 15 51  3
   23  PKKPdf    1901.07   0 16  2 27
   24  SKKPdf    2112.52   0 16  5 58
   25  PKKSdf    2113.98   0 16  5 59
   26  SKKSdf    2325.36   0 16  9 31
   27  P'P'df    2407.79   0 16 10 53
   28  P'P'ab    2498.68   0 16 12 24
   29  S'S'df    3259.19   0 16 25  5
   30  LQ         898.62   0 15 45 44
   31  LR         997.34   0 15 47 23