There's a different way to look at seismic records that is particularly
interesting for microseisms.  For a long time I've been using the 
specgram function of Matlab to look at both microseisms and quakes.  
Specgram essentially divides the signal record into blocks of time 
and performs an FFT on each block.  It then displays the FFT amplitude 
as a gray scale (or other color map).  The Y axis of the display is 
increasing frequency, the X-axis is time, and brightness of each pixel 
corresponds to the amplitude of the signal at that time and frequency.
Essentially you get an image showing how each frequency component changes
with time.  

This type of display is frequently used in speech analysis, passive sonar,
and probably other fields.  This is not to be confused with the simple
FFT function implemented by many of the data acquisition programs that
gives a line of amplitude versus frequency, and which is useless 
by comparison.  

I was amazed at the different information available in this type 
of display compared with looking at a time series.  You can see 
amplitude and frequency shifts of the microseisms (presumably as 
storms change location and intensity).  You can see frequency shifts 
of the (dispersed) surface waves of a quake as it arrives.  
I have identified quakes by looking at the specgram display that I 
couldn't make out looking at the time series because they were buried 
in high-frequency noise.

You can also see interesting higher-frequency signals, including line 
spectra that shift and come and go mysteriously (probably cultural noise 
of some type).

The representation allows you to easily distinguish body and surface waves 
by their spectra, but because the FFT is done on blocks of data it is 
not useful for calculating very accurate arrival times.

If anyone's interested I can dig out some old data and post a picture.  It 
would be pretty easy to implement the algorithms in one of the data 
acquisition/display programs....

Jack

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