Things are starting to pick up here now that my professor and the postdocs are all back from their assorted adventures, so I have moved beyond just reading papers and watching computer tutorials. This week, I have spent a lot of time playing around with some of the existing MATLAB correlation and pre-processing programs, learning what they do, how they do it, and how it will be useful to me. I also wrote my first program, a simple method of stacking the correlations that come out of another program. My program is probably of questionable efficiency, since I am still quite new to this, but I can tell that in the process of making it, I have learned a lot about programming in MATLAB.
I have also begun to meet more of the people around here. I work in one corner of a large office, and the graduate students stationed in the other segments of the same office have all introduced themselves to me. When I mentioned to them that I was here through IRIS, I learned that two of the graduate students on this floor were also IRIS interns during their undergrad. Having such a network of IRIS alumni is really a cool thing.
Assignment #2: The datasets and tools with which I am working
The data with which I am working this summer is from the USArray, specifically from the Transportable Array stations between approximately 40° and 42° N. This continent-wide stripe runs from northern California on the west coast, through my hometown of Lincoln, Nebraska, and then on to my current location in Boston on the east coast. Someday, I should try to visit that area in northern California, just so I will have been on both ends and the middle of our area of interest. There are lots of researchers using USArray data, and for good reason; the USArray project is both widespread and comprehensive when it comes to how this country moves. We’re starting with the raw data, but luckily for me, most of the pre-processing functions have already been written and will only need parameter tweaking.
The primary weapon in my confrontation with the correlations is MATLAB. I will be using and editing code written by the postdocs and others, as well as writing some of my own, in order to piece together body waves from the ambient noise. Within MATLAB, I have use of the GISMO (Geophysical Institute Seismology MATLAB Objects) toolbox, a downloadable collection of functions designed for seismic trace analysis by University of Alaska Fairbanks professors. I have spent a fair bit of time over the past few days dissecting and playing around with GISMO’s correlations functions in order to figure out how best to apply them this summer.
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