Using Python to Store, Display, and Analyze Pressure Observations from Earthscope's USArray Network

The Earthscope US Transportable Array (USArray) is a seismic network of over 400 active stations currently located over the eastern continental United States. Stations are semi-uniformly spaced about 70 km apart, deployed at a location for approximately two years, and then moved to the eastern edge of the grid for redeployment. The stations were outfitted in 2010 while over the Central Plains with pressure sensors capable of providing observations at a frequency of 1 Hz.

These observations are being collected, archived, and displayed by the University of Utah for research as well as passed on via MADIS for use in operational weather prediction models. Python was chosen to accomplish these tasks due to its object-oriented nature and ability to handle large datasets. PyTables is being used to archive millions of pressure observations collected per day since 2010 in an efficient and accessible manner. Using this archive, pressure perturbation time series are being created for each station using filtering techniques from SciPy to identify meteorological pressure disturbances such as cyclogenesis events, severe convection, and gravity waves. Analyses of pressure perturbation frequencies have been generated using Python packages, including NumPy, matplotlib, and basemap. Finally, Python is employed for web displays and pressure perturbation calculations for active USArray stations in real-time.