12B.2 Marshall Space Flight Center and the open-source radar software revolution

Thursday, 17 September 2015: 4:45 PM
University C (Embassy Suites Hotel and Conference Center )
Timothy J. Lang, NASA/MSFC, Huntsville, AL; and B. Dolan, B. Fuchs, P. Hein, E. Thompson, S. Collis, J. Helmus, and N. Guy

Handout (9.6 MB)

Within the radar meteorology community, a grass-roots movement has started to reshape how we produce, ingest, analyze, and display our data. There is a new focus on using open-source software toolkits that are collaboratively developed, well documented, and enforced with rigorous version control. NASA Marshall has begun to take a leadership role in this revolution by teaming up with researchers at several institutions to develop and test open-source radar analysis and display software. These object-oriented Python modules, many of which are currently available from https://github.com/nasa and https://github.com/tjlang, are easily installed and cover a wide range of scientific applications. These include ingesting, analyzing, and displaying NOAA national 3D radar mosaics (MMM-Py), as well as performing Doppler and polarimetric radar retrievals of aviation-related turbulence (PyTDA), low-level 2D winds (SingleDop), precipitation characteristics (DualPol), and radar beam blockage (PyBlock). Most of these packages integrate seamlessly with the Department of Energy led Python Atmospheric Radiation Measurement (ARM) Radar Toolkit (Py-ART), which is used for data ingest, supporting data quality control, the creation of new variable fields, and writing out processed data to file. A new Python module based on polarimetric radar retrievals developed at Colorado State University (CSU_RadarTools) also is used for processing data. This presentation will focus on how these NASA packages are being specifically used to advance the agency's science goals for a variety of missions. NASA Marshall's participation in other collaborative radar software development efforts, including contributions to Py-ART, ARTview, and PyRadarMet, also will be discussed.
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