Open Source Software Projects for Various Radar Platforms

With file formats, naming conventions, and aging platforms, working with weather radar data has been a notoriously difficult endeavor until recently. Tools for plotting and analyzing radar data have existed generally at an institutional or proprietary level. Community tools, such as Solo II/3, have been indispensible. However, they do not necessarily take advantage of modern computing technologies and address the shift of academic and government institutions to open source platforms for cost savings, performance, and development flexibility. Great strides have been made in this area recently and momentum continues to grow to develop the next generation of software for weather radar data analysis. This presentation introduces ongoing work on three separate open source software projects – the ARM Radar Toolkit Viewer (ARTView), the Aircraft Weather Observations Toolkit (AWOT), and PyRadarMet.

The Atmospheric Radiation Measurement (ARM) Climate Research Facility acquired six weather radars near 2009 with various file formats and sampling strategies. The inability to process these data with “off-the-shelf” tools led to the development of the Python – ARM Radar Toolkit (Py-ART). This software package continues to grow and develop with both dedicated developers and community involvement. ARTView takes advantage of this quickly developing package that is able to read a large majority of file types and put them in a standard data structure. ARTView began as a relatively simple graphical user interface (GUI) display that allowed a user to browse through volumes of weather radar data with simple keyboard and mouse navigation. Functionality continues to be developed within ARTView, from basic zoom/pan and point selection to more advanced editing modules by connecting to internal Py-ART modules. (https://github.com/nguy/artview)

Internal software within the National Oceanic & Atmospheric Administration (NOAA) National Severe Storms Laboratory (NSSL) was heavily developed in the 1990s to support research using the NOAA P-3 aircraft platform. A scanning, tail radar is of special interest to the research community, as it provides an unprecedented view of precipitating storms. Special challenges exist when dealing with airborne observations, such as correcting for platform motion and projecting the data onto a Cartesian surface. The NSSL package depends upon software libraries with diminishing to no development and support. AWOT uses the open source Python environment to create visualization plots of weather radar, ambient environmental variables along track and dropsonde data not only for the NOAA -3, but also has the capability of reading and displaying data from the University of Wyoming King Air (UWKA), the LATMOS French Falcon, and the University of North Dakota Citation aircraft. Various processing algorithms for radar data are in development, including geo-referencing, coordinate interpolation, and dual-Doppler retrievals. A sounding component is available within the package, as well as reading ground based radar data via a connection to the Py-ART package. (https://github.com/nguy/AWOT)

PyRadarMet is a Python toolbox of fundamental weather radar calculations, meant to be useful in the planning phase and during field project deployments. Many basic calculations are provided by the easy access python interface. In addition, a geometric terrain beam-block fraction calculation and ZDR bias calculation module is provided. This package has been ported to an R-package as well as being implemented into the wradlib open source package for radar data processing. (https://github.com/nguy/PyRadarMet)