172 ARTView Towards an Open Source Graphical User Interface for Radar Data

Tuesday, 29 August 2017
Zurich (Swissotel Chicago)
Anderson Luis Gama, Univ. of Stuttgart, Stuttgart, Germany; and N. Guy

Handout (2.4 MB)

Weather radar data has been notoriously difficult to work with in the past, leading to proprietary or single use software. Recently, a shift of academic and government institutions to open source platforms for cost savings, performance, and development flexibility has spurred the development of new community software. One such tool has been Py-ART, an easy-to-use library for accessing, plotting and modifying data. This however still requires the use of a programming language, in this case Python.

A Graphical User Interface (GUI) allows users with a range of programming skills to interact with weather radar data. Programs like SOLO (SOLO-ii) have provided such an environment. However, it has become increasingly difficult to deploy SOLO on modern computing systems. This presentation introduces ongoing work to develop a GUI front-end desgined to leverage the expanding number of Py-ART functionalities. The interface itself is written using PyQt, a Python interface to the widely-used Qt library. We call this software ARTview.

The software can load any directory on the local machine where data is stored and the user can easily navigate through the files. ARTview is organized into modules that work independently or may be linked together. Display modules allow the user to create plots of polar-coordinate PPI, RHI and airborne radar, as well as Cartesian gridded data. A tool is provide to map polar to Cartesian coordinates. Customization of displays is available, axes limits may be changed dynamically via mouse or touchpad or through manually entered values. Titles, units, colormaps, text, background and range rings may be modified or added. Publication quality images may be saved at any time.

A number of analysis tools are provided within ARTview. One example is an internal module that allows the user to select a polygon in the plot and use this data to unfold velocity, remove bad data, or get statistics. Fields may be correlated with regression lines drawn. Editing data is possible by leveraging Py-ART functions, including dealiasing, attenuation correction and despeckling, as well as ARTview internal modules. An interface is provided to allow the user to access the raw data from the terminal in a Python environment and see the result in real time. In this way, ARTView can also be used as an extension of the Py-ART programming capabilities.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner