Title: “The Open Radar Stack: Bringing Weather Radar Data into Pangeo”
Invited Speaker: Max Grover (ORCID:0000-0002-0370-8974)
When: Wednesday April 3, 12PM EDT
Where: Launch Meeting - Zoom
Abstract: Weather radar data is a complex, yet critical dataset to understanding our weather and climate system. These observational datasets have traditionally been plagued by a plethora of non-standard, difficult to read data formats, requiring the development of open-source toolkits to enable open science in this space. The Python ARM Radar Toolkit (Py-ART) package was created over a decade ago to tackle this challenge, with its data model created prior to the development of Xarray. The World Meteorological Organization (WMO) recently adopted a new universal weather radar data standard, FM301, which will be used moving forward. This new data standard moves to a hierarchical tree-based data structure, which is mimicked in the xradar package, a new package focused solely on IO, with a collection of xarray-based data readers. Last year, we ported many of the existing data readers into this xradar, and now we plan to integrate this with the existing Python ARM Radar Toolkit (Py-ART) package. Users will be able to read a variety of data formats, apply their analysis, visualize their dataset, and output to the WMO FM301 data standard.
The plan moving forward is to move most all of the Input/Output functionality, which was previously in each radar package (Py-ART, wradlib, etc.). Once users read in their data using xradar, they can use accessors, which are connections to other toolkits (similar to the approach many of the existing Pangeo tools). For example, we plan on implementing a Py-ART accessor, which will enable users to use the full suite of functionality in Py-ART. This enables direct cross-compatibility between libraries, enabling Py-ART users to use features in wradlib. One common ARM data correction task in wradlib that would be helpful to use within Py-ART is beam blockage corrections. Users will easily be able to carry out this task using this ecosystem. We will provide updates related to progress on this integration, and demo the new science enabled by using the new data structure.
- 20 minutes - Community Showcase
- 40 minutes - Showcase Discussion/Community Check-ins