Tuesday, 29 August 2023
Boundary Waters (Hyatt Regency Minneapolis)
The Lidar Radar Open Software Environment (LROSE) is being developed to meet the challenges of complex radar and lidar processing needs faced by users in the research and education communities. Through support from the National Science Foundation, Colorado State University and the National Center for Atmospheric Research are developing the LROSE 'Virtual Toolbox' stocked with core algorithm modules for those typical processing steps that are well understood and documented in the peer-reviewed literature. LROSE focuses on key software building blocks for data processing and analysis workflows: Convert, Display, Quality Control, Grid, Echo, and Wind. Our current 'stable' release is called "Topaz" and the 'development' release is called "Jade", which consist of a suite of well-documented software modules for performing radar and lidar analysis.
Recently, the LROSE team has developed a new version of the LROSE Science Gateway, which aims to increase accessibility to the LROSE applications in the cloud. The LROSE Science Gateway is now hosted on a JupyterHub server deployed on NSF’s Jetstream2. The JupyterHub server hosts introductory tutorials that guide users through common scientific workflows and the only requirements are 1) a modern web browser and 2) a GitHub account. The initial tutorials demonstrate how to calculate specific differential phase (KDP), run the NCAR particle identification (PID) algorithm, and estimate precipitation rates, perform basic quality control procedures available in LROSE, create NEXRAD mosaics, and generate multi-Doppler analyses using FRACTL and SAMURAI. Additionally, these tutorials show how LROSE can be combined with other open source packages such as Py-ART in scientific workflows. These tutorials are also available on GitHub for use on personal machines. Community members will learn how to access the JupyterHub server, contribute workflows to the LROSE Science Gateway, and develop educational workshops or classroom exercises.
Recent updates to LROSE will also be presented, including support for new Mac OS machines, improvements to the installation process, a dramatic speed up in SAMURAI performance, a new clutter application in RadxClutter, improved categorical censoring in RadxPid and RadxRate, and bug fixes.
Recently, the LROSE team has developed a new version of the LROSE Science Gateway, which aims to increase accessibility to the LROSE applications in the cloud. The LROSE Science Gateway is now hosted on a JupyterHub server deployed on NSF’s Jetstream2. The JupyterHub server hosts introductory tutorials that guide users through common scientific workflows and the only requirements are 1) a modern web browser and 2) a GitHub account. The initial tutorials demonstrate how to calculate specific differential phase (KDP), run the NCAR particle identification (PID) algorithm, and estimate precipitation rates, perform basic quality control procedures available in LROSE, create NEXRAD mosaics, and generate multi-Doppler analyses using FRACTL and SAMURAI. Additionally, these tutorials show how LROSE can be combined with other open source packages such as Py-ART in scientific workflows. These tutorials are also available on GitHub for use on personal machines. Community members will learn how to access the JupyterHub server, contribute workflows to the LROSE Science Gateway, and develop educational workshops or classroom exercises.
Recent updates to LROSE will also be presented, including support for new Mac OS machines, improvements to the installation process, a dramatic speed up in SAMURAI performance, a new clutter application in RadxClutter, improved categorical censoring in RadxPid and RadxRate, and bug fixes.
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