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LROSE: The Lidar Radar Open Software Environment

Overview

The current LROSE release is called “Colette” (a versatile climbing rose) and encompasses six key toolsets that define a core lidar/radar workflow: Convert, Display, QC, Grid, Echo, and Winds. Colette focuses on high-quality, well-tested, well-maintained and well-documented key applications as ‘building blocks’, allowing users to assemble trusted, reproducible workflows to accomplish more complex scientific tasks.

Some highlights for Colette:

• The cmake build option now supports qt6.
• Packages are available for Centos, Ubuntu, Fedora 37, 38, 39, Alma Linux, Suse.
• Bug fixes and updates to Radx applications.
• HawkEdit is now a beta version, and has undergone considerable testing from users.

Colette can be compiled in C++ for native apps on Linux or Mac. Preliminary support is available for some tools on Windows.

We encourage users to register in order to receive critical software updates, and sign up for the mailing list to help build the LROSE community.

Help can be obtained by posting issues directly to the lrose-core GitHub repository, via our help mailing list, or Discourse user forum.

LROSE is a co-operative project between:

• Dept. of Atmospheric Science at Colorado State University (CSU) and the
• The Earth Observing Lab at the National Center for Atmospheric Research (NCAR).

LROSE is funded by the National Science Foundation.

Citations for LROSE tools

Please cite the version of LROSE tools you use for publication. If you are unsure of the version, please cite the latest stable release.

• lrose-colette, 2024: DeHart, J., Dixon, M., Javornik, B., Bell, M., Cha, T.-Y., DesRosiers, A., & Lee, W.-C. (2024). nsf-lrose/lrose-releases: lrose-colette-20240525 (lrose-colette-20240525). Zenodo. https://doi.org/10.5281/zenodo.11510075
• lrose-jade, 2023: DeHart, J., Dixon, M., Javornik, B., Bell, M., Cha, T.-Y., DesRosiers, A., & Lee, W.-C. (2024). nsf-lrose/lrose-releases: lrose-jade-20230814 (lrose-jade-20230814). Zenodo. https://doi.org/10.5281/zenodo.11479603
• lrose-topaz, 2022: Michael M. Bell. (2022). nsf-lrose/lrose-topaz: lrose-topaz-20220222 (lrose-topaz-20220222). Zenodo. https://doi.org/10.5281/zenodo.6909479
• lrose-elle, 2021: Michael M. Bell, Michael Dixon, Wen-Chau Lee, Brenda Javornik, Jennifer DeHart, & Ting-Yu Cha. (2021). nsf-lrose/lrose-elle: lrose-elle stable final release 20210312 (lrose-elle-20210312). Zenodo. https://doi.org/10.5281/zenodo.5523312
• lrose-cyclone, 2020: Michael M. Bell, & Bruno Melli. (2020). nsf-lrose/lrose-cyclone: lrose-cyclone release 20200110 (lrose-cyclone-20200110). Zenodo. https://doi.org/10.5281/zenodo.3604387
• lrose-blaze, 2019: Michael M. Bell. (2019). nsf-lrose/lrose-blaze: lrose-blaze-20190105 (lrose-blaze-20190105). Zenodo. https://doi.org/10.5281/zenodo.2532758

Installation Instructions

• Homebrew Installation
  • Mac Homebrew installation - For Native applications on the Mac, the recommended method is to use Homebrew. The formula contains all the necessary dependencies and builds instructions.

• Source Installation - Intended for users who wish to do a manual build or build in a non-standard location. Source compilation is best performed using a supplied Python script.
  • Build system - For LINUX and MAC OS cmake/autoconf/manual builds and code development

• CIDD Binary Installation
  • CIDD Binary Release - CIDD depends on a 32-bit build, which complicates the build and install for the core. The CIDD display application is not included in the standard lrose-core packages (above).

Tutorials

We are in the process of transitioning most of our tutorials to our new LROSE Science Gateway hosted on JupyterHub servers deployed on NSF's Jetstream2 supercomputer at Indiana University. The notebooks can also be found on our GitHub repository. This work is supported by NSF award AGS-2103776. For more information, please contact the LROSE team directly for JupyterHub access or setting up a classroom exercise or workshop.

Our old tutorials can be found here.

Toolsets

In the current release, the following tools are available:

Convert

• RadxPrint - Query files to determine properties and support by the Radx engine
• RadxConvert - Convert 24 different lidar and radar formats to CfRadial NetCDF format
• RadxBufr - Convert Bufr format to CfRadial NetCDF format

Display

• HawkEye - Real-time and archive display suitable for both scanning and vertically pointing radars.

Quality Control

• RadxDiffFields - Compare two fields in different CfRadial files
• RadxDiffVol - Compare two volumes in different CfRadial files
• RadxMergeFields - Merge fields from different CfRadial files
• RadxFilter - Perform simple filtering operations
• RadxPersistentClutter - Create a mask for persistent ground clutter
• RadxDealias - Dealias single-Doppler data
• RadxQc - General quality control
• IntfRemove - Identify and remove interference in Titan data
• RadxModelQc - Filter Radx data
• RadxClutMon - Clutter analysis
• TsCalAuto - Radar calibration analysis
• RadarCal - Analyze calibration data
• RadxSunMon - Search for sun spikes and perform solar analysis
• SunCal - Analyze time series data from sun scans

Grid

• Radx2Grid - Gridding and interpolation of ground-based radar data

Echo

• RadxKdp - KDP and Attenuation calculations
• RadxPid - KDP, Attenuation, and Particle Identification
• RadxRate - KDP, Attenuation, PID, and Rain Rate
• RadxQpe - Accumulated Quantitative Precipitation Estimation
• RadxHca - NEXRAD Hydrometeor Classification Algorithm
• RateAccum - Accumulated Precipitation (recommended)
• PrecipAccum - Accumulated Precipitation (not recommended)
• RadxBeamBlock - Beam Blockage Estimation
• ConvStrat - Identify convective and stratiform regions in Cartesian radar volume
• RadxMesoCyclone - Identify mesocyclones in radar data
• QpeVerify - Compare radar-derived and observed precipitation accumulation
• RefractCompute - Compute refractivity
• RefractCalib - Create calibration file used by RefractCompute
• CalcMoisture - Calculate moisture fields from refractivity
• Titan - Thunderstorm Identification, Tracking, Analysis, and Nowcasting application
• Tracks2Ascii - Print out storm and track data in ASCII format
• Tstorms2Xml - Convert storms data to XML or Spdb
• StormInitLocation - Write out the initiation location of significant storms
• ScaleSep - Separate a radar image into different spatial scales
• Colide - Detect and extrapolate boundaries
• ctrec - Track echo motion
• Rview - Visualize Titan data (spatially)
• TimeHist - Visualize Titan data (through time)

Wind

• RadxEvad - Extended Velocity Azimuth Display single-Doppler retrieval
• FRACTL - Fast Reorder and CEDRIC Technique in LROSE multi-Doppler retrieval
• SAMURAI - Variational multi-Doppler retrieval and analysis package
• VORTRAC - Vortex Objective Radar Tracking and Circulation single-Doppler retrieval
• OpticalFlow - Estimate 2-D velocity of a radar field

Practical Radar Meteorology

The material contained here is designed to supplement radar textbooks and course materials with scientific background on common procedures used in radar meteorology. When combined with the above tutorials and documentation, these practical guides will help apply LROSE tools for scientific applications.

1. Cartesian Gridding of Polar Radar Data
2. Convective/Stratiform Partitioning
3. Kdp Calculation
4. Rain Rate Calculations
5. Attenuation Correction
6. Particle Identification using Fuzzy Logic
7. Quantitative Precipitation Estimation
8. Velocity Dealiasing

LROSE Workshops

LROSE AMS 2020 Mini Workshop

• Meeting Notes
• LROSE Mini-Workshop Slides
• LROSE Cyclone Multi-Doppler Tutorial Slides
• Brief Hawkeye Tutorial Slides

LROSE Fall 2021 Virtual Workshop

• Meeting Notes
• Pre-recorded Videos
• Session Recordings and Slides

LROSE AMS 2023 Workshop

• Meeting Notes
• Session Recordings and Slides