Building an Open-Source NOAA MRMS Radar Renderer in Python

When I started building Weather Experience, I wasn't planning to release an open-source project. I simply wanted to answer a question: Could I build a modern radar rendering pipeline using NOAA's publicly available MRMS data? That question led me down a rabbit hole of GRIB2 decoding, radar products, rendering pipelines, performance benchmarking, and ultimately the release of MRMS Renderer, the first open-source project from Taylor Creative Development.

Why MRMS?

NOAA's Multi-Radar/Multi-Sensor (MRMS) system provides an incredible amount of weather data. For my use case, I focused on the ReflectivityAtLowestAltitude product because it provides an excellent foundation for radar visualization. The challenge wasn't obtaining the data. The challenge was turning that data into something useful.

The Pipeline

MRMS Renderer performs the complete workflow:

• Discover the latest MRMS products directly from NOAA/NCEP
• Download and decompress GRIB2 data
• Decode the grid using ecCodes
• Process reflectivity values with NumPy
• Render transparent PNG radar frames
• Generate an animation manifest
• Display animated radar over OpenStreetMap using Leaflet

Everything runs locally. The project intentionally does not provide a hosted radar service. Instead, it demonstrates how developers can work directly with NOAA's publicly available data.

Performance

One of the biggest questions I had at the beginning was performance. Could this realistically be done fast enough for a modern application? Rather than speculate, I wrote benchmarks.

On my M4 Pro MacBook Pro over a standard Wi-Fi connection, the complete pipeline-from downloading the latest MRMS frame through rendering the finished PNG-consistently completed in around two seconds.

The surprising result wasn't the renderer. The renderer itself was already highly optimized using NumPy vectorization. The largest source of latency turned out to be downloading the GRIB2 data itself. That finding helped shape later architectural decisions for Weather Experience, where I plan to build on top of this work.

Building It Like a Real Project

The original prototype lived in a research directory full of experimental scripts. Before releasing anything publicly, I wanted to treat it like a real software project. That meant:

• Separating the code into reusable modules
• Writing automated tests
• Documenting the architecture
• Publishing under the Apache License 2.0
• Performing a clean-room installation from a fresh clone
• Ensuring the README alone was sufficient to get someone from clone to working animation

That last step caught a real onboarding bug before the first public release. I'm glad it did.

Why Open Source?

Although MRMS Renderer was created to support another application, it quickly became obvious that it could stand on its own. Rather than hide the implementation inside a proprietary application, I decided to release it under the Apache License 2.0 so other developers could learn from it, build on it, and improve it.

One of my goals with Taylor Creative Development is to contribute useful software back to the developer community whenever it makes sense. MRMS Renderer is the first step in that direction.

What's Next?

MRMS Renderer is intentionally focused. I don't want it to become a giant weather framework. Instead, I want it to remain a clean, approachable reference implementation for working with NOAA MRMS radar data. If it helps someone build a weather application, learn how GRIB2 works, or experiment with radar visualization, then it's already accomplished its goal.

The project is available on GitHub:

Repository: https://github.com/Taylor-Creative-Development/mrms-renderer

I'd love feedback on the architecture, documentation, implementation, or ideas for future improvements.