radar-datatree

radar-datatree#

radar-datatree — Cloud-native, time-aware weather radar datasets radar-datatree — Cloud-native, time-aware weather radar datasets

Companion code for Ladino-Rincón et al. (2026, in preparation). An open-source project by AtmoScale.

The problem isn’t NEXRAD data. It’s the infrastructure around it.

Open the full archive in five lines of Python — no downloads, no decoders, no waiting.

60×faster than file-based
22×less RAM
100 TBqueryable from a laptop

Choose your path

Analyze your own event

Open the live KLOT archive, slice a single severe-weather scan, and plot the polarimetric signature — in 5 lines.

radar datatree: Cloud-native, time-aware weather radar datasets

Reproduce paper results

Reproduce Ryzhkov et al. (2016) Fig. 4 in ~10 s on a laptop. Then push to seasonal scale with Marshall–Palmer QPE.

QVP Analysis: Traditional vs ARCO Workflows

Understand the data model

The DataTree / Icechunk / Zarr stack, the AtmoScale parent platform, and a glossary of every radar acronym in one place.

About

What is radar-datatree?

radar-datatree is a FAIR and cloud-native framework that turns fragmented weather radar archives — millions of standalone binary files with no temporal indexing — into hierarchical, time-indexed, analysis-ready datasets queryable directly from object storage. Built on the WMO FM-301/CfRadial 2.1 standard, xarray.DataTree, Zarr v3, and Icechunk.

Instead of downloading and parsing thousands of binary files, you get direct access to time-indexed, multidimensional arrays — right from your Python session.