# About

## Parent platform

`radar-datatree` is the open-source on-ramp to **[AtmoScale](https://atmoscale.ai)** — the institutional platform for turning radar, satellite, and model data into cloud-native, decision-ready products. Use this repository to learn the data model, reproduce published results, or analyze events on your own. Talk to AtmoScale when you need it operationalized for your institution.

### What's here vs. what's on the platform

| | This repository | AtmoScale platform |
|---|---|---|
| **Data** | Public archives on `s3://nexrad-arco` (anonymous reads) | Curated archives, custom radar networks, multi-modal fusion |
| **Code** | Tutorials, reproducible notebooks, the helper module | Managed pipelines, dashboards, alerting |
| **Use case** | Research, reproducibility, learning the data model | Operations, institutional deployments, SLA-backed delivery |
| **Support** | GitHub Issues (community) | Direct support from the AtmoScale team |

```{button-link} https://atmoscale.ai
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Visit AtmoScale →
```

## Technology Stack

```{dropdown} Built on proven open-source technologies
:color: info
:icon: tools

| Component | Purpose |
|-----------|---------|
| **WMO FM-301 / CfRadial 2.1** | Standardized radar data model ensuring interoperability |
| **xarray.DataTree** | Hierarchical data structures for multi-dimensional arrays |
| **Zarr v3** | Cloud-optimized storage with chunked compression |
| **Icechunk** | ACID-compliant transactional storage with version control |
| **xradar** | Radar-specific I/O, QC, and processing utilities |
| **rustytree-xarray** | Rust-backed DataTree backend (recommended engine) |

The stack ensures compatibility with existing tools while enabling cloud-native workflows.
```

## Links

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```{button-link} https://github.com/AtmoScale/radar-datatree
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:outline:

GitHub Repository
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```{button-link} https://doi.org/10.48550/arXiv.2510.24943
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arXiv Preprint
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```{button-link} https://registry.opendata.aws/nexrad-arco/
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AWS Open Data
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```{button-link} https://xarray.dev
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xarray Docs
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## Citation

**Forthcoming paper (in preparation):**

> Ladino-Rincón, A., et al. (2026). *Radar DataTree: A FAIR and Cloud-Native Framework for Scalable Weather Radar Archives.* (Manuscript in preparation.)

**Earlier preprint:**

> Ladino-Rincón, A., & Nesbitt, S. W. (2025). *Radar DataTree: A FAIR and Cloud-Native Framework for Scalable Weather Radar Archives.* arXiv:2510.24943. [doi:10.48550/arXiv.2510.24943](https://doi.org/10.48550/arXiv.2510.24943)