README.md

---
license: etalab-2.0
tags:
- climate
- weather
- forecasting
pretty_name: 5 Minutes Radar Rainfall over mainland France
size_categories:
- 100K<n<1M
---

# 📡 5 Minutes Radar Rainfall over mainland France

**Short name**: `radar-rainfall`
**Source**: Météo-France
**License**: Etalab 2.0 (Open License 2.0)

## 🗂️ Dataset Summary

This dataset provides high-resolution radar-based rainfall accumulation data over mainland France. Each file contains the rainfall accumulation (in hundredths of millimeters) over the **past 5 minutes**, with a **spatial resolution of 1 km**.

The data is derived from the radar precipitation mosaic produced by **Météo-France**.

* **Temporal resolution**: every 5 minutes
* **Spatial resolution**: 1 km
* **Grid size**: (1536, 1536)
* **Coverage**: France mainland
* **Projection**: Data is in a Stereographic projection and not in a regular Latitude/Longitude projection 🚨
* **Period covered**: currently 2020–2025 (will be extended back to 2015 in future versions)
* **Data format**: `.npz` (NumPy compressed archive)
* **Total size**: approx. 15 GB/year (\~100,000 files/year)

## 📁 Dataset Structure

Files are organized in folders by year. Each `.npz` file corresponds to a single 5-minute time step.

```bash
radar-rainfall/
├── 2020/
│   ├── 202001010000.npz
│   ├── 202001010005.npz
│   └── ...
├── 2021/
│   └── ...
└── ...
```

Each `.npz` file contains a 2D NumPy array representing the rainfall accumulation over the French territory during that 5-minute interval. Units are **hundredths of millimeters**.

## 🧪 Example Usage

To open and visualize a single `.npz` file:

```python
import numpy as np
import matplotlib.pyplot as plt

# Load the file
data = np.load("2020/202004201700.npz")  # Adjust path as needed
rain = data['arr_0']  # The array is stored under 'arr_0'
print(rain.shape)  # Shape = (1536, 1536)

# Negative values indicate no data, replace them with NaN:
rain = np.where(rain < 0, np.nan, rain)

# Visualize
plt.imshow(rain, cmap="Blues")
plt.colorbar(label="Rainfall (x0.01 mm / 5min)")
plt.title("Rainfall Accumulation – 2020-04-20 17:00 UTC")
plt.savefig("rainfall_20200420_1700.png")
```

![basic usage](rainfall_20200420_1700_basic.png)

The provided `plots.py` module contains some utilities to make nice maps in a regular lat/lon grid.
To convert data to mm/h and plot a beautiful map:

```python
import numpy as np
from plots import plot_map_rain

data = np.load("2020/202004201700.npz")
rain = data['arr_0']
rain = np.where(rain < 0, np.nan, rain)
rain = rain / 100  # Convert from mm10-2 to mm
rain = rain * 60 / 5  # Convert from mm in 5 minutes to mm/h

plot_map_rain(
    rain,
    title="Rainfall Rate – 2020-04-20 17:00 UTC",
    path="rainfall_20200420_1700_map.png"
)
```

![nice map](rainfall_20200420_1700_map.png)

## 🔍 Potential Use Cases

* Precipitation **nowcasting** and short-term forecasting
* Training datasets for **machine learning** or **deep learning** models in meteorology
* **Visualization** and analysis of rainfall patterns
* Research in hydrology, flood risk prediction, and climate science

## 📜 Licensing

The dataset is made available under the **Etalab Open License 2.0**, which permits free reuse, including for commercial purposes, provided proper attribution is given.

More information: [https://www.etalab.gouv.fr/licence-ouverte-open-licence/](https://www.etalab.gouv.fr/licence-ouverte-open-licence/)

## 📦 Citation

If you use this dataset in your work, please cite it as:

```
@misc{radar_rainfall_france,
  title        = {5 Minutes Radar Rainfall over French Mainland Territory},
  author       = {Météo-France},
  year         = {2025},
  howpublished = {\url{https://huggingface.co/datasets/meteofrance/radar-rainfall}},
  note         = {Distributed under Etalab 2.0 License}
}
```

## 🙏 Acknowledgements

Data provided by **Météo-France**. Processed and distributed by **Météo-France AI Lab** for open research and development purposes.