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πŸ“‘ 5 Minutes Radar Rainfall over mainland France

Short name: radar-rainfall Source: MΓ©tΓ©o-France License: Etalab 2.0 (Open License 2.0)

πŸ—‚οΈ 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 MΓ©tΓ©o-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)

πŸ“ Dataset Structure

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

radar-rainfall/
β”œβ”€β”€ 2020/
β”‚   β”œβ”€β”€ 202001010000.npz
β”‚   β”œβ”€β”€ 202001010005.npz
β”‚   └── ...
β”œβ”€β”€ 2021/
β”‚   └── ...
└── ...

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.

πŸ§ͺ Example Usage

To open and visualize a single .npz file:

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

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:

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

πŸ” 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

πŸ“œ 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/

πŸ“¦ 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       = {MΓ©tΓ©o-France},
  year         = {2025},
  howpublished = {\url{https://huggingface.co/datasets/meteofrance/radar-rainfall}},
  note         = {Distributed under Etalab 2.0 License}
}

πŸ™ Acknowledgements

Data provided by MΓ©tΓ©o-France. Processed and distributed by MΓ©tΓ©o-France AI Lab for open research and development purposes.

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