Description¶
This notebook describes how to access and use the zarr-version of the French radar data provided by Météo-France. The dataset includes aproximately ~500.000 5 min timesteps covering a 1536 x 1536 resolution with 1km grid-size. The original radar.npz files are stored in (mm x 10^-2) and the .zarr dataset is in precipitation rate (mm/h).
Related repositories¶
The conversion of the radar data was done by the code hosted on https://
github .com /mlcast -community /mlcast -dataset -FR -MF. The radar dataset can be directly downloaded from Météo-France Hugging Face repository.
The v0.1.0 zarr dataset covers the temporal period of 2020-01-01 to 2024-12-31.
Citation¶
Data provided by Météo-France. Processed and distributed by Météo-France AI Lab for open research and development purposes. Please cite 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}
}Licence: CC-BY-4.0
import matplotlib.pyplot as plt
import xarray as xr
import cartopy.feature as cfeature
import cartopy.crs as ccrs
import mlcast_datasetscat = mlcast_datasets.open_catalog()
list(cat.precipitation)['radklim_hourly',
'radklim_5_minutes',
'dmi_10_minutes',
'it_dpc_sri_5min',
'uk_metoffice_5min',
'be_rmi_radclim_mfb_5min',
'fr_mf_prate_5min']FR-MF - 5-min Rainfall rate¶
The French MF SRI dataset is available in the intake catalog as fr_mf_prate_5min.
ds = cat.precipitation.fr_mf_prate_5min.to_dask()
dsvar_name = "prate"
crs_name = ds[var_name].grid_mapping
data_crs = ccrs.Projection(ds[crs_name].crs_wkt)
g = (
ds[var_name]
.sel(time="2023-11-17")
.isel(time=slice(None, 3))
.plot(
transform=data_crs,
cmap="viridis",
add_colorbar=True,
col="time",
robust=True,
subplot_kws=dict(projection=data_crs),
vmin=0,
)
)
for ax in g.axes.flat:
ax.coastlines()
ax.gridlines(draw_labels=["top", "left"])