A Python package to parse RADOLAN binary data files to NetCDF
- create CF-conform NetCDFs for RADOLAN data and parse RADOLAN binary files
- write back to RADOLAN-binary format
- supported products:
- RADOLAN-RW (gauge adjusted hourly rainfall sum)
- RADOLAN-RY (5-minute unadjusted rainfall sum), example notebook also available on mybinder
- RADKLIM-YW (5-minute rainfall sum with "climatological" corrections), example notebook also available on mybinder
Assuming that you have some RADOLAN binary files on your hard drive it only takes some lines of code using radolan_to_netcdf
to create a CF-conform NetCDF:
import tqdm
import radolan_to_netcdf as rtn
fn_netcdf = 'radolan_ry.nc'
rtn.create_empty_netcdf(fn=fn_netcdf, product_name='RY')
for fn in tqdm.tqdm(fn_list):
data, metadata = rtn.read_in_one_bin_file(fn)
rtn.append_to_netcdf(fn_netcdf, data_list=[data, ], metadata_list=[metadata, ],)
For the full example using RADOLAN-RY data (5-minute radar rainfall composite for Germany), see the notebook here or open it on mybinder
The content of the created NetCDF can easily be plotted on a dynamic map thanks to xarray
and hvplot
with a time-slider:
import xarray as xr
import hvplot.xarray
ds = xr.open_dataset(fn_netcdf)
plot = ds.rainfall_amount.hvplot.quadmesh(
x='longitudes',
y='latitudes',
frame_width=500,
rasterize=True,
tiles='ESRI',
project=True,
geo=True,
clim=(0.1, 2),
cmap='rainbow',
clabel='rainfall amount (mm)')
plot.opts('Image', clipping_colors={'min': 'transparent', 'NaN': 'gray'}, alpha=0.5, toolbar='above')
- Parsing the RADOLAN binary files is done using
wradlib
. - The RADOLAN radar products are produced by the German Meteorological Service (DWD). Many of these products are openly available at https://opendata.dwd.de/.
- This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.