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title: Format
subtitle: Structure and metadata of RADOLAN binary files and how to decode them.
---

# Format

RADOLAN was distributed in binary format for roughly 20 years now. In the last years, especially with the evolving [POLARA framework](https://www.dwd.de/DE/forschung/atmosphaerenbeob/wetterradar/wetterradar_node.html) HDF5 based products emerged. 

In August 2025 The Deutscher Wetterdienst [announced](https://www.dwd.de/DE/leistungen/opendata/neuigkeiten/opendata_august2025_1.html) the sunsetting of several products in the legacy binary format to be exchanged with new ODIM_H5 based products after November 30, 2025.

In the following sections all formats are described in great detail.

```{code-cell} python
import io
import tarfile
import warnings

warnings.filterwarnings("ignore")

import matplotlib.pyplot as plt
import numpy as np
import wradlib as wrl
import xarray as xr
```

(odim-format)=
## ODIM_H5 format

ODIM_H5 was developed by the [EUMETNET Operational Programme for the Exchange of Weather Radar Information (OPERA)](https://eumetnet.eu/observations/weather-radar-network/). The [OPERA Data Information Model (ODIM) document](https://www.eumetnet.eu/wp-content/uploads/2021/07/ODIM_H5_v2.4.pdf) can be accessed from their website. 

To get an insight of the inner HDF5 layout, we just open the file with {func}`xarray:xarray.open_datatree` and visualize the structure. You can inspect the different groups, datasets and attributes. 

```{code-cell} python
# load radolan files
rw_filename = "../data/hdf5/raa01-rw_10000-latest-dwd---bin.hdf5"
ds = xr.open_datatree(rw_filename)
display(ds)
```

For this kind of RADOLAN data {{ wradlib }} implemented a transformation layer to read the data with the same reader as the binary and ASCII format data and present it in the same consistent {class}`xarray:xarray.Dataset`. This functionality is available starting with {{ wradlib }} version 2.6.0.

```{code-cell} python
ds = xr.open_dataset(rw_filename, engine="radolan")
display(ds)
ds.ACRR.plot()
```

## Binary format

The RADOLAN binary data file format is described in the [RADOLAN/RADVOR-OP Kompositformat](https://www.dwd.de/DE/leistungen/radolan/radolan_info/radolan_radvor_op_komposit_format_pdf.pdf?__blob=publicationFile) document. The radolan composite files consists of an ascii header containing all needed information to decode the following binary data block. $\omega radlib$ provides {func}`wradlib.io.read_radolan_composite` to read the data.

The function {func}`wradlib.io.parse_dwd_composite_header` takes care of correctly decoding the ascii header. All available header information is transferred into the metadata dictionary.

```{code-cell} python
# load radolan files
rw_filename = "../data/misc/raa01-rw_10000-1408102050-dwd---bin.gz"
import os
print(os.getcwd())
filehandle = wrl.io.get_radolan_filehandle(rw_filename)
header = wrl.io.read_radolan_header(filehandle)
print(header)
```

```{code-cell} python
attrs = wrl.io.parse_dwd_composite_header(header)
print(attrs)
```

In the following example, the header information of four different composites is extracted.

```{code-cell} python
# load radolan file
rx_filename = "../data/showcase/legacy/raa01-rx_10000-1408102050-dwd---bin.gz"
ex_filename = "../data/showcase/legacy/raa01-ex_10000-1408102050-dwd---bin.gz"
rw_filename = "../data/showcase/legacy/raa01-rw_10000-1408102050-dwd---bin.gz"
sf_filename = "../data/showcase/legacy/raa01-sf_10000-1408102050-dwd---bin.gz"

rxdata, rxattrs = wrl.io.read_radolan_composite(rx_filename)
exdata, exattrs = wrl.io.read_radolan_composite(ex_filename)
rwdata, rwattrs = wrl.io.read_radolan_composite(rw_filename)
sfdata, sfattrs = wrl.io.read_radolan_composite(sf_filename)

# print the available attributes
print("RX Attributes:")
for key, value in rxattrs.items():
    print(key + ":", value)
print("----------------------------------------------------------------")
# print the available attributes
print("EX Attributes:")
for key, value in exattrs.items():
    print(key + ":", value)
print("----------------------------------------------------------------")

# print the available attributes
print("RW Attributes:")
for key, value in rwattrs.items():
    print(key + ":", value)
print("----------------------------------------------------------------")

# print the available attributes
print("SF Attributes:")
for key, value in sfattrs.items():
    print(key + ":", value)
print("----------------------------------------------------------------")
```

## ASCII format

The ASCII GIS Format is prepended by a limited header and has two flavours as follows:

- RADOLAN / reproc (RADARKLIMATOLOGIE) 2001 – 2019

```
    ncols 900
    nrows 1100
    xllcorner -443462
    yllcorner -4758645
    cellsize 1000
    nodata_value -9999.0
```
    Units: 1.0 mm

- RADOLAN / recent, 2020 – jetzt :
```
    ncols 900
    nrows 900
    xllcorner -523462y
    llcorner -4658645
    cellsize 1000
    NODATA_value -1
```
    Units: 0.1 mm

Product and Datetime need to be extracted from the filename, so extra care has to be taken to not tamper with the filenames. Finally, we exploit {func}`wradlib.io.open_radolan_mfdataset` to load the data into a consistent {class}`xarray.Dataset`.

```{code-cell} python
fname = "../data/asc/RW-20221018.tar.gz"
fp = tarfile.open(fname)
names = fp.getnames()
buffer = [io.BytesIO(fp.extractfile(name).read()) for name in names]
for buf, name in zip(buffer, names):
    buf.name = name
ds = wrl.io.open_radolan_mfdataset(buffer)
display(ds)
```