dwdopen
Python library to download numerical weather prediction (NWP) data from DWD Open Data. List currently available models, parameters, and runs. Select what data you want and download it as GRIB2 file(s).
Install
Requires Python 3.11 or newer.
pip install dwdopen
Quickstart
from dwdopen import DWD, Every
with DWD() as dwd:
icon_eu = dwd.nwp.model("icon-eu")
query = icon_eu.select(["T_2M", "TOT_PREC"], steps=Every("0h", "24h", "3h"))
query.download("forecast.grib2")
This downloads 2 m temperature and total precipitation for the next 24 hours, every 3 hours, from the newest ICON-EU run that is completely published, into one GRIB2 file.
Discovery
dwd.nwp.models() # ['aicon', 'icon', 'icon-art', ..., 'icon-eu-eps']
icon_eu.parameters() # ['ALB_RAD', 'ALHFL_S', ..., 'T_2M', ...]
icon_eu.parameter("T") # on pressure (100) and model (150) levels
icon_eu.levels("T", "pressure") # [50, 70, 100, ..., 850, ..., 1000] (hPa)
icon_eu.runs() # [..., Run(2026-10-27T06:00Z)], oldest first
Examples
These continue inside the with DWD() as dwd: block of the quickstart.
Upper air: temperature on 850 and 500 hPa at +12 h.
upper_air = icon_eu.select("T", level_type="pressure", levels=[850, 500], steps=["12h"])
upper_air.download("t.grib2")
Ensemble: the first 5 members of ICON-EU-EPS, one file per member, into a directory.
from dwdopen import Between
eps = dwd.nwp.model("icon-eu-eps")
ensemble = eps.select("T_2M", members=Between(1, 5), steps="24h")
ensemble.download("members/", combine="member")
A scheduled job: give a directory instead of a file name, and the file is named after
the model, run and selection. Running the job again for the same run downloads nothing.
query is the one from the quickstart.
result = query.download("/data/icon-eu/")
# /data/icon-eu/icon-eu_2026-10-27T0600_TOT_PREC+T_2M_single_0h-24h_ec484355.grib2
result.assets_skipped # 18 on the second run: the file was already there
Look before you download: resolve() freezes a query against one run and gives you a
plan to inspect. The plan never switches to a newer run later.
plan = query.resolve()
print(plan)
# ResolvedRequest(run=2026-10-27T06:00Z, 18 assets, 12.1 MB, TOT_PREC, T_2M,
# 9 steps 0h..24h)
plan.download("forecast.grib2")
The data is on the native ICON grid
DWD publishes every model on the unstructured triangular ICON grid. To get a regular lat-lon grid, regrid with CDO. For ICON global, DWD provides ready-made weights:
# from https://opendata.dwd.de/weather/lib/cdo/ICON_GLOBAL2WORLD_025_EASY.tar.bz2
cdo -f nc remap,target_grid_world_025.txt,weights_icogl2world_025.nc t_2m.grib2 t_2m.nc
For ICON-EU and the other models see Regridding in the guide.
Features
The guide explains each of these in detail.
- Every ICON model on DWD Open Data: ICON, ICON-EU, ICON-D2, ICON-D2-RUC, their ensembles, ICON-ART and AICON. Nothing is hard-coded.
- Steps as durations:
"6h",["0h", "3h"],Every("0h", "48h", "3h"),Between("0h", "48h"),"all", and 15 or 5 minute steps for ICON-D2 and ICON-D2-RUC. - Vertical levels: pressure levels in hPa, model levels and soil levels.
- Ensemble members:
members=[1, 2, 5],Between(1, 10), or all of them. - ICON-ART wavelengths:
wavelengths=532for the dust backscatter fields. - Complete runs only: by default a run that DWD is still publishing is skipped, and
require="partial"takes what is there and reports the rest. - Combining: return one file, one per parameter, one per ensemble member, or one file per GRIB message.
- Safe, resumable downloads: concurrent, written atomically, already downloaded files are skipped, with a progress bar.
- Clear errors: every error is a
DWDOpenError, and typos in names and options are caught before anything is downloaded.
Roadmap
After 1.0
- A command-line interface.
Long term
The goal is a complete Python interface to DWD Open Data:
- Observations and current station reports (
weather/weather_reports). - Radar: composites and single-site products (
weather/radar). - Point forecasts: MOSMIX (
weather/local_forecasts). - Weather warnings (
weather/alerts). - Satellite products (
weather/satellite).
License
MIT. See LICENSE.
Forecast data itself is provided by Deutscher Wetterdienst (DWD) under its own terms of use.
Metadata
Release files for dwdopen 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| dwdopen-1.0.1.tar.gz | 84.6 kB | With provenance | Details for dwdopen-1.0.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| dwdopen-1.0.1-py3-none-any.whl | Python 3 | none | any | Details for dwdopen-1.0.1-py3-none-any.whl |
Total release size: 139.9 kB
Release files / dwdopen-1.0.1.tar.gz
| Download URL | dwdopen-1.0.1.tar.gz |
|---|---|
| Size | 84.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
10f060bb4e6b6623cea5e22d033c8cb5c57231b0d50ff42db4d5c08313a7197c
|
|
BLAKE2b-256 checksum How to use checksums |
69fec48288d75b4e44a9762ff2a70ddc9ee8d6c3eed56077bc0d53cc0a9748e4
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.16
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 11, 2026.
Transparency logRelease files / dwdopen-1.0.1-py3-none-any.whl
| Download URL | dwdopen-1.0.1-py3-none-any.whl |
|---|---|
| Size | 55.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
0b310462ea51efa2ff7fa6f6e69456600b8bae7bd77963511ddf81f3f8277f9b
|
|
BLAKE2b-256 checksum How to use checksums |
980eef9c13efe3e9d6f97400bb2c6143e57a59fc07e7bf738889e63b9776fc3d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.16
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 11, 2026.
Transparency logSecurity for dwdopen 1.0.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
Both files in this release have been uploaded with provenance metadata.
Attestation for dwdopen-1.0.1.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 11, 2026.
Transparency logA note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.