DWD ICON-EU forecast, 5 day
| Spatial domain | Europe |
| Spatial resolution | 0.0625 degrees (~7km) |
| Time domain | Forecasts initialized 2026-02-10 00:00:00 UTC to Present |
| Time resolution | Forecasts initialized every 6 hours |
| Forecast domain | Forecast lead time 0-120 hours (0-5 days) ahead |
| Forecast resolution | Forecast step 0-78 hours: hourly, 81-120 hours: 3 hourly |
ICON-EU is a regional weather forecast model operated by Deutscher Wetterdienst (DWD), Germany's national meteorological service. ICON-EU is a nested configuration of DWD's global ICON (Icosahedral Non-hydrostatic) model that provides high-resolution forecasts over Europe.
This dataset is an archive of past and present ICON-EU forecasts. Forecasts are identified by an initialization time (init_time) denoting the start time of the model run and step forward in time along the lead_time dimension. This dataset contains only the 00, 06, 12, and 18 hour UTC initialization times which produce the full length, 5 day forecast.
Examples
|
Quickstart (Github) |
|
Quickstart (Colab) |
import dynamical_catalog # dynamical-catalog>=0.7.0
ds = dynamical_catalog.open("dwd-icon-eu-forecast-5-day")
ds["temperature_2m"].sel(init_time="2026-04-01T00", latitude=50, longitude=10).max().compute()Dimensions
| min | max | units | |
|---|---|---|---|
| init_time | 2026-02-10T00:00:00Z | Present | seconds since 1970-01-01 |
| latitude | 29.5 | 70.5 | degree_north |
| lead_time | 0 | 432000 | seconds |
| longitude | -23.5 | 62.5 | degree_east |
Variables
Access a variable by its name (the bold identifier, e.g. ds["cloud_cover_high"]).
Dimensions: init_time × lead_time × latitude × longitude
| variable | units |
|---|---|
cloud_cover_high
High cloud cover (hcc)Cloud cover (0 - 400 hPa).
|
percent |
cloud_cover_low
Low cloud cover (lcc)Cloud cover (800 hPa - surface).
|
percent |
cloud_cover_medium
Medium cloud cover (mcc)Cloud cover (400 - 800 hPa).
|
percent |
convective_available_potential_energy_atmosphere
Convective available potential energy (cape)
|
J kg-1 |
dew_point_temperature_2m
2 metre dewpoint temperature (2d)
|
degree_Celsius |
downward_diffuse_short_wave_radiation_flux_surface
Surface diffuse short-wave radiation flux (aswdifd_s)
|
W m-2 |
downward_direct_short_wave_radiation_flux_surface
Surface direct short-wave radiation flux (aswdir_s)Average value since the previous forecast step.
|
W m-2 |
precipitable_water_atmosphere
Precipitable water (pwat)
|
kg m-2 |
precipitation_surface
Precipitation rate (prate)Average precipitation rate since the previous forecast step. Units equivalent to mm/s.
|
kg m-2 s-1 |
pressure_reduced_to_mean_sea_level
Pressure reduced to MSL (prmsl)
|
Pa |
pressure_surface
Surface pressure (sp)
|
Pa |
relative_humidity_2m
2 metre relative humidity (2r)
|
percent |
snow_thickness_surface
Snow depth (sde)
|
m |
snow_water_equivalent_surface
Snow depth water equivalent (sd)Set to 0 over water surfaces and snow-free land points.
|
m |
temperature_2m
2 metre temperature (2t)
|
degree_Celsius |
total_cloud_cover_atmosphere
Total cloud cover (tcc)
|
percent |
wind_gust_10m
Maximum 10 metre wind gust since previous post-processing (10fg)
|
m s-1 |
wind_u_10m
10 metre U wind component (10u)
|
m s-1 |
wind_v_10m
10 metre V wind component (10v)
|
m s-1 |
Details
License
Dataset licensed under CC BY 4.0.
Attribution and citation
DWD ICON-EU data processed by dynamical.org.
Or DWD ICON-EU from dynamical.org.
Source
The source grib files this archive is constructed from are provided by DWD Open Data and the dynamical.org DWD ICON grib archive on Source Cooperative.
Storage
Icechunk storage generously provided by AWS Open Data. Storage for the dynamical.org DWD ICON-EU grib archive is generously provided by Source Cooperative, a Radiant Earth initiative.
Chunks & shards
This dataset is stored in Zarr format, which splits each variable into a grid of chunks — the smallest unit read from storage. Chunks are grouped into larger shards (the objects actually written to storage), which keeps the object count manageable for long-archive datasets. When possible, aligning your reads with this dataset's chunk grid can significantly improve data access speed.
The element count and coordinate span of this dataset:
| dimension | chunk | shard |
|---|---|---|
| init_time | 1 (6 hours) | 1 (6 hours) |
| lead_time | 93 (121 hours) | 93 (121 hours) |
| latitude | 219 (13.6875°) | 657 (41.0625°) |
| longitude | 153 (9.5625°) | 1377 (86.0625°) |
| uncompressed | 11.9 MiB | 321.0 MiB |
Compression
The data values in this dataset have been rounded in their binary floating point representation to improve compression. See Klöwer et al. 2021 for more information on this approach. The exact number of rounded bits can be found in our reformatting code.