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

STAC (browse)

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)

dynamical.org - DWD ICON-EU forecast, 5 day

Maximum temperature in a forecast

import dynamical_catalog  # dynamical-catalog>=0.5.0

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

	units	dimensions
cloud_cover_high (`hcc`) High cloud cover Cloud cover (0 - 400 hPa).	percent	init_time × lead_time × latitude × longitude

cloud_cover_low (`lcc`) Low cloud cover Cloud cover (800 hPa - surface).	percent	init_time × lead_time × latitude × longitude

cloud_cover_medium (`mcc`) Medium cloud cover Cloud cover (400 - 800 hPa).	percent	init_time × lead_time × latitude × longitude

convective_available_potential_energy_atmosphere (`cape`) Convective available potential energy	J kg-1	init_time × lead_time × latitude × longitude

dew_point_temperature_2m (`2d`) 2 metre dewpoint temperature	degree_Celsius	init_time × lead_time × latitude × longitude

downward_diffuse_short_wave_radiation_flux_surface (`aswdifd_s`) Surface diffuse short-wave radiation flux	W m-2	init_time × lead_time × latitude × longitude

downward_direct_short_wave_radiation_flux_surface (`aswdir_s`) Surface direct short-wave radiation flux Average value since the previous forecast step.	W m-2	init_time × lead_time × latitude × longitude

precipitable_water_atmosphere (`pwat`) Precipitable water	kg m-2	init_time × lead_time × latitude × longitude

precipitation_surface (`prate`) Precipitation rate Average precipitation rate since the previous forecast step. Units equivalent to mm/s.	kg m-2 s-1	init_time × lead_time × latitude × longitude

pressure_reduced_to_mean_sea_level (`prmsl`) Pressure reduced to MSL	Pa	init_time × lead_time × latitude × longitude

pressure_surface (`sp`) Surface pressure	Pa	init_time × lead_time × latitude × longitude

relative_humidity_2m (`2r`) 2 metre relative humidity	percent	init_time × lead_time × latitude × longitude

snow_thickness_surface (`sde`) Snow depth	m	init_time × lead_time × latitude × longitude

snow_water_equivalent_surface (`sd`) Snow depth water equivalent Set to 0 over water surfaces and snow-free land points.	m	init_time × lead_time × latitude × longitude

temperature_2m (`2t`) 2 metre temperature	degree_Celsius	init_time × lead_time × latitude × longitude

total_cloud_cover_atmosphere (`tcc`) Total cloud cover	percent	init_time × lead_time × latitude × longitude

wind_gust_10m (`10fg`) Maximum 10 metre wind gust since previous post-processing	m s-1	init_time × lead_time × latitude × longitude

wind_u_10m (`10u`) 10 metre U wind component	m s-1	init_time × lead_time × latitude × longitude

wind_v_10m (`10v`) 10 metre V wind component	m s-1	init_time × lead_time × latitude × longitude

Don't see what you're looking for? Let us know at [email protected].

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

The same values are published in the dynamical-org:chunking field of this dataset's STAC collection metadata.

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.