ECMWF AIFS Single forecast

Spatial domain	Global
Spatial resolution	0.25 degrees (~20km)
Time domain	Forecasts initialized 2024-04-01 00:00:00 UTC to Present
Time resolution	Forecasts initialized every 6 hours
Forecast domain	Forecast lead time 0-360 hours (0-15 days) ahead
Forecast resolution	6 hourly

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The Artificial Intelligence Forecasting System (AIFS) is a data driven forecast model developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). This is the non-ensemble configuration of AIFS that produces a single forecast trace. AIFS is trained on ECMWF's ERA5 re-analysis and ECMWF's operational numerical weather prediction (NWP) analyses.

This dataset is an archive of past and present ECMWF AIFS Single forecasts. Forecasts are identified by an initialization time (init_time) denoting the start time of the model run. Each forecast steps forward in time along the lead_time dimension, from 0 to 360 hours (15 days) at a 6 hourly step.

Examples

	Open notebook in github
	Open notebook in colab
	Icechunk example usage notebook ***

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dynamical.org - ECMWF AIFS Single forecast

Maximum temperature in a forecast

import xarray as xr  # xarray>=2025.1.2 and zarr>=3.0.8 for zarr v3 support

ds = xr.open_zarr("https://data.dynamical.org/ecmwf/aifs-single/forecast/latest.zarr")
ds["temperature_2m"].sel(init_time="2025-01-01T00", latitude=0, longitude=0).max().compute()

Dimensions

	min	max	units
init_time	2024-04-01T00:00:00	Present	seconds since 1970-01-01

latitude	-90	90	degree_north

lead_time	0 days 00:00:00	15 days 00:00:00	seconds

longitude	-180	179.75	degree_east

Variables

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

downward_long_wave_radiation_flux_surface (`sdlwrf`) Surface downward long-wave radiation flux	W m-2	init_time × lead_time × latitude × longitude

downward_short_wave_radiation_flux_surface (`sdswrf`) Surface downward short-wave radiation flux	W m-2	init_time × lead_time × latitude × longitude

expected_forecast_length Expected forecast length	seconds	init_time

geopotential_height_500hpa (`gh`) Geopotential height	m	init_time × lead_time × latitude × longitude

geopotential_height_850hpa (`gh`) Geopotential height	m	init_time × lead_time × latitude × longitude

geopotential_height_925hpa (`gh`) Geopotential height	m	init_time × lead_time × latitude × longitude

ingested_forecast_length Ingested forecast length	seconds	init_time

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

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

temperature_850hpa (`t`) Temperature	degree_Celsius	init_time × lead_time × latitude × longitude

temperature_925hpa (`t`) Temperature	degree_Celsius	init_time × lead_time × latitude × longitude

total_cloud_cover_atmosphere (`tcc`) Total Cloud Cover	percent	init_time × lead_time × latitude × longitude

valid_time Valid time	seconds since 1970-01-01	init_time × lead_time

wind_u_100m (`100u`) 100 metre U wind component	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_100m (`100v`) 100 metre V 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

This data is based on data and products of the European Centre for Medium-Range Weather Forecasts (ECMWF). Use is governed by the CC BY 4.0 license and the ECMWF Terms of Use.

Attribution and citation

ECMWF AIFS Single forecast data processed by dynamical.org from ECMWF Open Data.

Or ECMWF AIFS Single from dynamical.org.

Source

The source grib files this archive is constructed from are provided by ECMWF Open Data and accessed from the AWS Open Data Registry.

ECMWF does not provide user support for the free & open datasets. Users should refer to the public User Forum for any questions related to the source material.

Model updates

AIFS is updated regularly. Find details of recent and upcoming changes to the forecasting system on the ECMWF website.

Storage

Storage for this dataset is generously provided by Source Cooperative, a Radiant Earth initiative. Icechunk storage generously provided by AWS Open Data.

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.