NOAA GEFS forecast, 35 day

updating

Spatial domain	Global
Spatial resolution	0-240 hours: 0.25 degrees (~20km), 243-840 hours: 0.5 degrees (~40km)
Time domain	Forecasts initialized 2020-10-01 00:00:00 UTC to Present
Time resolution	Forecasts initialized every 24 hours.
Forecast domain	Forecast lead time 0-840 hours (0-35 days) ahead
Forecast resolution	Forecast step 0-240 hours: 3 hourly, 243-840 hours: 6 hourly

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The Global Ensemble Forecast System (GEFS) is a National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) weather forecast model. GEFS creates 31 separate forecasts (ensemble members) to describe the range of forecast uncertainty.

This dataset is an archive of past and present GEFS forecasts. Forecasts are identified by an initialization time (init_time) denoting the start time of the model run as well as by the ensemble_member. Each forecast has a 3 hourly forecast step along the lead_time dimension. This dataset contains only the 00 hour UTC initialization times which produce the full length, 35 day forecast.

Storage for this dataset is generously provided by Source Cooperative, a Radiant Earth initiative.

Dimensions

	min	max	units
ensemble_member	0	30	realization

init_time	2020-10-01T00:00:00	Present	seconds since 1970-01-01

latitude	-90	90	degrees_north

lead_time	0 days 00:00:00	35 days 00:00:00	seconds

longitude	-180	179.75	degrees_east

Variables

	units	dimensions
categorical_freezing_rain_surface Categorical freezing rain	0=no; 1=yes	init_time × ensemble_member × lead_time × latitude × longitude

categorical_ice_pellets_surface Categorical ice pellets	0=no; 1=yes	init_time × ensemble_member × lead_time × latitude × longitude

categorical_rain_surface Categorical rain	0=no; 1=yes	init_time × ensemble_member × lead_time × latitude × longitude

categorical_snow_surface Categorical snow	0=no; 1=yes	init_time × ensemble_member × lead_time × latitude × longitude

downward_long_wave_radiation_flux_surface Surface downward long-wave radiation flux Average value in the last 6 hour period (00, 06, 12, 18 UTC) or 3 hour period (03, 09, 15, 21 UTC).	W/(m^2)	init_time × ensemble_member × lead_time × latitude × longitude

downward_short_wave_radiation_flux_surface Surface downward short-wave radiation flux Average value in the last 6 hour period (00, 06, 12, 18 UTC) or 3 hour period (03, 09, 15, 21 UTC).	W/(m^2)	init_time × ensemble_member × lead_time × latitude × longitude

expected_forecast_length	seconds	init_time

geopotential_height_cloud_ceiling Geopotential height	gpm	init_time × ensemble_member × lead_time × latitude × longitude

ingested_forecast_length	seconds	init_time × ensemble_member

maximum_temperature_2m Maximum temperature	C	init_time × ensemble_member × lead_time × latitude × longitude

minimum_temperature_2m Minimum temperature	C	init_time × ensemble_member × lead_time × latitude × longitude

percent_frozen_precipitation_surface Percent frozen precipitation	%	init_time × ensemble_member × lead_time × latitude × longitude

precipitable_water_atmosphere Precipitable water	kg/(m^2)	init_time × ensemble_member × lead_time × latitude × longitude

precipitation_surface Total Precipitation Average precipitation rate since the previous forecast step.	mm/s	init_time × ensemble_member × lead_time × latitude × longitude

pressure_reduced_to_mean_sea_level Pressure reduced to MSL	Pa	init_time × ensemble_member × lead_time × latitude × longitude

pressure_surface Surface pressure	Pa	init_time × ensemble_member × lead_time × latitude × longitude

relative_humidity_2m 2 metre relative humidity	%	init_time × ensemble_member × lead_time × latitude × longitude

temperature_2m 2 metre temperature	C	init_time × ensemble_member × lead_time × latitude × longitude

total_cloud_cover_atmosphere Total Cloud Cover Average value in the last 6 hour period (00, 06, 12, 18 UTC) or 3 hour period (03, 09, 15, 21 UTC).	%	init_time × ensemble_member × lead_time × latitude × longitude

valid_time	seconds since 1970-01-01	init_time × lead_time

wind_u_100m 100 metre U wind component All lead times of this variable are interpolated from a 0.5 degree grid.	m/s	init_time × ensemble_member × lead_time × latitude × longitude

wind_u_10m 10 metre U wind component	m/s	init_time × ensemble_member × lead_time × latitude × longitude

wind_v_100m 100 metre V wind component All lead times of this variable are interpolated from a 0.5 degree grid.	m/s	init_time × ensemble_member × lead_time × latitude × longitude

wind_v_10m 10 metre V wind component	m/s	init_time × ensemble_member × lead_time × latitude × longitude

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

Examples

	Open notebook in github
	Open notebook in colab

dynamical.org - NOAA GEFS forecast, 35 day

Maximum temperature in ensemble forecast

import xarray as xr  # xarray>=2025.1.2 and zarr>=3.0.4 for zarr v3 support

ds = xr.open_zarr("https://data.dynamical.org/noaa/gefs/forecast-35-day/[email protected]")
ds['temperature_2m'].sel(init_time="2025-01-01T00", latitude=0, longitude=0).max().compute()

Details

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.

The source data is available at both 0.25-degree and 0.5-degree resolutions. All variables—except where noted, including the 100m wind components—are derived from a 0.25-degree grid for the first 240 hours of each forecast and from a 0.5-degree grid for the remainder. Bilinear interpolation is used to convert 0.5-degree data to a 0.25-degree grid. The original 0.5-degree values can be retrieved by selecting every other pixel starting from offset 0 in both the latitude and longitude dimensions (e.g. array[::2, ::2]).