NOAA GEFS forecast, 35 day

Weather forecasts from the Global Ensemble Forecast System (GEFS) model operated by NOAA NWS NCEP, transformed into Zarr format by dynamical.org.

Product Details

Visibility: Public
Owner: dynamical.org
Created: 25 Feb 2025
Last Updated: 15 Aug 2025

Product Contents

NOAA GEFS forecast, 35 day - dynamical.org zarr


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

Description

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.

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.

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

Dimensions

Dimension	Min	Max	Units
init_time	2020-10-01T00:00:00	Present	seconds since 1970-01-01
ensemble_member	0	30	realization
lead_time	0 days 00:00:00	35 days 00:00:00	seconds
latitude	-90	90	degrees_north
longitude	-180	179.75	degrees_east

Variables

Variable	Units	Dimensions
categorical_freezing_rain_surface	0=no; 1=yes	init_time × ensemble_member × lead_time × latitude × longitude
categorical_freezing_rain_surface_avg	0=no; 1=yes	init_time × lead_time × latitude × longitude
categorical_ice_pellets_surface	0=no; 1=yes	init_time × ensemble_member × lead_time × latitude × longitude
categorical_ice_pellets_surface_avg	0=no; 1=yes	init_time × lead_time × latitude × longitude
categorical_rain_surface	0=no; 1=yes	init_time × ensemble_member × lead_time × latitude × longitude
categorical_rain_surface_avg	0=no; 1=yes	init_time × lead_time × latitude × longitude
categorical_snow_surface	0=no; 1=yes	init_time × ensemble_member × lead_time × latitude × longitude
categorical_snow_surface_avg	0=no; 1=yes	init_time × lead_time × latitude × longitude
downward_long_wave_radiation_flux_surface	W/(m^2)	init_time × ensemble_member × lead_time × latitude × longitude
downward_long_wave_radiation_flux_surface_avg	W/(m^2)	init_time × lead_time × latitude × longitude
downward_short_wave_radiation_flux_surface	W/(m^2)	init_time × ensemble_member × lead_time × latitude × longitude
downward_short_wave_radiation_flux_surface_avg	W/(m^2)	init_time × lead_time × latitude × longitude
expected_forecast_length	seconds	init_time
geopotential_height_cloud_ceiling	gpm	init_time × ensemble_member × lead_time × latitude × longitude
ingested_forecast_length	seconds	init_time × ensemble_member
maximum_temperature_2m	C	init_time × ensemble_member × lead_time × latitude × longitude
maximum_temperature_2m_avg	C	init_time × lead_time × latitude × longitude
minimum_temperature_2m	C	init_time × ensemble_member × lead_time × latitude × longitude
minimum_temperature_2m_avg	C	init_time × lead_time × latitude × longitude
percent_frozen_precipitation_surface	%	init_time × ensemble_member × lead_time × latitude × longitude
precipitable_water_atmosphere	kg/(m^2)	init_time × ensemble_member × lead_time × latitude × longitude
precipitable_water_atmosphere_avg	kg/(m^2)	init_time × lead_time × latitude × longitude
precipitation_surface	kg/(m^2)	init_time × ensemble_member × lead_time × latitude × longitude
precipitation_surface_avg	kg/(m^2)	init_time × lead_time × latitude × longitude
pressure_reduced_to_mean_sea_level	Pa	init_time × ensemble_member × lead_time × latitude × longitude
pressure_reduced_to_mean_sea_level_avg	Pa	init_time × lead_time × latitude × longitude
pressure_surface	Pa	init_time × ensemble_member × lead_time × latitude × longitude
pressure_surface_avg	Pa	init_time × lead_time × latitude × longitude
relative_humidity_2m	%	init_time × ensemble_member × lead_time × latitude × longitude
relative_humidity_2m_avg	%	init_time × lead_time × latitude × longitude
temperature_2m	C	init_time × ensemble_member × lead_time × latitude × longitude
temperature_2m_avg	C	init_time × lead_time × latitude × longitude
total_cloud_cover_atmosphere	%	init_time × ensemble_member × lead_time × latitude × longitude
total_cloud_cover_atmosphere_avg	%	init_time × lead_time × latitude × longitude
valid_time	seconds since 1970-01-01	init_time × lead_time
wind_u_100m	m/s	init_time × ensemble_member × lead_time × latitude × longitude
wind_u_10m	m/s	init_time × ensemble_member × lead_time × latitude × longitude
wind_u_10m_avg	m/s	init_time × lead_time × latitude × longitude
wind_v_100m	m/s	init_time × ensemble_member × lead_time × latitude × longitude
wind_v_10m	m/s	init_time × ensemble_member × lead_time × latitude × longitude
wind_v_10m_avg	m/s	init_time × lead_time × latitude × longitude

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NOAA GEFS forecast, 35 day

NOAA GEFS forecast, 35 day

NOAA GEFS forecast, 35 day - dynamical.org zarr

Data Access

Description

Dimensions

Variables

Examples