NOAA GFS analysis, hourly

available

Spatial domain	Global
Spatial resolution	0.25 degrees (~20km)
Time domain	2015-01-15 00:00:00 UTC to 2024-07-01 00:00:00 UTC
Time resolution	1 hour

⎘

* Email optional. Providing your email as a query param helps us understand usage and impact to keep dynamical.org supported for the long-term. For catalog updates follow here.

The Global Forecast System (GFS) is a National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) weather forecast model that generates data for dozens of atmospheric and land-soil variables, including temperatures, winds, precipitation, soil moisture, and atmospheric ozone concentration. The system couples four separate models (atmosphere, ocean model, land/soil model, and sea ice) that work together to depict weather conditions.

This dataset is an "analysis" containing the model's best estimate of each value at each timestep. In other words, it does not contain a forecast dimension. GFS starts a new model run every 6 hours and dynamical.org has created this analysis by concatenating the first 6 hours of each forecast. Before 2021-02-27 GFS had a 3 hourly step at early forecast hours. In this reanalysis we have used linear interpolation in the time dimension to fill in the two timesteps between the three-hourly values prior to 2021-02-27.

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

Dimensions

	min	max	units
latitude	-90	90	decimal degrees

longitude	-180	179.75	decimal degrees

time	2015-01-15 00:00:00 UTC	2024-06-30 23:00:00 UTC	seconds since 1970-01-01 00:00:00

Variables

	units	dimensions
precipitation_surface Precipitation rate at earth surface	kg/(m^2 s)	time × latitude × longitude

temperature_2m Temperature 2 meters above earth surface	C	time × latitude × longitude

wind_u_10m Wind speed u-component 10 meters above earth surface	m/s	time × latitude × longitude

wind_v_10m Wind speed v-component 10 meters above earth surface	m/s	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 GFS analysis, hourly

Mean temperature for a single day

import xarray as xr

ds = xr.open_zarr("https://data.dynamical.org/noaa/gfs/analysis-hourly/[email protected]")
ds["temperature_2m"].sel(time="2024-06-01T00:00").mean().compute()

Details

The data values in this dataset have been rounded in their binary representation to improve compression. We round to retain 9 bits of the floating point number's mantissa (a 10 digit significand) which creates a maximum of 0.2% difference between the original and rounded value. See Klöwer et al. 2021 for more information.