NOAA HRRR analysis

Spatial domain	Continental United States
Spatial resolution	3 km
Time domain	2014-10-01 00:00:00 UTC to Present
Time resolution	1 hour

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The High-Resolution Rapid Refresh (HRRR) is a NOAA real-time 3-km resolution, hourly updated, cloud-resolving, convection-allowing atmospheric model, initialized by 3km grids with 3km radar assimilation. Radar data is assimilated in the HRRR every 15 min over a 1-h period adding further detail to that provided by the hourly data assimilation from the 13km radar-enhanced Rapid Refresh.

This analysis dataset is an archive of the model's best estimate of past weather. It is created by concatenating the first hour of each historical forecast to provide a dataset with dimensions time, x, and y.

This dataset uses the native HRRR Lambert Conformal Conic projection, with spatial indexing along the x and y dimensions. The example notebook shows how to use the embedded spatial reference to select geographic areas of interest.

Related Datasets

NOAA HRRR forecast, 48 hour - Weather forecasts from the High-Resolution Rapid Refresh (HRRR) model operated by NOAA NWS NCEP.

Examples

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

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dynamical.org - NOAA HRRR analysis

Temperature at a specific place and time

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/noaa/hrrr/analysis/latest.zarr")
ds["temperature_2m"].sel(time="2025-01-01T00", x=0, y=0, method="nearest").compute()

Dimensions

	min	max	units
time	2014-10-01T00:00:00	Present	seconds since 1970-01-01

x	-2700000	2700000	m

y	-1600000	1600000	m

Variables

	units	dimensions
categorical_freezing_rain_surface Categorical freezing rain 0=no; 1=yes	1	time × y × x

categorical_ice_pellets_surface Categorical ice pellets 0=no; 1=yes	1	time × y × x

categorical_rain_surface Categorical rain 0=no; 1=yes	1	time × y × x

categorical_snow_surface Categorical snow 0=no; 1=yes	1	time × y × x

composite_reflectivity Maximum/Composite radar reflectivity	dBZ	time × y × x

dew_point_temperature_2m 2 metre dewpoint temperature	degree_Celsius	time × y × x

downward_long_wave_radiation_flux_surface Surface downward long-wave radiation flux	W m-2	time × y × x

downward_short_wave_radiation_flux_surface Surface downward short-wave radiation flux	W m-2	time × y × x

geopotential_height_cloud_ceiling Geopotential height	m	time × y × x

latitude Latitude	degree_north	y × x

longitude Longitude	degree_east	y × x

percent_frozen_precipitation_surface Percent frozen precipitation	percent	time × y × x

precipitable_water_atmosphere Precipitable water	kg m-2	time × y × x

precipitation_surface Precipitation rate Average precipitation rate since the previous forecast step. Units equivalent to mm/s.	kg m-2 s-1	time × y × x

pressure_reduced_to_mean_sea_level Pressure reduced to MSL	Pa	time × y × x

pressure_surface Surface pressure	Pa	time × y × x

relative_humidity_2m 2 metre relative humidity	percent	time × y × x

snow_area_fraction_surface Snow cover	1	time × y × x

snow_thickness_surface Snow depth	m	time × y × x

snow_water_equivalent_surface Snow depth water equivalent	m	time × y × x

snowfall_surface Total snowfall rate Average snowfall rate since the previous forecast step.	m s-1	time × y × x

temperature_2m 2 metre temperature	degree_Celsius	time × y × x

total_cloud_cover_atmosphere Total Cloud Cover	percent	time × y × x

wind_gust_surface Wind speed (gust)	m s-1	time × y × x

wind_u_10m 10 metre U wind component	m s-1	time × y × x

wind_u_80m 80 metre U wind component	m s-1	time × y × x

wind_v_10m 10 metre V wind component	m s-1	time × y × x

wind_v_80m 80 metre V wind component	m s-1	time × y × x

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

NOAA NWS NCEP HRRR data processed by dynamical.org from NOAA Open Data Dissemination archives.

Or NOAA HRRR from dynamical.org.

Construction

HRRR starts a new model run every hour and dynamical.org has created this analysis by concatenating the first step of each forecast along the time dimension. Accumulated variables (e.g. precipitation) are read from the second step of the previous hour's forecast.

Data availability

There are a significant number of missing source files before August 2018 (HRRR v1 and v2 period), and a small number from August 2018 to December 2020 (HRRR v3 period).

downward_long_wave_radiation_flux_surface and relative_humidity_2m are unavailable before August 2016 (HRRR v1 period).

This dataset has NaN values where source data are unavailable.

Source

The source grib files this archive is constructed from are provided by NOAA Open Data Dissemination (NODD) and accessed from the AWS Open Data Registry. Operational data is additionally accessed from NOAA NOMADS.

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.