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 |
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
|
Quickstart (Github) |
|
Quickstart (Colab) |
import dynamical_catalog # dynamical-catalog>=0.5.0
ds = dynamical_catalog.open("noaa-hrrr-analysis")
ds["temperature_2m"].sel(time="2025-01-01T00", x=0, y=0, method="nearest").compute()Dimensions
| min | max | units | |
|---|---|---|---|
| time | 2014-10-01T00:00:00Z | Present | seconds since 1970-01-01 |
| x | -2697520.143 | 2696479.857 | m |
| y | -1587306.153 | 1586693.847 | m |
Variables
Access a variable by its name (the bold identifier, e.g. ds["categorical_freezing_rain_surface"]).
Dimensions: time × y × x
| variable | units |
|---|---|
categorical_freezing_rain_surface
Categorical freezing rain (cfrzr)0=no; 1=yes
|
1 |
categorical_ice_pellets_surface
Categorical ice pellets (cicep)0=no; 1=yes
|
1 |
categorical_rain_surface
Categorical rain (crain)0=no; 1=yes
|
1 |
categorical_snow_surface
Categorical snow (csnow)0=no; 1=yes
|
1 |
composite_reflectivity
Maximum/Composite radar reflectivity (refc)
|
dBZ |
dew_point_temperature_2m
2 metre dewpoint temperature (2d)
|
degree_Celsius |
downward_long_wave_radiation_flux_surface
Surface downward long-wave radiation flux (sdlwrf)
|
W m-2 |
downward_short_wave_radiation_flux_surface
Surface downward short-wave radiation flux (sdswrf)
|
W m-2 |
geopotential_height_cloud_ceiling
Geopotential height (gh)
|
m |
percent_frozen_precipitation_surface
Percent frozen precipitation (cpofp)
|
percent |
precipitable_water_atmosphere
Precipitable water (pwat)
|
kg m-2 |
precipitation_surface
Precipitation rate (prate)Average precipitation rate since the previous forecast step. Units equivalent to mm/s.
|
kg m-2 s-1 |
pressure_reduced_to_mean_sea_level
Pressure reduced to MSL (prmsl)
|
Pa |
pressure_surface
Surface pressure (sp)
|
Pa |
relative_humidity_2m
2 metre relative humidity (2r)
|
percent |
snow_area_fraction_surface
Snow cover (snowc)
|
1 |
snow_thickness_surface
Snow depth (sde)
|
m |
snow_water_equivalent_surface
Snow depth water equivalent (sd)
|
m |
snowfall_surface
Total snowfall rate (tsrate)Average snowfall rate since the previous forecast step.
|
m s-1 |
temperature_2m
2 metre temperature (2t)
|
degree_Celsius |
total_cloud_cover_atmosphere
Total cloud cover (tcc)
|
percent |
wind_gust_surface
Wind speed (gust) (gust)
|
m s-1 |
wind_u_10m
10 metre U wind component (10u)
|
m s-1 |
wind_u_80m
80 metre U wind component (80u)
|
m s-1 |
wind_v_10m
10 metre V wind component (10v)
|
m s-1 |
wind_v_80m
80 metre V wind component (80v)
|
m s-1 |
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.
Chunks & shards
This dataset is stored in Zarr format, which splits each variable into a grid of chunks — the smallest unit read from storage. Chunks are grouped into larger shards (the objects actually written to storage), which keeps the object count manageable for long-archive datasets. When possible, aligning your reads with this dataset's chunk grid can significantly improve data access speed.
The element count and coordinate span of this dataset:
| dimension | chunk | shard |
|---|---|---|
| time | 2160 (90 days) | 2160 (90 days) |
| y | 45 (135 km) | 540 (1620 km) |
| x | 45 (135 km) | 450 (1350 km) |
| uncompressed | 16.7 MiB | 2.0 GiB |
The same values are published in the dynamical-org:chunking field of this dataset's STAC collection metadata.
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.