The High-Resolution Rapid Refresh (HRRR)

Composite Reflectivity
The 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
.
HRRR implementations at NCEP
- HRRRv1 - 30 Sept 2014
- HRRRv2 - 23 Aug 2016
- HRRRv3 - 12 July 2018
- HRRRv4 - 2 Dec 2020
Information here in
HRRRv4/RAPv5 summary - Jan 2020
HRRR Colorado Labs Award video
- a 2-minute layperson-level description on the HRRR from late 2015
and why it is important. (October 2015)
HRRRv4/RAPv5
.
Key features for HRRRv4:
- improved cloud representation for boundary-top clouds, especially for shallow cold-air layers with cold-air retention
- better cloud bands (snow squalls, hurricane bands, lake-effect bands)
- 3km ensemble data assimilation for improved storm prediction for 1-12h
- inline smoke prediction
- improved lake temperatures
- Extension to 48h forecast every 6h.
HRRR Ensemble (HRRRE) prediction -
documentation as of March 2020
2022 HRRR description - Dowell et al 2022
HRRRv2 physics description in
Benjamin et al. 2016,
A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh.
Mon. Wea. Rev., 144, 1669-1694.
-
Google Cloud Platform HRRR archive
- native, isobaric, surface - since 2014
requires installing a program called gsutil, but once that is done it is very straightforward to get one or multiple files.
-
https://cloud.google.com/storage/docs/gsutil_install
AWS - Amazon Web Services - HRRR archive
- native, isobaric, surface - since 2014
Univ. of Utah HRRR archive - surface, isobaric - for HRRR-oper and HRRR-experimental
Python library used to pull HRRR archive data from different cloud archive sources
NOAA NOMADS archive
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