Install DagsHub:
pip install dagshubTo stream this data directly on DagsHub
from dagshub.streaming import DagsHubFilesystem
fs = DagsHubFilesystem(".", repo_url="https://test.dagshub.com/DagsHub-Datasets/noaa-rrfs-dataset")
fs.listdir("s3://noaa-rrfs-pds")Description
The Rapid Refresh Forecast System (RRFS) is the National Oceanic and Atmospheric Administration’s (NOAA) next generation convection-allowing, rapidly-updated ensemble prediction system, currently scheduled for operational implementation in 2024. The operational configuration will feature a 3 km grid covering North America and include deterministic forecasts every hour out to 18 hours, with deterministic and ensemble forecasts to 60 hours four times per day at 00, 06, 12, and 18 UTC.The RRFS will provide guidance to support forecast interests including, but not limited to, aviation, severe convective weather, renewable energy, heavy precipitation, and winter weather on timescales where rapidly-updated guidance is particularly useful.
The RRFS is underpinned by the Unified Forecast System (UFS), a community-based Earth modeling initiative, and benefits from collaborative development efforts across NOAA, academia, and research institutions.
This bucket provides access to real time, experimental RRFS prototype output as of October 2022. This bucket also holds output from past experimental RRFS prototypes that were evaluated as a part of NOAA testbed projects. The immediate section describes the data for the real time system. The section that follows thereafter describes outputs from three past NOAA Testbed experiments.
Real time, experimental RRFS Prototype output
The real-time RRFS prototype is experimental and evolving. It is not under 24×7 monitoring and is not operational. Output may be delayed or missing. Outputs will change. When significant changes to output take place, this description will be updated.
We currently provide hourly deterministic forecasts at 3 km grid spacing over the CONUS out to 60 hours at 00 and 12 UTC, and out to 18 hours at other times. Future enhancements will include an ensemble forecast component and expansion to the planned North American domain. All forecasts are initialized from a hybrid 3DEnVar data assimilation system with hourly updates. Output is available on the S3 bucket for every third cycle, and is organized by cycle day and time of day. For example, `rrfs_a/rrfs_a.20221012/00/` contains the forecast initialized at 00 UTC on 12 October 2022. Users will find two types of output in GRIB2 format. The first is:
rrfs.t00z.natlev.f018.conus_3km.grib2
Meaning that this is the RRFS_A initialized at 00 UTC, covers the CONUS domain, and is the native level post-processed gridded data at hour 18. This output is on a Lambert Conic Conformal domain at 3 km grid spacing.
The second output file in grib2 format is:
rrfs.t00z.prslev.f018.conus_3km.grib2
Meaning that this is the pressure level post-processed gridded data.
Past output from NOAA Testbed Experiments
This bucket also provides datasets from three of the 2021 NOAA Testbed Experiments. During each of these experiments, a prototype version of RRFS under development was run. The following is a high-level overview dates and RRFS configurations for each of the Testbed Experiments.
2021 Hazardous Weather Testbed (HWT) Spring Forecast Experiment (May 3 through June 4 2021) and 2021 Hydrometeorological Testbed Annual Flash Flood and Intense Rainfall Experiment (FFaIR) (June 21 through July 23 2021, excluding the week of July 4). A 9-member multi-physics ensemble with stochastic perturbations run once per day at 3 km grid spacing covering North America out to 60 hours. Initial conditions and lateral boundary conditions are taken from the GFS and GEFS.
2021-2022 Hydrometeorological Testbed Winter Weather Experiment (WWE) (mid November through mid-March). Select cases only. Deterministic forecasts were run once per day at 00 UTC at 3 km grid spacing covering the CONUS out to 60 hours. A 36-member, 3 km ensemble Kalman filter data assimilation approach is implemented through hourly cycling starting at 18 UTC on the previous day.
For each cycle of the HWT and FFaIR experiments, the dataset is organized by cycle day, time of day, and member. For example, `rrfs.20210504/00/mem01/` contains the forecast from ensemble member 1 initialized at 00 UTC on 04 May 2021. Users will find two types of output in GRIB2 format. The first is:
rrfs.t00z.mem01.naf024.grib2
Meaning that this is RRFS ensemble member 1 initialized at 00 UTC, covers the North American domain, and is the post-processed gridded data at hour 24. This output is on a rotated latitude-longitude domain at 3 km grid spacing. These are large files and users may wish to subset or re-project the grid after downloading. We recommend using the WGRIB2 application for such purposes.
The second output file in grib2 format is as follows:
rrfs.t00z.mem01.testbed.conusf020.grib2
These grids have been subset from the much larger North American domain to a CONUS domain on a Lambert Conic Conformal projection and also contain significantly fewer fields, resulting in smaller files.
Graphics for select runs are also included in a plots/ directory under each experiment day for quick, yet simple visualization.
For each cycle of the WWE, the dataset is organized by cycle day and time of day. For example, `rrfs.20220306/00/` contains data for the forecast initialized at 00 UTC on 06 March 2022. The initial conditions for the 36 ensemble members are located in the `ens_ics/mem???` subdirectories. Users will find two types of output in GRIB2 format in the post subdirectories. The first is:
BGDAWP.GrbF12
Meaning that this is the forecast initialized at 00 UTC, covers the CONUS domain, and is the pressure level post-processed gridded data at forecast hour 18. This output is on a Lambert Conic Conformal grid at 3 km grid spacing.
The second output file in grib2 format is as follows:
testbed.conusf030.grib2
These grids contain significantly fewer fields, resulting in smaller files.
This work is supported by the Unified Forecast System Research to Operation (UFS R2O) Project which is jointly funded by NOAA’s Office of Science and Technology Integration (OSTI) of National Weather Service (NWS) and Weather Program Office (WPO), [Joint Technology Transfer Initiative (JTTI)] of the Office of Oceanic and Atmospheric Research (OAR).
*DISCLAIMER* The output provided here is experimental and is subject to change, outages, and gaps. Please contact the data managers for additional information or questions.
Additional information
Documentation
Update frequency
Daily
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License
Open Data. There are no restrictions on the use of this data.
