Purpose and scope
The NOAA Unified Forecast System (UFS) / Global Ensemble Forecast System version 13 (GEFSv13) replay data set was developed to provide initial conditions for the retrospective forecast archive in support of the next implementation of the NOAA medium range forecast system (GEFSv13 / GFSv17).
This data set was produced by replaying [Orbe et.al 2017] the coupled version of the new UFS model to external reanalyses: ERA5 for the atmosphere and ORAS5 for the ocean and ice. For the replay experiment, we used the HR1 tag of the NOAA UFS coupled model that included atmospheric, oceanic, ice, land, and wave model components (see Table 1 for component description).
Table 1: Summary of the UFS and reply components in the GEFSv13 replay dataset.
Earth system component Model version Resolution Replay constraint Atmosphere UFS/FV3. HR1 physics C386 cube sphere (¼ degree), 127 vertical levels Temperature, specific humidity, winds (horizontal velocity components), ozone, surface pressure replayed to ERA5 Land Noah-MP LSM Four vertical levels Snow depth assimilation from NCEI Global Historical Climatology Network (GHCN) and snow cover from U.S. National Ice Center Interactive Multisensor Snow and Ice Mapping System (IMS) Ocean MOM6 72 hybrid levels, nominal ¼ degree tri-polar grid Temperature, salinity, currents (horizontal velocity components) replayed to ORAS5 Ice CICE6 ¼ degree tri-polar grid, 5 ice categories, 7 model levels Ice concentration inserted from ORAS5 using Sea-ice, Ocean, and Coupled Assimilation project (SOCA) Wave WaveWatch III ¼ degree None
Replay methodology allows the resulting dataset to track the dynamics of selected variables from the external reference dataset, yet allows for the coupled model to generate unconstrained model variables consistent with the UFS dynamics. For example, the replay constrains the dynamics of the (3d) temperature, humidity, and winds in the atmosphere and temperature, salinity and currents in the ocean. At the same time, the UFS model was free to compute its own surface fluxes between coupled components and to compute land and wave model states that were not directly constrained by the external reanalyses.
In addition to replaying the atmospheric and oceanic states to the external reanalysis, we used a future version of NOAA’s JEDI-based land data assimilation system (Gichamo and Draper, 2022) to constrain snow depth by assimilating snow depth observations from the NCEI Global Historical Climatology Network (GHCN) daily station data and satellite-derived snow cover from the U.S. National Ice Center Interactive Multisensor Snow and Ice Mapping System (IMS). The JEDI Sea-ice Ocean and Coupled Analysis system (SOCA) was used to adjust the sea-ice thickness, concentration, and the snow-depth over ice to be consistent with the ORAS5 sea-ice analysis.
The original replay dataset covered the period from January 1994 to October 2023 at a nominal ¼ resolution. Since the original production, the replay dataset was extended several times to near present day. We expect to continue these extensions until GEFSv13 / GFSv17 is transitioned to operational practice. In addition to the ¼ version of the replay dataset, we are also producing a native 1 degree version of the replay dataset by replaying the 1 degree version of the UFS model to ERA5 and ORAS5 reanalysis for the period 1958 to 2023. A sample of the 1 degree native replay data is available and will be extended as model output is produced.
The replay dataset is staged in an egress free environment on AWS and GCP cloud services, courtesy of the NOAA Open Data Dissemination program. The original output of the model is stored in AWS using native model output. To facilitate analysis of the replay dataset and to enable efficient AI training pipelines, we also have a curated version of the replay dataset in the zarr format on the GCP cloud service. (see Data access tab for details)
