The Unified Forecast System, UFS, forms the core of NOAA’s operational global modeling system for global weather across multiple time scales, including the Global Forecast System (GFS) for medium range weather out to 16 days,  the Global Ensemble Forecast System (GEFS) for subseasonal range out to 45 days, and the Seasonal Forecast System (SFS) for predictions out to one year.  Currently, the UFS consists of the FV3 dynamical core with the Common Community Physics Package (CCPP) for the atmosphere,  MOM6 for the ocean, GOCART for aerosols, CICE6 for sea ice and WW3 for ocean waves. NOAH and NOAH-MP land models are currently available as options within the CCPP framework for UFS global applications including GFS and GEFS. The components are coupled using the Community Mediator for Earth Prediction Systems (CMEPS). For the current and upcoming implementations of GFS (e.g., GFSv16 and GFSv17) and GEFS (e.g., GEFSv12 and GEFSv13) the Gridpoint Statistical Interpolation (GSI) provides the data assimilation system to initialize the model forecasts using observations for all components of the coupled systems. In the future the Joint Effort for Data Assimilation Integration (JEDI) project will replace the GSI.

The Medium-Range and Subseasonal-Seasonal (MRW/S2S) component, also referred to as the MRW/S2S Application Team, of the UFS-R2O project is focused on transitioning cutting-edge research into the operational GFS and GEFS.  The primary development foci for advancing the skill of NOAA’s operational predictions of timescales from medium-range weather to one year are:

• Diagnose the sources of and mitigate atmospheric model biases associated with parameterized physics deficiencies, especially those associated with layers of high static stability in the lower atmosphere that affect the initiation of convection and the representation of land-atmosphere interactions.

• Improved representation of tropical variability, including tropical modes such as the Madden Julian Oscillation (MJO),  El Niño–Southern Oscillation (ENSO), and the quasi-biennial oscillation (QBO) as well as their teleconnections to the midlatitudes and sudden Stratospheric warming.

• Improve quantification of model uncertainty in ensemble forecasts, particularly near model component interfaces.

• Improve initialization of (coupled) model forecasts, through improved use of observations and advances in data assimilation algorithms.

These objectives are the driving force for advancing the GFS, GEFS and SFS for the duration of the UFS R2O project , and the plan for addressing them is organized into 6 cross-cutting teams . Briefly, the cross-cutting teams  and their primary deliverables are as follows:

1. Modeling Infrastructure (learn more) 

2. Atmospheric composition (learn more)

3. Data Assimilation and Reanalysis & Reforecast (learn more)

4. Atmospheric physics (learn more)

5. Marine components (learn more)

6. Verification and Post-processing (learn more)  

The  objective of the MRW/S2S Application Team  is  to lead the develop a coupled ensemble prediction system, which consists of GFS, MOM6, CICE6, CMEPS and WWIII, for medium-range weather subseasonal to seasonal forecasts and to contribute to the development of the seasonal forecast system for operational implementation at NCEP at the conclusion of this project. The project focuses on a) improved couplings between components, performing testing and evaluation of prototypes; and, b) developing and refining stochastic parameterizations in the land, atmosphere, and ocean to improve coupled data assimilation and ensemble prediction.

To build a state-of-the-art coupled forecast system requires the participation of all  application teams and cross-cutting working groups to develop model physics, dynamics, coupling infrastructure, coupled data assimilation and verification and validation strategies. This sub-project is focused on the application of the coupled system for medium-range weather and S2S forecasting.  The goal is to develop a coupled model suitable for medium-range and S2S forecasting, to incorporate and test new and improved science and technology presented by the WGs in the coupled system, to investigate model forecast biases and feedback to the developers, to set up and test the system in the NCEP operational environment, and ultimately to put together a best performing fully coupled earth system model for NCEP operational applications, including GFS, GEFS, and SFS..

Ensemble prediction is an essential part of this coupled system. This sub-project will also develop and refine parameterizations in the coupled UFS to provide more physically based, process-level stochastic representations of model uncertainty.  This is expected to improve ensemble spread and reduce systematic error, both in coupled data assimilation and free forecasts. In coordination with the physics development application team, a long-term vision is to include a capability of modeling the stochasticity that is intrinsic to physical processes on subgrid scales in the advanced UFS physics suite for operations