NOAA Climate Test Bed - Advancing NOAA's Operational Subseasonal to Seasonal Prediction Capability

NOAA’s Modeling, Analysis, Predictions, and Projections (MAPP) Program is funding seven new Climate Test Bed projects (six grants, seven other awards) for an initial $1.03 million and a $2.04 million over the life of the project (two years).

NOAA’s operational prediction efforts are a core part of NOAA’s mission to support economic vitality and protect American lives and resources. As part of NOAA’s research Line Office OAR, the MAPP program supports research and its transition into improved operational capabilities, products, and services. MAPP supports research to improve the NWS National Centers for Environmental Prediction (NCEP) Climate Prediction Center’s operational products in part by partnering with NCEP to support the Climate Test Bed to test and demonstrate the potential for scientific advances from the community external to NCEP to improve operational climate predictions. MAPP provides support for testing and demonstration research phases, whereas NCEP provides support for the operational implementation phase.

In FY 2018, the MAPP Program, in partnership with the NWS/OSTI/NGGPS Program, solicited proposals involving the external community to advance the Climate Prediction Center’s subseasonal to seasonal prediction capabilities via the Climate Test Bed. These project build on a long and highly successful series of investments that have resulted in numerous prominent operational transitions at the Weather Service, including the Noah land surface model and improvements, the CPC week 3-4 forecast products, various operational drought products, the North American Multi Model Ensemble, various improvements to the operational Climate Forecast System, and many others. Research projects for FY18-FY19 will focus on the following areas:

  1. Testing and demonstration of experimental prediction methodologies (e.g. new calibration or post-processing techniques, verification techniques) or systems (e.g., experimental multi-model combinations, hybrid statistical/dynamical systems, merging of systems across timescales to advance subseasonal prediction) developed in the broader community for operational purposes.
  2. Improving multi-model ensemble prediction systems such as the North American Multi Model Ensemble (NMME ) by testing and demonstrating the utility of new or higher-resolution models, improved forecast initialization practices, or upgrades to other aspects of the system.

The seven new projects supported by MAPP CTB in FY18 include:

  • “A Hybrid Statistical-Dynamical System for the Seamless Prediction of Daily Extremes and Subseasonal to Seasonal Climate Variability”
    • PI: Dan Collins, NOAA/CPC
  • “A New Technique for Improved MJO Prediction”
    • PI: Chidong Zhang, NOAA/PMEL
    • Co-PI: Wanqiu Wang, NOAA/CPC
  • “Operational transition of novel statistical–dynamical forecasts for tropical subseasonal-to-seasonal drivers”
    • PI: Carl Schreck, North Carolina State University
    • Co-PI: Stephen Baxter, NOAA/CPC
  • “Sensitivity of NMME Seasonal Predictions to Ocean Eddy Resolving Coupled Models”
    • PI: Benjamin Kirtman, University of Miami-RSMAS
    • Co-PI: Robert Burgman, Florida International University
  • “Skillfully Predicting Atmospheric Rivers and Their Impacts in Weeks 2-5 Based on the State of the MJO and QBO”
    • PI: Elizabeth Barnes, Colorado State University
  • “Subseasonal to Seasonal Prediction with NCAR’s CESM2-WACCM”
    • PI: Jadwiga Richter, UCAR
    • Co-PIs: Dan Collins, NOAA/CPC; Judith Perlwitz, NOAA/ESRL/PSD
  • “Testing, refinement and demonstration of probabilistic multi-model, calibrated sub-seasonal global forecast products”
    • PI: Andrew Robertson, Columbia University
    • Co-PI: Dan Collins, NOAA/CPC

The OAR Office of Weather and Air Quality consulted on funding decisions for these new projects.


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