Proposal Title: A diagnostic toolbox for the verification and validation of subseasonal stratosphere-troposphere coupling processes in NOAA’s Unified Forecast System
Principal Investigator: Eric Ray (CIRES and NOAA/ESRL/CSD)
Co-Investigators:
Amy H. Butler (CIRES and NOAA/ESRL/CSD)
Judith Perlwitz (NOAA/ESRL PSD)
Craig Long (NOAA/NCEP CPC)
Collaborators:
EMC, CPC, NOAA/ESRL PSD
ABSTRACT:
Dynamic coupling between the stratosphere and the troposphere is an important potential source of subseasonal to seasonal (S2S) predictive skill of surface temperature and precipitation. Nonetheless, NOAA forecast models do not take full advantage of this source. One issue is that certain stratospheric phenomenon and processes, such as the Quasi-biennial Oscillation and wave dynamics are poorly simulated in prediction systems due to sensitivities to model vertical resolution, model tops, and adequate, small-scale gravity wave drag parameterization. Another issue is that systematic bias correction must be properly accounted for, as S2S prediction systems have stratospheric temperature biases that are coupled with biases in both the stratospheric and tropospheric large-scale circulation. Identifying these biases and model deficiencies is critical for improving forecasting on subseasonal to seasonal timescales including weeks 3-4.
We propose to develop a diagnostic toolbox to efficiently analyze relevant stratospheric processes, their forecast biases and verification, and their predicted coupling to sensible weather in the new NCEP operational FV3-based Global Ensemble Forecast System (FV3-GEFS). Primary project objectives are (1) the development of process-based diagnostics to assess stratospheric biases and stratosphere-troposphere coupling in the coupled forecast system; (2) the formulation of new validation and verification metrics designed to exploit opportunistic stratospheric information for improving Weeks 3-4 prediction; and (3) the application of these diagnostics and metrics to upcoming NOAA GEFS-FV3 reforecasts and real-time forecasts.
The project addresses the program priority Advances in verification and validation by developing process-based diagnostics designed to improve forecasting across various scales. Through collaborations with NCEP’s Environmental Modeling Center (EMC) and the Developmental Testbed Center (DTC), the compatibility of the developed toolbox with DTC’s Model Evaluation Tool (MET) verification package will be ensured.
