Accelerating Stochastic Physics Development in the NOAA Unified Forecast System (UFS)

Modern numerical weather prediction (NWP) model forecasts for various applications require not only high-quality deterministic forecasts but also information about forecast uncertainty. An ensemble forecast is commonly used to provide an estimation of forecast uncertainty. Since a great deal of the forecast uncertainty comes from dynamical processes not resolved or explicitly represented by NWP models, there is a need to correctly quantify and simulate NWP model uncertainty for an ensemble forecast to be useful and reliable.

We present an overview of a theoretical framework for accelerating the stochastic parametrization development in NOAA’s UFS to simulate the uncertainty in unresolved physics. This framework is derived from the connection in mathematical physics between the Mori-Zwanzig formalism and multidimensional Langevin processes. It serves as the physical basis for the future development of stochastic physics parameterization schemes in the UFS. Using this framework, we have developed a new process-level stochastic physics parameterization scheme in the UFS, which is formulated as a multidimensional Langevin process. We illustrate that the previously implemented stochastic physics schemes in the UFS are simplified variants of multidimensional Langevin processes. We will also show a preliminary performance comparison of these variants with the process-level scheme in the UFS ensemble predictions on short, medium and the sub-seasonal scales.