A Model Framework for Stochastic Representation of Uncertainties Associated with Physical Processes in NOAA’s Next Generation Global Prediction System (NGGPS)

AbstractIn this study we propose a physical process based stochastic parameterization scheme using cellular automata for NOAA’s next generation global prediction system. The cellular automata, used to simulate stochastic processes, such as the production and destruction of sub-grid convective elements, are conditioned on unresolved vertical motion that follows a prescribed stochastically generated skewed distribution (SGS). The SGS is described by a stochastic differential equation and linked to observations by taking into account the first four moments from an observed data-set. In the proposed parameterization framework, we emphasize the need for a dynamical memory term to be included in physical process based stochastic parameterizations, and we illustrate the requirement for the dynamical memory using the Mori-Zwanzig formalism. Although this paper focuses on the methodology, early results indicate that if we apply our stochastic framework to deep cumulus convection, it is found that the frequency dis...