From lisa.bengtsson at noaa.gov Tue Jan 22 10:52:28 2019 From: lisa.bengtsson at noaa.gov (Lisa Bengtsson - NOAA Affiliate) Date: Tue, 22 Jan 2019 10:52:28 -0700 Subject: [Stoch] Stochastic physics parameterization Message-ID: Dear all, I would like to bring your attention to our recent study published in MWR: Bengtsson, L., J. Bao, P. Pegion, C. Penland, S. Michelson, and J. Whitaker : A model framework for stochastic representation of uncertainties associated with physical processes in NOAA?s Next Generation Global Prediction System (NGGPS). Here is the abstract: In 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 distribution of precipitation is improved in a single member stochastic forecast, and that some improved spread/skill relationship in ensemble runs can be found in state-variables in the tropics, as well as sub-tropics. Kind regards, Lisa --------------------------------- --------------------------------- Lisa Bengtsson Phone : 1 (303) 497 5971 Research Scientist - Meteorologist University of Colorado/NOAA Earth System Research Lab Email: lisa.bengtsson at noaa.gov 325 Broadway Office: Skaggs Research Cntr 3B-307 Boulder, CO, USA 80303-3328 -------------- next part -------------- An HTML attachment was scrubbed... URL: