Simulation of Subgrid Orographic Convection and Precipitation with 2-D Cloud-Resolving Models Embedded in a GCM Grid

Friday, 18 December 2015
Poster Hall (Moscone South)
Joonhee Jung, Colorado State University, Department of Atmospheric Science, Fort Collins, CO, United States and Akio Arakawa, University of California Los Angeles, Atmospheric and Oceanic Sciences, Los Angeles, CA, United States
Through explicitly resolved cloud-scale processes by embedded 2-D cloud-resolving models (CRMs), the Multiscale Modeling Framework (MMF) known as the superparameterization has been reasonably successful to simulate various atmospheric events over a wide range of time scales. One thing to be justified is, however, if the influence of complex 3-D topography can be adequately represented by the embedded 2-D CRMs. In this study, simulations are performed in the presence of a variety of topography with embedded 3-D and 2-D CRMs in a single-column inactive GCM. Through the comparison between these simulations, it is demonstrated that the 2-D representation of topography is able to simulate the statistics of precipitation due to 3-D topography reasonably well as long as the topographic characteristics, such as the mean and standard deviation, are closely recognized. It is also shown that the use of two perpendicular sets of 2-D representations tends to reduce the error due to a 2-D representation.