Downscaling mesoscale meteorological models for computational wind engineering applications

Abstract Considerable interest exists in joining the capabilities of mesoscale meteorological models (MMM) with those of computational wind engineering (CWE) models to produce realistic simulations, which address emerging issues in wind engineering and environmental applications. The model equations are similar for MMM and CWE, but there are significant differences in the objectives and approaches. Complete synthesis of these models is still premature and computational burdens are enormous. Appropriate procedures for joining these models have not been established yet and measurement data required for verification is limited. For convenience in presentations and discussions, coupling methods are divided into four groups: (1) coupling MMM and CWE models for up-scaling or downscaling, (2) up-scaling a CWE model to include the mesoscale meteorological influences, (3) downscaling an MMM to include the CWE capabilities, and (4) a combination of the above three approaches. Mochida et al. (this issue) focuses on up-scaling CWE from an engineering point of view and the present paper focuses on downscaling MMM from a meteorological point of view. Topics addressed here are (1) to understand the differences in the purposes and approaches of MMM and CWE models and (2) to identify issues and explore ways of coupling MMM and CWE modeling capabilities.

[1]  R. Pielke,et al.  A comprehensive meteorological modeling system—RAMS , 1992 .

[2]  Yoshihide Tominaga,et al.  Up-scaling CWE models to include mesoscale meteorological influences , 2011 .

[3]  G. Mellor,et al.  Development of a turbulence closure model for geophysical fluid problems , 1982 .

[4]  Michael Schatzmann,et al.  Flow and Transport in the Obstacle Layer: First Results of the Micro-Scale Model MITRAS , 2003 .

[5]  R. Pielke Mesoscale Meteorological Modeling , 1984 .

[6]  Ralf Koppmann,et al.  Joint modelling of obstacle induced and mesoscale changes—Current limits and challenges , 2011 .

[7]  Li-Jie Zhang,et al.  Study on the micro-scale simulation of wind field over complex terrain by RAMS/FLUENT modeling system , 2010 .

[8]  Richard A. Anthes,et al.  Data Assimilation and Initialization of Hurricane Prediction Models , 1974 .

[9]  Katharina Heinke Schlünzen,et al.  Influence of thermal effects on street canyon circulations , 2004 .

[10]  G. Mellor,et al.  A Hierarchy of Turbulence Closure Models for Planetary Boundary Layers. , 1974 .

[11]  S. Bunker,et al.  Development of a Nested Grid, Second Moment Turbulence Closure Model and Application to the 1982 ASCOT Brush Creek Data Simulation , 1988 .

[12]  D. Randerson,et al.  Atmospheric science and power production , 1984 .

[13]  Three-dimensional prediction of maize pollen dispersal and cross-pollination, and the effects of windbreaks. , 2009, Environmental biosafety research.

[14]  Tetsuji Yamada,et al.  Simulations of Nocturnal Drainage Flows by a q2l Turbulence Closure Model , 1983 .

[15]  Itsushi Uno,et al.  Numerical modeling of the nocturnal urban boundary layer , 1989 .

[16]  Bert Blocken,et al.  Coupled urban wind flow and indoor natural ventilation modelling on a high-resolution grid: A case study for the Amsterdam ArenA stadium , 2010, Environ. Model. Softw..

[17]  Roger A. Pielke,et al.  Large eddy simulation of microburst winds flowing around a building , 1993 .

[18]  Jong-Jin Baik,et al.  A Numerical Study of Thermal Effects on Flow and Pollutant Dispersion in Urban Street Canyons , 1999 .

[19]  C. W. Hirt,et al.  Calculating three-dimensional flows around structures and over rough terrain☆ , 1972 .

[20]  I. Orlanski A rational subdivision of scales for atmospheric processes , 1975 .

[21]  Zhen Huang,et al.  The impact of solar radiation and street layout on pollutant dispersion in street canyon , 2005 .