Developing a high-resolution wind map for a complex terrain with a coupled MM5/CALMET system

[1] This study investigates the wind energy potential in Hong Kong, a region with a complex terrain, by coupling the prognostic MM5 mesoscale model with the CALMET diagnostic model to produce high-resolution wind fields. Hourly wind fields were simulated for the entire year of 2004. The MM5 simulations were performed on a nested grid from 40.5 km down to 1.5 km horizontal resolution. The CALMET meteorological model was used in a domain that includes the entire Hong Kong region with a high horizontal resolution of 100 m. The MM5 model wind field (1.5 km horizontal resolution) output was input into the CALMET diagnostic meteorological model every hour along with an objective analysis procedure using all available observations. Verification was achieved through two steps. In the first step, the data from three meteorological surface stations that were not assimilated into the CALMET model were compared horizontally with the simulated wind fields. In the second step, the simulated wind fields were compared vertically with the vertical wind profile collected from two upper air sounding stations. The results of this study identified the locations of the highest wind energy potential in HK down to 100 m resolution.

[1]  Ying-Hwa Kuo,et al.  Regional Real-Time Numerical Weather Prediction: Current Status and Future Potential , 1998 .

[2]  Hongxing Yang,et al.  Wind power potential and characteristic analysis of the Pearl River Delta region, China , 2006 .

[3]  David R. Stauffer,et al.  A Multiscale Four-Dimensional Data Assimilation System Applied in the San Joaquin Valley during SARMAP. Part I: Modeling Design and Basic Performance Characteristics , 1995 .

[4]  Albert A. M. Holtslag,et al.  A Simple Scheme for Daytime Estimates of the Surface Fluxes from Routine Weather Data , 1983 .

[5]  N. Mortensen,et al.  The numerical wind atlas - the KAMM/WAsP method , 2001 .

[6]  B. Lamb,et al.  Modeling Ozone Formation and Transport in the Cascadia Region of the Pacific Northwest , 2000 .

[7]  David R. Stauffer,et al.  Multiscale four-dimensional data assimilation , 1994 .

[8]  T. Warner,et al.  Separate and Coupled Testing of Meteorological and Hydrological Forecast Models for the Susquehanna River Basin in Pennsylvania , 1991 .

[9]  J. Fung,et al.  Application of Refined Land-Use Categories for High Resolution Mesoscale Atmospheric Modelling , 2006 .

[10]  Brian K. Lamb,et al.  A Numerical Daily Air Quality Forecast System for The Pacific Northwest , 2004 .

[11]  C. Russell Philbrick,et al.  Evaluating the performance of a computationally efficient MM5/CALMET system for developing wind field inputs to air quality models , 2003 .

[12]  Jianping Huang,et al.  Integrated processes analysis and systematic meteorological classification of ozone episodes in Hong Kong , 2006 .

[13]  Mukund Patel,et al.  Wind and Solar Power Systems , 1999 .

[14]  D. Stauffer,et al.  Use of Four-Dimensional Data Assimilation in a Limited-Area Mesoscale Model. Part I: Experiments with Synoptic-Scale Data , 1990 .

[15]  Jason Ching,et al.  Simulation of Meteorological Fields Within and Above Urban and Rural Canopies with a Mesoscale Model , 2004 .

[16]  Alexis K.H. Lau,et al.  Numerical simulation and process analysis of typhoon-related ozone episodes in Hong Kong , 2005 .

[17]  Erik Lundtang Petersen,et al.  Extrapolation of mean wind statistics with special regard to wind energy applications , 1984 .

[18]  Alexis K.H. Lau,et al.  Observational and modeling analysis of a severe air pollution episode in western Hong Kong , 2005 .

[19]  David R. Stauffer,et al.  Use of Four-Dimensional Data Assimilation in a Limited-Area Mesoscale Model Part II: Effects of Data Assimilation within the Planetary Boundary Layer , 1991 .

[20]  J. Dudhia.  A Nonhydrostatic Version of the Penn State–NCAR Mesoscale Model: Validation Tests and Simulation of an Atlantic Cyclone and Cold Front , 1993 .

[21]  J. Hunt,et al.  Turbulent wind flow over a low hill , 1975 .

[22]  David G. Streets,et al.  Present and future emissions of air pollutants in China:: SO2, NOx, and CO , 2000 .

[23]  G. Grell,et al.  A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5) , 1994 .

[24]  W. R. Hargraves,et al.  Methods for Estimating Wind Speed Frequency Distributions. , 1978 .

[25]  Mark Z. Jacobson,et al.  An integrated air pollution modeling system for urban and regional scales: 1. Structure and performance , 1997 .

[26]  Mark Z. Jacobson,et al.  An integrated air pollution modeling system for urban and regional scales: 2. Simulations for SCAQS 1987 , 1997 .

[27]  D. Weisser,et al.  A wind energy analysis of Grenada: an estimation using the 'Weibull' density function , 2003 .