The atmospheric flow in the coastal zone is investigated using lidar and mast measurements and model simulations. Novel dual-Doppler scanning lidars were used to investigate the flow over a 7km transect across the coast, and vertically profiling lidars were used to study the vertical wind profile at offshore and onshore positions. The Weather, Research and Forecasting model is set up in 12 different configurations using 2 planetary boundary layer schemes, 3 horizontal grid spacings and varied sources of land use, and initial and lower boundary conditions. All model simulations describe the observed mean wind profile well at different onshore and offshore locations from the surface up to 500m. The simulated mean horizontal wind speed gradient across the shoreline is close to that observed, although all simulations show wind speeds that are slightly higher than those observed. Inland at the lowest observed height, the model has the largest deviations compared to the observations. Taylor diagrams show that using ERA-Interim data as boundary conditions improves the model skill scores. Simulations with 0.5 and 1km horizontal grid spacing show poorer model performance compared to those with a 2km spacing, partially because smaller resolved wave lengths degrade standard error metrics. Modeled and observed velocity spectra were compared and showed that simulations with the finest horizontal grid spacing resolved more high-frequency atmospheric motion. Plain Language Summary There is strong interest in accurate estimation of the wind resource for wind farms that are located in the coastal zone. These areas have high wind speeds for onshore flow conditions and grid connectivity is relatively easy. The atmospheric flow in the coastal zone is investigated using weather model simulations and a relatively new device (a scanning wind lidar) that can measure the wind speed using a laser beam. The weather model is set up in 12 different configurations, with varying parametrization schemes and boundary conditions. All model simulations describe the observed mean wind profile well at different onshore and offshore locations. The simulated mean horizontal wind speed gradient across the shoreline is close to that observed, although all simulations show wind speeds that are slightly higher than those observed. Inland at the lowest observed height, the model has the largest deviations compared to the observations. Simulations with the finest horizontal grid show poorer model performance, whereas using boundary conditions from the European Centre gives a better model performance. Although having a negative impact on standard performance metrics, simulations with the finest horizontal grid spacing resolved more atmospheric motion.
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Hong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
Xie, Bo
Fung, Jimmy C. H.
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Hong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
Hong Kong Univ Sci & Technol, Dept Math, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
Fung, Jimmy C. H.
Chan, Allen
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Hong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
Chan, Allen
Lau, Alexis
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Hong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
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Nanjing Univ, MOE, Key Lab Mesoscale Severe Weather, Nanjing 210008, Jiangsu, Peoples R China
Nanjing Univ, Sch Atmospher Sci, Nanjing 210008, Jiangsu, Peoples R China
Univ Calif Berkeley, Lawrence Berkeley Natl Lab, Div Earth Sci, Berkeley, CA 94720 USANanjing Univ, MOE, Key Lab Mesoscale Severe Weather, Nanjing 210008, Jiangsu, Peoples R China
Zhou, Bowen
Simon, Jason S.
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Univ Calif Berkeley, Dept Civil & Environm Engn, Berkeley, CA 94720 USANanjing Univ, MOE, Key Lab Mesoscale Severe Weather, Nanjing 210008, Jiangsu, Peoples R China
Simon, Jason S.
Chow, Fotini K.
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Univ Calif Berkeley, Dept Civil & Environm Engn, Berkeley, CA 94720 USANanjing Univ, MOE, Key Lab Mesoscale Severe Weather, Nanjing 210008, Jiangsu, Peoples R China
机构:
Hong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
Xie, Bo
Fung, Jimmy C. H.
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Hong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
Hong Kong Univ Sci & Technol, Dept Math, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
Fung, Jimmy C. H.
Chan, Allen
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Hong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
Chan, Allen
Lau, Alexis
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Hong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Div Environm, Hong Kong, Hong Kong, Peoples R China
机构:
Nanjing Univ, MOE, Key Lab Mesoscale Severe Weather, Nanjing 210008, Jiangsu, Peoples R China
Nanjing Univ, Sch Atmospher Sci, Nanjing 210008, Jiangsu, Peoples R China
Univ Calif Berkeley, Lawrence Berkeley Natl Lab, Div Earth Sci, Berkeley, CA 94720 USANanjing Univ, MOE, Key Lab Mesoscale Severe Weather, Nanjing 210008, Jiangsu, Peoples R China
Zhou, Bowen
Simon, Jason S.
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h-index: 0
机构:
Univ Calif Berkeley, Dept Civil & Environm Engn, Berkeley, CA 94720 USANanjing Univ, MOE, Key Lab Mesoscale Severe Weather, Nanjing 210008, Jiangsu, Peoples R China
Simon, Jason S.
Chow, Fotini K.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Calif Berkeley, Dept Civil & Environm Engn, Berkeley, CA 94720 USANanjing Univ, MOE, Key Lab Mesoscale Severe Weather, Nanjing 210008, Jiangsu, Peoples R China