The research presented herein is a mix of meteorological and wind engineering disciplines. In many cases, there is a gap between these two fields and this thesis is an attempt to bridge that gap through multiscale wind modelling approaches. Data and methods used in this study cover a multitude of spatial and temporal scales. Applications are in the fields of sustainability and resilience. This relationship between multiscale wind modelling and sustainability and resilience is investigated examining several case studies of three different developments: urban, rural and coastal.
An urban wind modelling methodology is proposed and applied for a specific development in downtown Toronto, Canada. Micro-scale wind energy maps are created using computational fluid dynamics, analytical models, and the Canadian Wind Energy Atlas. It is demonstrated that urban wind energy projects are currently not feasible/sustainable due to decoupling between urban wind turbine power curves and wind speed histograms. Wind climatology for Toronto is calculated using the reanalysis data for the period 1948-2015. A trend analysis reveals statistically significant positive trends of the most frequent wind directions. Low-frequency wind spectra shows three distinguished peaks. The lowest frequency peak has the period of 11 year and it is linked to solar activity. The first methodology for microscale modelling of urban winds in changing climate is developed. Maximum wind speeds are more affected by climate change than the means.
A wind sustainability study is performed for a unique development in South Central Kansas, United States. The analyses are conducted on the wind data obtained from the closest weather station and for the period 1984-2015. The WAsP package is used to calculate the wind atlas and wind resources at the site. Five locations suitable for installation of wind turbines are determined.
A downburst that struck Livorno, Italy, on October 1, 2012 is analyzed from the wind resilience perspective. The analyses are conducted by gathering all available and relevant meteorological data. This research allowed for better understanding of downbursts, created a reference broad-band of information for the future calibration of analytical, physical and numerical models, and highlighted the potential of merging wind engineering and meteorology