###### Abstract  
In this study, the resilience of large cities and their built infrastructure in New Zealand to extreme winds, is investigated by coupling the outputs of a very high-resolution, 333-m resolution, numerical weather prediction (NWP) model with computational fluid dynamics (CFD) simulations. Following an extreme wind event on 18 September 2020 in Auckland, in which two trucks travelling over the Auckland Harbour bridge tipped over and damaged the bridge structure, a CFD simulation of airflow over the bridge using the Reynolds-averaged Navier-Stokes (RANS) method and NWP wind speed forecasts as the inlet profile is conducted. The 333 m NWP forecasts were validated against four nearby observation sites, showing generally high correlations of greater than 0.8 and low mean bias (\(\pm\)3 m s\({}^{-1}\)) and RMSE (\(<\)3 m s\({}^{-1}\)) values. The CFD-based estimates of the mean wind speed-up over the bridge showed that the mean wind speed could increase by a factor of 1.15-1.20 in the vicinity of the road where the toppled vehicles were travelling. Additionally, NWP forecasts and CFD estimates of wind gusts at the maximum bridge height, within the area not affected by the bridge structure, agreed well with a value of about 25 m s\({}^{-1}\). An anemometer mounted at the top of the bridge arch measured a higher gust wind speed of about 35 m s\({}^{-1}\) that could have been influenced by the gust speed-up resulting from the flow separation from the bridge arch, which is demonstrated in the CFD results. The results demonstrate the importance of understanding localised wind speed-up effects and distinguishing them from the approaching undisturbed airflow. numerical weather prediction (NWP); downscaling; computational fluid dynamics (CFD); wind hazards; RANS turbulence models; numerical simulation; atmospheric boundary layer 2021  
1  
<ccs2020>  
technique. The significant increase in numerical simulation capabilities over the last few decades has made it possible to develop high-resolution sub-km weather models and also integrate fine-scale models with coarser models to have realistic initial and boundary conditions [5]. Thus, coupling NWP and CFD models can provide an opportunity to investigate the strong winds over urban areas utilising real meteorological conditions, such as cyclones, thunderstorms, and fronts, as the initial and boundary conditions of the CFD simulations. The concept of coupling mesoscale NWP models to a CFD model has been studied previously, e.g., [6; 7; 8; 9], to investigate various climate and environment parameters in urban areas, such as wind speed and direction, and temperature. CFD simulations can be used to assess urban microclimate by resolving heat and mass transfer and their interaction with buildings and other urban obstacles. Several wind engineering and environmental studies, including wind hazard assessment [10; 11], pollutant dispersion and air quality [6; 12; 13], pedestrian-level wind speeds [14], and energy demand [3; 15], significantly benefit from high-resolution CFD simulations of urban areas. Unlike the mesoscale models, which are not capable of resolving urban heterogeneous structures, CFD microscale models have the advantage of accurately resolving the urban roughness sublayer, in which most human activities are located [9]. Reviews of the coupling approach and CFD analysis of urban microclimate are provided by [PERSON] et al. [5] and [PERSON] et al. [1], respectively. In NWP/CFD coupling approaches, both time-varying and non-time-varying boundary conditions provided by the NWP models could be used as inlet conditions to the CFD model. In the present study, non-time-varying boundary conditions are used. [PERSON] et al. [4] coupled a building resolving large eddy simulation (LES) with NWP models to study strong winds during passage of a major typhoon over the central district of Tokyo.