Diagnostic wind models (DWM) may present a feasible choice when full computational fluid dynamics (CFD) is not applicable due to unbearable numerical costs. For selected cases with DWM, it is possible to derive high resolution wind fields in a fraction of time needed to solve the Navier Stokes equations with a comparable quality. DWM solve an optimization problem under the constraint of mass conservation. The initial wind field is interpolated from measurements or a coarse-grid numerical weather prediction model application. Obstacles placed in the wind field are considered by a wake parameterization, which corrects the wind field for the momentum deficit by decreasing the wind speed or reversing the flow in the vicinity of obstacles (Roeckle, 1990, Nelson et al., 2008). The optimization problem is formulated in minimizing the deviation to the modified initial wind field. The solution is a vector potential of the desired wind field, which makes this approach inherently mass conserving. An important application of DWM is in urban air quality modeling, where street-canyon resolving wind fields are required for the realistic computation of emission dispersal.