Using a qualitative physical analysis, A. Praskovsky and P. Neilley developed a simplified empirical model of the flow near mountainous terrain. They based the model on four assumptions about the structure of a velocity field: 1) the statistical characteristics of a velocity field in mountainous areas are mainly defined by the aeromechanical parameters of the ambient flow, 2) the influence of terrain on all statistical characteristics of the velocity field is uniquely defined by the ambient wind direction, 3) the statistical characteristics of a velocity field can be considered locally quasi-stationary, and 4) the statistical characteristics of the velocity field near mountains are independent of the air viscosity.
Based on this model, Praskovsky and Neilley determined from these assumptions that any statistical characteristic of the velocity field in the vicinity of the terrain, in particular the mean and standard deviation of the wind speed components and energy dissipation rate, are linearly proportional to the mean ambient wind speed. The proportionality factors are unknown and perhaps very complex, but are unique functions of the ambient wind direction.
This model provides a simple surrogate for an implicit theoretical model of complex flow near mountains. It can be used for designing real-time operational algorithms for turbulence diagnosis in specified locations on the basis of ground anemometer and/or wind profiler measurements, in particular along the arrival and departure flight paths.
The model was applied to develop a real-time, ground anemometer-based turbulence diagnosis algorithm as well as real-time quality control algorithms for the anemometer data at the new Hong Kong airport. These algorithms revealed surprisingly high skill in both turbulence diagnosis and quality control, and were deployed in the airport Windshear and Turbulence Warning System.
The model is currently being applied to design ground anemometer and wind profiler-based real-time time turbulence diagnosis algorithms for the Juneau and Anchorage airports in Alaska. Future work includes the generalization of this model to take into account the dependence of turbulence severity on atmospheric stability, intensity of gravity waves and other relevant parameters.