Airlines have made it possible for people to travel almost anywhere in the world for fairly affordable prices. It has also broken many barriers and allowed families to live in different countries and still keep in touch. In fact, air travel between countries is so cheap in some parts of the world that it is often the cheapest way to travel. For instance, one of the cheapest modes of transportation in Europe at the moment is air travel. In a country like Norway where the construction of railway and road network is a tedious job, it is perhaps the most convenient mode of transportation of people and goods. However, the convenience comes at the cost of comfort and safety because of the unfavourable flight conditions prevailing in the mountainous regions. The regions are characterized by recirculation, mountain waves, hydraulic transitions, rotors and vortices which are all hazardous flying conditions. For the flight operation to be pleasant it is important to predict these hazardous flying conditions. Such predictions are complicated by the existence of a wide variety of spatio-temporal scales involved in the atmospheric flow. Most atmospheric processes are limited to a certain time- and length-scale, which is reflected in their classification into global-, meso-, and microscale processes. The overlapping between the chosen scales of interest and the scales of any physical process determine whether the process may be neglected, parameterized (empirically or physically) or directly resolved in a model. It is obvious that all scales are interrelated. Kinetic energy is passed down from larger scales to smaller scales and is finally dissipated as heat. Unfortunately, it is not possible to satisfactorily resolve all the scales in a computationally tractable way using a single model. It is however possible to tackle this problem by coupling different models with each targeting different climatic scales. For example a global model with a grid size of 200km-300km may be coupled with a meso scale model having a grid resolution of 1km-20km, which itself may be coupled with a micro scale model with a resolution of 10-100m. We are involved in the development and deployment of a Multiscale Turbulence prediction model at Norwegian airports. Our research in the last six years has focused on four areas:
- Real-time turbulence alert system: Norwegian airports are characterized by complex terrain dominated by rotors, hydraulic jumps, mountain waves and strong wind shear. This has resulted in several incidents in the past. In order to predict the turbulence intensity in real time a RANS based code named SIMRA has been developed and coupled to the numerical weather prediction code HARMONIE. The system gives a real time forecast on the www.ippc.no website.
- Validation of the alert system: Flight Data and AMDAR data are being used to validate the model. New strategies are being employed for validation work. New presentation strategy is being developed offline and implemented in the alert system.
- Special Analysis: ICAO (International Civil Aviation Organization) recommends site specific analysis for airports close which terrain modifications or building constructions are proposed. Best practice guidelines and work flow for such studies have been developed which leads to reliable analysis.
- Wake vortices (WV) generated by an aircraft is a source of risk for the following aircraft. The probability of WV related accidents increases closer to ground due to shorter recovery time after a WV encounter. The WV may also rebound from the ground and linger on in the flight path corridor. Hence, solutions that can reduce the risk of WV encounters are needed to ensure increased flight safety. In this research we propose an interesting approach to model such wake vortices in real time using a hybrid Eulerian-Lagrangian approach. In the animation above we have demonstrated how wake vortices left behind by an aircraft at the Vaernes airport in Norway get transported and decayed (using a Lagrangian approach) under the influence of a background wind and turbulence field (computed using a Eulerian approach). We are currently concentrating on quantitative validations both in idealized situation as well as in a realistic set-up.