Combined Weather Monitoring and Prediction Systems Sample Clauses

Combined Weather Monitoring and Prediction Systems. Algorithms to deduce robust eddy dissipation rate estimates from various measurement sources and forecast models should be developed. • Added value from the measurement data can be extracted by the assembly of spatial ensembles. This approach could be enhanced by methods of 4D data analysis. • Because many applications rely on short-term weather prediction enhanced nowcasting methods employing more sophisticated physical and/or statistical methods should be developed. • Methods for blending of nowcasting and numerical weather prediction in time may bridge the temporal gap between the methods. Blending of nowcasting and numerical weather prediction in space may improve the prediction skill along the flight path. • Numerical weather prediction models should assimilate available local measurements in order to improve their forecast skill. It should be investigated which measurements are best suited to improve the prediction skill of the respective required parameters (wind, temperature, turbulence). • The accuracies achieved by the various measurements sensors (in-situ, remote, and airborne e.g. AMDAR/ACARS), by nowcasting methods, and by weather prediction models should be determined and compared. The respective accuracies (i) should guide the selection of the weather monitoring and prediction methods, (ii) are important inputs for probabilistic wake vortex prediction, and (iii) are critical for the feasibility and success of the different operational concepts. • Methods for the determination of weather data along the intended flight path of an aircraft are needed for airborne wake vortex prediction. These methods may employ meteorological measurements of the own aircraft and of neighbouring aircraft (provided by ADS-B) and/or may use uplinked ground based weather data. The fusion of weather data from different sources may improve the overall performance of the system.