Real time weather for autonomous driving based on seamless integration of Ultra Rapid Data Assimilation and Nowcasting
The increasing demand on high resolved weather products finds an ally in the growing availability of meteorological measurements coming from automobiles. This fact supports the development of real time weather forecast systems - an essential key in autonomous driving.
The project Fleet Weather Maps (Flotten Wetter Karte; FloWKar), a collaboration of the German Meteorological Service (DWD) and the German car manufacturer AUDI AG, explores how future environmental data from millions of vehicle sensors and weather stations on Germany's roads can be used to improve forecast, nowcasting and warnings for key customers.
A complete real time weather concept is established, focusing on the flow and processing of high resolved measurements and weather products and the development of corresponding forecasts. The fast data exchange is followed by quality control according to weather service standards and smart aggregation strategies, integrating all available data into a real time weather map. Aiming for fast weather forecasting, a data assimilation cycle with 5-min-update rate is necessary, so an ultra-rapid data assimilation (URDA) method is proposed. A real-world application employs the high resolved project observations in a 5-minute assimilation cycle of the regional operational weather model COSMO-D2, focusing on the model performance optimization near surface and its predictions along road sections in Germany,where the current observation network is not enough dense.
Dr. Zoi Paschalidi German Meteorological Service (DWD)