Improving high-impact numerical weather prediction with drone observations
Meteomatics have co-created a scientific publication with MeteoSwiss demonstrating how Meteomatics weather drones improve the forecasting of high impact weather, by filling the gap in the current operational observing system.
The current operational observing systems are lacking data in the planetary boundary layer. Novel ground based lidar and drone observations can fill this gap and improve high-impact numerical weather forecasts.
The current atmospheric observing systems fail to provide a satisfactory amount of spatially and temporally-resolved observations of temperature and humidity in the planetary boundary layer (PBL) despite their potential positive impact on numerical weather prediction (NWP). This is particularly critical for humidity, which exhibits a very high variability in space and time or for the vertical distribution of temperature, determining the atmosphere’s stability.
Novel ground-based lidar remote sensing technologies and in-situ measurements from unmanned aerial vehicles can fill this observational gap, but operational maturity was so far lacking. Meteodrones can provide high quality in-situ observations of various meteorological variables with high temporal and vertical resolution.
The paper concludes that both lidar and drone observation systems have shown to considerably improve analyses and forecasts of high-impact weather, such as thunderstorms and fog in an operational, convective-scale NWP framework. The results of this study demonstrate the necessity for and the value of additional, high-frequency PBL observations for NWP and how lidar and drone observations can fill the gap in the current operational observing system.
Access the report - here