Investigating the impact of new active remote sensing instruments on Numerical Weather Prediction (NWP) models and developing observing strategies for these instruments for future field campaigns and operational applications

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The first assimilation of airborne Doppler lidar observations in a global weather forecast model recently demonstrated that such observations can significantly reduce analysis and forecast errors. However, the observational data base was limited to eight research flights. Similar impact studies using airborne water vapour lidar data led to forecast deterioration, but the data set was too small to fully explain reasons for the negative impact. In the near future, DLR is planning to deploy an airborne Doppler lidar together with a water vapour lidar during several field campaigns. This is expected to provide a unique data set to investigate the sensitivity of forecast models to initial conditions and to improve the understanding of physical processes causing high-impact weather. This project intends to develop and evaluate adaptive observing strategies for upcoming field campaigns using airborne lidars and will investigate the applicability of an operational adaptation of the observing system to sensitive areas. The collected observations will be assimilated in the ECMWF global model to investigate the value of targeted observations, the potential of air- and spaceborne lidars for the future observing system, and will investigate extra-tropical transition (ET) of tropical cyclones through dedicated sensitivity studies.