[10-1] Invited

Novel observations for convective-scale weather prediction

Martin Weissmann (Hans-Ertel Centre for Weather Research, LMU Munich), Heiner Lange (Hans-Ertel Centre for Weather Research, LMU Munich), Leonhard Scheck (Hans-Ertel Centre for Weather Research, LMU Munich), Tobias Necker (Hans-Ertel Centre for Weather Research, LMU Munich)

Forecasting convective precipitation is a major focus of regional weather models. In this regard, modern km-scale forecast models that explicitly represent convection facilitated significant improvements. Data assimilation systems for such high-resolution models, however, are still comparably immature, both regarding data assimilation methodology and the use of high-resolution observations that are required to address the stochastic nature and short life-time of convective systems.

The first part of the talk provides an overview on novel, potential high-impact observations for convective scale weather prediction. Promising data sources include cloud- or precipitation-affected satellite, polarimetric radar, lidar and global navigation satellite systems total delay observations as well as high-resolution aircraft, solar and wind power production, weather cameras and mobile phone pressure sensors.

The second part presents two efforts for the use of potential high-impact observations in the experimental ensemble data assimilation system of Deutscher Wetterdienst (DWD): (i) The assimilation of high-resolution Mode-S aircraft observations and (ii) the assimilation of cloud-affected visible observations from geostationary satellites. We demonstrate the beneficial impact of both data sets, but the assimilation of cloud-affected observations is limited by systematic model deficiencies in representing clouds and hydrometeors.