Preparing AROME assimilation experiments for cloud-affected satellite observations

Despite the abundance of satellite observations, their assimilation in all-sky scenarios remains difficult, which hinders the use of high-resolution information in forecast models. In this work, we focus on the direct assimilation of satellite radiances (visible 0.6 μm, infrared IR 6.2 and 7.3 μm of the Seviri instrument) under all-sky conditions into the convection-permitting Numerical Weather Prediction (NWP) model AROME, which is in operation at Geosphere Austria, the Austrian weather service. Our research aims to exploit the potential of assimilating visible and IR channels under all-sky conditions making use of convection-permitting weather models that can explicitly resolve deep convection. In particular, we are looking at the use of the Radiative Transfer for TOVS (RTTOV), as an observational operator, to generate synthetic images for each channel. We endeavor to optimize the operator settings for running simulations within the convective-scale AROME model. Our first experiment focuses on testing IR synthetic images generated under all-sky conditions during a summer period (August) over Austria.