A comparative study of libRadtran and RTTOV predicted satellite images using the WRF forecasting output

ABSTRACTThe assimilation of cloudy radiances remains important in improving precipitation and severe weather forecasting. In practice, Numerical Weather Prediction (NWP) Models frequently do not predict meso-scale phenomena, so the phenomenon is either predicted but not realised, or is well predicted but not where it is observed. Radiative Transfer Models such as TIROS-Television and Infrared Observation Satellite Operational Vertical Sounder (RTTOV) and libRadtran are the mathematical operators used in the simulation of satellite data. In the data assimilation process, an effective reproduction of the mesoscale convective phenomenon leads to high quality data analysis. Therefore, we are looking for an operator that reproduces the NWP model’s behaviour in a realistic way. Several cloud parameterisation schemes are available in RTTOV and libRadtran to simulate the satellite cloudy radiances. Each selected scheme may result in different simulated brightness temperature data compared to those observed by sat...