Temperature and Humidity Profiles Retrieval in a Plain Area from Fengyun-3D/HIRAS Sensor Using a 1D-VAR Assimilation Scheme

Abstract

In this study, a one-dimensional variational (1D-VAR) retrieval system is proposed to simultaneously retrieve temperature and humidity atmospheric profiles under clear-sky conditions. Our technique requires observations from the Fengyun-3D Hyperspectral Infrared Radiation Atmospheric Sounding (HIRAS) satellite combined with the Weather Research and Forecast (WRF) model. In the method, the radiative transfer for the TIROS Operational Vertical Sounder (TOVS (RTTOV) model is also used as a forward observation operator. The accuracy of our approach was evaluated using as a case study the region of Beijing in China. Predicted temperature and humidity profiles were compared against ERA-Interim data, which was used as reference. Mean bias (MB) of the temperature profiles varied between −0.8 K to 0.9 K, while the root-mean-square error (RMSE) ranged from 0.5 K to 2.6 K. In the boundary layer, the 1D-VAR algorithm performed better compared with the first guess. In the middle troposphere, the retrievals were more dependent on the first guess. With respect to relative humidity predictions, the accuracy of the evaluation of the whole troposphere was improved with the inclusion of the satellite observations, reporting an MB varying from −5.68% to 2.83%. Compared with Atmospheric Infrared Sounder’s (AIRS’) products, our predicted temperature profiles showed a very good consistency and the humidity predictions were also of an acceptable prediction accuracy. All in all, results clearly evidenced the promising potential of our proposed approach for retrieving temperature and humidity profiles under clear-sky conditions.