The Retrieval of Temperature and Humidity Profiles for FY-3D/MWHTS in the Arctic Region

Microwave Humidity and Temperature Sounder (MWHTS) is one of the most important payloads on the Fengyun-3 (FY-3) satellite, and it can realize simultaneous detection of atmospheric temperature and humidity profiles. At present, the measurement data from MWHTS is not yet assimilated in the Arctic region. It is helpful to improve the initial field of the assimilation system by evaluating the accuracy of MWHTS atmospheric temperature and humidity profiles retrieval parameters in the Arctic region. In this paper, we propose a deep learning method for atmospheric temperature and humidity profiles retrieval to evaluate the accuracy of MWHTS atmospheric parameters. The results show that the RMSE of temperature profile is less than 2K, and the RMSE of humidity profile is between 10-20%. And the retrieval accuracy of LSTM is slightly better than that of DNN.