Background Field Algorithm Model of Atmospheric Temperature Based on Microwave Remote Sensing

With the increased demand for atmospheric parameters, microwave remote sensing technology began to emerge. Ground-based microwave radiometer is an important means of atmospheric observation on land. Ground-based microwave radiometer is capable of reflecting atmospheric parameters based on atmospheric bright temperature values. Due to the fact that ground-based microwave radiometer inversion accuracy can be affected by the atmospheric temperature background. It is necessary to establish a high density and high accuracy atmospheric temperature background field. This paper is based on the principles of atmospheric thermodynamics and atmospheric kinematics. Using the Fourier transform thought, a physical model-based background field generation method is proposed. The atmospheric temperature profile generated from the background field is compared with the real atmospheric temperature profile. The result was analyzed by means of root mean square error (RMSE). It shows that, compared with the fall and winter seasons, atmospheric temperature background fields are more realistic in spring and summer.