Paper Infomation
The improved calibration method and retrieval models using advanced ground-based multi-frequency microwave sounder
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Author: Jieying He, Shengwei Zhang
Abstract: The paper presents an improved ground-based atmospheric microwave sounder with multi-frequency channels. Compared to international used atmospheric microwave sounder, the merits of the instrument is described. To derive more accurate brightness temperature from microwave sounder observation, the paper presents 4 calibration processes in different process to perfect the calibration, including LN2 calibration, tipping curve calibration, nonlinear correction and quasi real time calibration. Since the close relationship between cloud and integrated water vapor and liquid water content, the paper describes several cloud-judgment models, and presents an improved cloud modal considering all the characteristics of all cloud models. Furthermore, the objective of this study is to test ANN (Artificial Neural Network) methodology for the problems of integrated water vapor and liquid water path derivation, using the improved ground-based atmospheric microwave sounder brightness temperatures and surface information such as temperature, humidity, pressure and so on. Compared to the commonly used method linear regression, this paper built a better retrieval model using ANN theory which can be high nonlinear and provide a tool to fit function to data. The present model gave an average RMS（Root Mean Square）error of integrated water vapor and liquid water content are less than 0.05cm and 0.5mm dependent on the actual atmospheric situation.
Keywords: calibration; Artificial Neural Network; integrated water vapor; liquid water path; Root Mean Square
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