Research On Quality Control And Inversion Algorithm Of Ground-based Microwave Radiometer

Ground based microwave radiometer is a meteorological observation equipment based on atmospheric microwave remote sensing technology.It has many advantages,such as reliable calibration method,high resolution,easy to carry,continuous detection and unattended,simple operation and so on.It is gradually becoming an important instrument for remote sensing of atmospheric profiles and an important means to obtain atmospheric temperature and humidity profiles.It is of great significance for understanding the evolution of weather at various scales and making near-term weather forecast.The quality of microwave radiometer data affects the use of data in business and scientific research.The quality control of ground-based microwave radiometer data is particularly important.Therefore,improving the quality of microwave radiometer observation data and inversion accuracy is of great significance to the meteorological department.Based on the study of traditional meteorological quality control algorithms and inversion algorithms,this paper deeply explores the quality problems of the equipment data,puts forward the data quality problems under the condition of precipitation,and gives the corresponding quality control methods.Combined with the cloud radar data,this paper tries to improve the inversion accuracy of temperature and humidity profiles under the cloud.It also evaluated the detection performance of two domestic microwave radiometers in operation at the China Meteorological Administration's Atmospheric Detection Test Base.The main research contents include:Firstly,introduced the relevant data and algorithms of microwave radiometers.The main research objects are LV1 brightness temperature data and LV2 product data,sounding data,forward brightness temperature data,interpolation algorithms,regression models,and BP neural network.Secondly,the quality control algorithm of the microwave radiometer is studied based on the characteristics of observations and the traditional meteorological quality control methods.In particular,an in-depth study of the influence of the water film of the radome on the brightness temperature data under precipitation conditions is carried out.The quality control method for the precipitation inspection in this paper is proposed.The threshold value of the algorithm is determined and the effectiveness of the quality control method is verified by data quality evaluation.Thirdly,based on the problem of low accuracy of temperature and humidity profile inversion under cloud conditions,the inversion algorithm data fusion research is carried out.A set of BP neural network algorithm model for inversion of temperature and humidity profile by microwave radiometer combined with cloud radar is established.The effectiveness of data fusion of inversion algorithm is verified by data evaluation and analysis.Finally,the relevant meteorological data are analyzed and evaluated and the algorithm is applied to the relevant systems.The detection performance of two domestic microwave radiometers is evaluated from the brightness temperature data accuracy,temperature and humidity profile,water vapor density and integrated water vapor content.The quality control is carried out for the equipment with poor detection performance.The brightness temperature data quality control of the microwave radiometer for the Winter Olympic Games can meet the needs of meteorological support services for the Winter Olympic Games.The results of different devices verify the effectiveness of the algorithm and the feasibility of its application in practical business.The related algorithms of the microwave radiometer have been applied to the mega-city observation platform and the intelligent vertical profile integrated control system.