Comprehensive Quality Control On TB Data Observed With A Ground-based Microwave Radiometer And The Efficiency Analysis

The ground-based microwave radiometer is an emerging meteorological observation instrument, it has a broad prospect in meteorological field. Ground-based microwave radiometer is used for atmospheric remote sensing, it can receive the microwave signal (expressed in brightness temperature) which launch by the atmosphere continuously, and can obtain the atmospheric temperature and humidity profile and the cloud-precipitation information by brightness temperature observations retrieving, or can assimilate with the numerical model. The position of the ground-based microwave radiometer is more and more obvious in atmospheric remote sensing, but the brightness temperature of different channels maybe become unusual because of outside influences such as electromagnetic interference, power unit or communications. The temperature measurement channels often affect the result of the subsequent temperature retrieval because of the cloud, and some channels are sensitive to environmental changes. So the quality control of the brightness temperature observation data by the ground-based microwave radiometer is very important before using. Aimed at the quality control on the brightness temperature observations (i.e. the Level1data)with a TP/WVP-3000type ground-based microwave radiometer in Beijing, a comprehensive quality control procedure including extremum check, time consistency check, which is routine quality control methods, radiative transfer calculation check and multichannel brightness temperature cross check, which is key method, is suggested. And comprehensive identifier QF and F is gave out. This paper analyzed603times clear sky sample and1415times full sample of two years between January in2010to December in2011, and the quality control efficiency is analyzed. The experiment verified the feasibility of the quality control procedure so that the procedure can be referenced by similar need, and the identifier QF and F can be discriminative and sensitive for the brightness temperature data in question, and the result can be used in the subsequent applications of the Level-1database during data choice.