An Application of Time Series Analysis in Judging the Working State of Ground-Based Microwave Radiometers and Data Calibration

Time series analysis on clear-sky brightness temperature (TB) data observed in the morning with ground-based microwave radiometer for atmospheric remote sensing is adapted to judge the working state of the radiometer system according to meteorological data variation features in terms of radiative transfer. The TB data taken as the first example in this study was for the ground-based microwave radiometer at Nanjing during the period from Nov. 27, 2010 to May 29, 2011. The radiometer has 12 channels including five channels at 22.235, 23.035, 23.835, 26.235, and 30 GHz for sensing air humidity and liquid water content and seven channels at 51.25, 52.28, 53.85, 54.94, 56.66, 57.29, and 58.80 GHz for sensing air temperature profiles. The correlation coefficients between the TB readouts from the radiometer and the simulated TB with radiosonde temperature and humidity profiles as input to radiative transfer calculation are greater than 0.9 for the first five channels while the correlation coefficients for the last seven channels are quite poor, especially for the channels at lower frequency such as 51.25, 52.28, and 53.38 GHz, at which the TB readout values in time series do not show the right atmospheric temperature variation features as time goes from November (winter) through spring to early summer (late May). The results show that the first five channels worked well in the period while the last seven channels didn’t, implying that the radiometer need to be maintained or repaired by manufacture. The methodology suggested by this paper has been applied to the similar radiometers at Wuhan and Beijing for quality control and calibration on observed TB data.