Quality assessment of FY-4 A’s geostationary interferometric infrared sounder observations data

The quality assessment of FY-4A Geostationary Interferometric Infrared Sounder (GIIRS) observation data can promote its application in numerical weather forecast. Using FY-4A Geostationary Interferometric Infrared Sounder (GIIRS) observation data in July 2020, this paper not only analyzes the dependence on FOV and latitude of noise for all channels of GIIRS, but also analyzes the distribution of bias (observation minus model) with time, FOV, latitude and zenith angle to evaluate the quality of GIIRS observation data. The results show that the noise of GIIRS exceeded the sensitivity index in the bands 727.5-733.8 cm⁻¹, 1107.5-1130 cm⁻¹, 1650-1776.9 cm⁻¹, and the biases and standard deviation of biases of these three bands are obviously larger than other channels. Except for the channels with large noise in long wave, the noise of each column is small in the middle and larger on both two sides when the noise of all bands is arranged in a 32×4 area array. Besides, the distribution of NEdT does not vary with latitude and FOR. So, when GIIRS data assimilation or variational inversion is carried out, the observation error can just consider the NEdT distribution of different channels in 32×4 array. The surface temperature of the numerical prediction model is underestimated in the daytime, which makes the underestimation of simulated radiation, reduces the absolute value of the bias, and makes the bias have obvious diurnal variation. The bias characteristics of middle-wave channels basically do not vary with the columns of 32×4 array, and are mainly related to the rows in the array. The bias correction can be carried out for the rows of 32×4 array, and the correction of latitude band and satellite zenith angle is basically not needed.