One-Dimensional Variational Retrieval of Temperature and Humidity Profiles from the FY4A GIIRS  

作　　者：Qiumeng XUE Li GUAN Xiaoning SHI 

机构地区：[1]Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,Nanjing University of Information Science and Technology,Nanjing 210044,China [2]Department of Mathematics,University of Wisconsin-Madison,Madison 53706,USA

出　　处：《Advances in Atmospheric Sciences》2022年第3期471-486,共16页大气科学进展（英文版）

基　　金：supported in part by the National Key Research and Development Program of China under Grant No.2018YFC1507302;in part by the National Natural Science Foundation of China under Grant No.41975028。

摘　　要：A physical retrieval approach based on the one-dimensional variational(1 D-Var) algorithm is applied in this paper to simultaneously retrieve atmospheric temperature and humidity profiles under both clear-sky and partly cloudy conditions from FY-4 A GIIRS(geostationary interferometric infrared sounder) observations. Radiosonde observations from upper-air stations in China and level-2 operational products from the Chinese National Satellite Meteorological Center(NSMC)during the periods from December 2019 to January 2020(winter) and from July 2020 to August 2020(summer) are used to validate the accuracies of the retrieved temperature and humidity profiles. Comparing the 1 D-Var-retrieved profiles to radiosonde data, the accuracy of the temperature retrievals at each vertical level of the troposphere is characterized by a root mean square error(RMSE) within 2 K, except for at the bottom level of the atmosphere under clear conditions. The RMSE increases slightly for the higher atmospheric layers, owing to the lack of temperature sounding channels there.Under partly cloudy conditions, the temperature at each vertical level can be obtained, while the level-2 operational products obtain values only at altitudes above the cloud top. In addition, the accuracy of the retrieved temperature profiles is greatly improved compared with the accuracies of the operational products. For the humidity retrievals, the mean RMSEs in the troposphere in winter and summer are both within 2 g kg^(–1). Moreover, the retrievals performed better compared with the ERA5 reanalysis data between 800 h Pa and 300 h Pa both in summer and winter in terms of RMSE.

关 键 词：temperature and humidity profiles one-dimensional variational(1D-Var) GIIRS hyperspectral data 

分 类 号：P407[天文地球—大气科学及气象学]