Study On The Atmospheric Temperature And Humidity Profiles Of Satellite Remote Sensing Based On One-dimensional Variational Algorithm

Atmospheric temperature and humidity profile are important atmospheric parameters,which are of great application value in numerical weather forecast and weather warning.Satellites equipped with hyperspectral infrared sensors have the advantages of wide coverage,continuous observation,and all-weather observation throughout the day.Therefore,using satellite data to perform inversion studies of atmospheric temperature and humidity profiles is of great significance in promoting the processing and application of satellite data.In order to obtain high-precision atmospheric temperature and moisture mixing profile data,this paper studies the variational inversion method of atmospheric temperature and moisture mixing profile based on the infrared hyperspectral data from Metop-A/IASI(Infrared Atmospheric Sounding Interferometer).Using the temperature and vapor detection channel data of IASI hyperspectral infrared sensor,combined with the CRTM(Community Radiation Transfer Model)model and the WRF(The Weather Research and Forecast)model forecasting technology,we use a one-dimensional variational method to study satellite data quality control,localization of background error covariance and calculation of observation error covariance,a variational inversion system for profiles of atmospheric temperature and vapor mixing ratio was constructed,and inversion experiments were conducted in Beijing,Qingdao,and Shenyang.The main research results and conclusions:(1)During the calculation of the observation error covariance,the modeling and testing of temperature and water vapor mixture ratio inversion were performed using the satellite observation data before and after the correction of deviation respectively,and the test results are compared.The comparison test of inversion results based on soundings shows that,using the WRF model forecast value as the background field,the errors and the root-mean-square-error of the temperature and water vapor mix ratio profile of the inversion test after deviation correction for both the modelling test and the checking test are improved compared to the results before the correction.(2)An experimental study for the channel selection of satellite instruments was conducted.Based on the Jacobi of the channel,the temperature and water vapor mixing test channels in the first part were improved,and the average error and root mean squared error of temperature and mixture radio profiles were reduced.(3)Using the current common NMC method in operation,the background error covariance is calculated,and the test results are compared with the background error covariance based on the statistical methods used in the first and second tests.It shows that the statistical methods used in this study are slightly better than the NMC method for small scale inversion experiments.The above test results all show that:Based on the one-dimensional variational method,Metop-A/IASI infrared hyperspectral data can be used for high-precision detection of atmospheric temperature and moisture mixing profile.