Retrieval of atmospheric temperature and moisture vertical profiles from satellite Advanced Infrared Sounder radiances with a new regularization parameter selecting method

Considering the characteristics of nonlinear problems, a new method based on the L-curve method and including the concept of entropy was designed to select the regularization parameter in the one-dimensional variational analysis-based sounding retrieval method. In the first iteration, this method uses an empirical regularization parameter derived by minimizing the entropy of variables. During subsequent iterations, it uses the L-curve method to select the regularization parameter in the vicinity of the regularization parameter selected in the last iteration. The new method was employed to select the regularization parameter in retrieving atmospheric temperature and moisture profiles from Atmospheric Infrared Sounder radiance measurements selected from the first day of each month in 2008. The results show that compared with the original L-curve method, the new method yields 5.5% and 2.5% improvements on temperature and relative humidity profiles, respectively. Compared with the discrepancy principle method, the improvements on temperature and relative humidity profiles are 1.6% and 2.0%, respectively.