Iteratively Regularized Gauss-Newton Method for Atmospheric Remote Sensing Applied to MIPAS and SCIAMACHY Limb Sounding Observations

Abstract

In this paper we present a retrieval algorithm for atmospheric remote sensing. The algorithm combines the Tikhonov regularization and the iteratively Gauss--Newton method and is devoted to the solution of multi-parameter inverse problems with simple bounds on the variables. The basic features of the algorithm: the solution of the bound-constrained minimization problem, the selection of the optimal regularization parameter, the derivation of the global regularization matrix and the characterization of the solution (error analysis) are presented in detailed. Numerical simulations are performed for ozone retrieval from SCIAMACHY limb scatter measurements.