Information operator approach applied to the retrieval of the vertical distribution of atmospheric constituents from ground-based high-resolution FTIR measurements

The analysis of high spectral resolution Fourier Transform infrared (FTIR) solar absorption spectra is an important issue in remote sensing. If this is done carefully, one can obtain information, not only about the total column abundances, but also about the vertical distribution of various constituents in the atmosphere. This work introduces the application of the information operator approach for extracting vertical profile information from ground-based FTIR measurements. The algorithm is implemented and tested within the well-known retrieval code SFIT2, adapting the optimal estimation method such as to take into account only the significant contributions to the solution. In particular, we demonstrate the feasibility of the method in an application to ground-based FTIR spectra taken in the framework of the Network for the Detection of Atmospheric Composition Change (NDACC) at Ile de La Réunion (21 S, 55 E). A thorough comparison is made between the original optimal estimation method, Tikhonov regularization and this alternative retrieval algorithm, regarding information content, retrieval robustness and corresponding full error budget evaluation for the target species ozone (O3), nitrous oxide (N2O), methane (CH4), and carbon monoxide (CO). It is shown that the information operator approach performs well and in most cases yields both a better accuracy and stability than the optimal estimation method. Additionally, the information operator approach has the advantage of being less sensitive to the choice of a priori information than the optimal estimation method and Tikhonov regularization. On the other hand, in general the Tikhonov regularization results seem to be slightly better than the optimal estimation method and information operator approach results when it comes to error budgets and column stability.