Work

Insights into Tikhonov regularization: application to trace gas column retrieval and the efficient calculation of total column averaging kernels

Year: 2014
Type: article
Abstract: . A concept is proposed to retrieve the vertical column densities of atmospheric trace gases from remote sensing measurements. It combines the numerical simplicity of a least-squares profile scaling retrieval with the numerically robust calculation of the total column averaging kernel using an analytic expression. The approach enables calculation of the total column averaging kernel on arbitrary vertical grids. Formally, the proposed method is equivalent to Tikhonov regularization of the first kind with an infinite regularization strength. Due to its efficiency it is particularly suited for implementation in operational data processing with high demands on processing time. To demonstrate the method, we apply it to CO column retrieval from simulated measurements in the 2.3 μm spectral region and to O3 column retrieval from the UV, which represents ideal measurements of a series of space-borne spectrometers like SCIAMACHY, TROPOMI, GOME, and GOME-2. For both spectral ranges, we consider clear-sky and cloudy scenes where clouds are modelled as an elevated Lambertian surface. Here, the smoothing error for the clear-sky and cloudy atmosphere is significant and reaches several percent, depending on the reference profile which is used for scaling. This underlines the importance of the column averaging kernel for a proper interpretation of retrieved column densities. Furthermore, we show that the total column smoothing error is affected by a discretization error when total column averaging kernels are not represented on a fine enough vertical grid. For both retrievals this effect becomes negligible by using a vertical grid with 20–40 equally thick layers between 0 and 50 km.
Language: English
Open Access status: gold
Estimated APC paid: $1,585
OpenAlex ID: W2105099327
FWCI: 2.715
Cites: 46
Cited by: 80
Related to: 10