Sensitivity studies of high-precision methane column concentration inversion using a line-by-line radiative transfer model

Hyper-spectral remote sensing may provide an effective solution to retrieve the methane (CH₄) concentration in an atmospheric column. As a result of exploring the absorptive characteristics of CH₄, an appropriate band is selected from hyperspectral data for the detection of its column concentration with high precision. Following the most recent inversion theory and methods, the line-by-line radiative transfer model (LBLRTM) is employed to forward model the impact of four sensitive factors on inversion precision, including CH₄ initial profile, temperature, overlapping gases, and surface albedo. The results indicate that the four optimized factors could improve the inversion precision of atmospheric CH₄ column concentration.