Channel selection method for the CH4 profile retrieval using the Atmospheric Sounder Spectrometer by Infrared Spectral Technology

Abstract

Methane (CH₄) is the second-largest greenhouse gas contributing to global warming, surpassed only by CO₂, has a large difference in its vertical concentration distribution, and closely affects the global environment and climate change. The variations in the vertical concentrations of CH₄ need to be monitored. Ground-based infrared hyperspectrometers can measure the fine variations of the CH₄ concentrations in the vertical distribution within the planetary boundary layer (PBL). However, different detection channels are easily affected by instrumental noise and other environmental factors, leading to differences in the channel spectral characteristics and thereby affecting the accuracy of the CH₄ profile retrieval. In this study, an information-weighted channel selection method is proposed for the CH₄ profile retrieval using the Atmospheric Sounder Spectrometer by Infrared Spectral Technology (ASSIST) to address the differences in the channel characteristics from the different interference factors. This method leverages the information content of CH₄ and its environmental interference factors in each channel to derive the weighting factors, and a comprehensive weighting approach is subsequently applied to ascertain the effective information content of CH₄. The method then establishes the threshold for the effective CH₄ information content, considering the influence of noise, to select the optimal channels. We employ this method in our study, and 22 channels are selected as the optimal channels for the CH₄ profile retrieval. We also evaluate the retrieval capability of the CH₄ profile and the anti-interference ability of the selected channels using simulated spectra under clear-sky conditions. When retrieving the CH₄ profile using the 1200–1390 cm⁻¹ band (394 channels in total), the CH₄ profile is mainly affected by temperature, water vapor, aerosol optical depth (AOD) and N₂O. In addition, the mean absolute error (MAE) and the root mean square error (RMSE) for the CH₄ profile retrieval using the selected channels are substantially reduced.