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

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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.