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As compared to high-spectral thermal infrared data, ultra-spectral thermal infrared data contains enhanced atmospheric vertical information of ozone (O3) and methane (CH4), which implies the possibility to improve the accuracy of retrieved O3 and CH4 profiles. Due to the narrow channel intervals of the ultra-spectral thermal infrared data, abundant special information as well as redundant information is induced. However, both of the information cannot be detected by the channel selection methods for high-spectral thermal infrared data, which impeding the superiority of ultra-spectral data for the retrieval of trace gas profiles. As such, a novel channel-selection method based on the gas sensitivity and weighting function characteristics (OWSP) has been promoted, aiming to enhance the retrieval efficiency and accuracy of O3 and CH4 profiles from ultra-spectral thermal infrared data. The method consists of two steps. First, the sensitivities of the channels to different gases are analyzed and the signal to interference ratio (rSTI) are then obtained. Based on that, channels with abundant information for retrieved gas and insensitivity to other gases can be detected, which are taken as the initial channel group. Second, a strategy of optimizing the distribution of the weighting function is promoted based on the features of Jacobians to O3 and CH4, and the channel information content can be quantified by the optimized weighting function. An iterative approach is then applied to select optimal channel group for the retrieval of atmospheric profiles. In this paper, the promotion effect of OWSP method for O3 and CH4 profile retrieval from ultra-spectral thermal infrared data is evaluated by being applied in the winter and summer atmospheric situation of the regions of Alxa Desert (AL), Beijing Tianjin district (JJ), Yangtze River Basin (YRD) and Pearl River Basin (PRD). The Optimal Sensitivity Profile (OSP) method, which suggests good performance for high-spectral thermal infrared data in the literature, is used in the control group herein. By comparing to the channel selection results of OSP method, it shows the OWSP method can effectively screen the correlated channels with similar information for the strong infrared radiation gas, O3, and select some channels with special information but relatively low sensitivity for the weak infrared radiation gas, CH4, ensuring the accuracy and efficiency of the following retrieval process. The retrieval results of O3 and CH4 profiles with the channel group selected by the two methods further prove that the OWSP method can efficiently improve the accuracy of the retrieved profiles in most situations, and the raise of mean retrieval accuracy of the O3 and CH4 profiles is 9.30% and 4.90%, respectively. This research is of important theoretical and application value, which can provide some essential technological supports in the development and data application of ultra-spectral TIR sensor for our country in the future.