The mesosphere-lower thermosphere (MLT) region is an important space region in the earth's atmosphere. As a significant parameter of atmospheric thermodynamics in the MLT region, the temperature is of great academic significance and application value. Since it is not affected by weather and geographical conditions, satellite-borne temperature detection can perform all-weather and long-term observation on a global scale. Thus, it becomes an important detection method to obtain the three-dimensional distribution and spatio-temporal evolution in the mid-upper atmospheric temperature. Previous satellite payloads, such as the wind imaging interferometer (WINDII) and the high-resolution Doppler interferometer (HRDI) on the UARS satellite, and the sounding of the atmosphere using broadband emission radiometry (SABER) on the TIMED satellite, have made contributions to the distribution detection of the mid-upper atmospheric temperature field. However, the MLT region still suffers from problems including incomplete space coverage or low detection accuracy. In October 2019, the Michelson interferometer for global high-resolution thermospheric imaging (MIGHTI) on NASA's ionospheric connection (ICON) explorer measured the radiation intensity of the O₂-A band through five discrete wavelength channels and obtained three years of continuous observation data. Based on the onion peeling algorithm and the theory of the O₂-A band airglow spectrum, this paper retrieves the atmospheric temperature profile in the 92-140 km area via the O₂-A band airglow radiation intensity measured by MIGHTI. In addition, comparisons with the observation results of the SABER satellite, the simulation data of the NRLMSIS-00 atmospheric model, and the temperature product of MIGHTI obtained by the ICON team using an optimization algorithm are conducted systematically to verify the rationality of MIGHTI temperature retrieval.

The relative radiation intensity of each spectral line in O₂-A band airglow which follows the Boltzmann distribution is affected by temperature. MIGHTI samples the O₂-A band signal through five channels, and the strength of signals in the B and D channels increases with the rising temperature, whereas the strength of the signal in channel C is just the opposite. The ratio of signal channels with different temperature responses is independent of the emission rate, and also changes monotonously with the temperature. Therefore, the atmospheric temperature can be accurately retrieved by measuring the ratio of channel signal strengths. The relative radiance of O₂-A band on the line of sight obtained from the limb-viewing observation of MIGHTI is stripped by the onion peeling algorithm to obtain the relative intensity of the target layer. Then, according to the relative intensity of the target layer of channels B, C, and D, the atmospheric temperature profile information is retrieved through combining the functional relationship between the channel strength ratio calculated by the MIGHTI instrument parameters and the temperature.

To evaluate the rationality and reliability of the MIGHTI temperature retrieval results obtained by the onion peeling algorithm, this paper verifies the MIGHTI retrieval results by comparing the measured data of SABER and simulation data of atmospheric model NRLMSIS-00. The results show that MIGHTI temperature retrieval is in good agreement with SABER at 92-100 km, and the temperature distribution of MIGHTI is basically consistent with that of the empirical model in the altitude range below 130 km, which shows the overall retrieval reliability of MIGHTI on a global scale. According to the characteristics of annual mid-upper atmospheric temperature changes, the detected temperature ratio of MIGHTI and SABER to the model temperature is calculated in one day of four seasons respectively. In the altitude range of 92-100 km, the temperature ratio profiles of MIGHTI and SABER are similar and very close to 1, which proves that MIGHTI has a strong temperature retrieval rationality in this altitude range. It is also compared with the temperature profile obtained by the optimization algorithm adopted by the ICON team to further evaluate the rationality of the onion peeling algorithm for retrieving MIGHTI temperature. Within the height range that can be retrieved by the optimization algorithm, the difference between the temperature values retrieved by the two algorithms differs slightly within ±5%, which further verifies the rationality of the temperature retrieval by the onion peeling algorithm.

The O₂-A band airglow measured by MIGHTI is retrieved and the atmospheric temperature distribution in this region is calculated by the onion peeling algorithm. By comparing the observation results of the SABER satellite, the NRLMSIS-00 atmospheric model data, and the MIGHTI temperature products obtained by the ICON team using the optimization method, the paper verifies the reliability and rationality of MIGHTI temperature retrieval. By measuring the shape of the O₂-A band airglow radiation spectrum, MIGHTI can detect the atmospheric temperature profile between 92-140 km, which covers the MLT area effectively. The minimum temperature error is 1 K at 90 km, and the maximum temperature retrieval error is 13 K at 140 km.