Numerical closed-loop experiments on retrieving atmospheric temperature and humidity profiles by high-resolution measurements of the outgoing thermal infrared (IR) radiation using a Russian Fourier spectrometer (IRFS-2) were performed. Three techniques were used: multiple linear regression (MLR), the iterative physical-mathematical approach (IPMA), and artificial neural networks (ANNs). The MLR technique gives significant root mean square (RMS) errors in the retrieval of the temperature profile, especially in the troposphere region; these errors may be as great as 2–3 K. The ANN and IPMA techniques are considerably more accurate, giving approximately equal RMS errors of 1.0–1.5 K at altitudes of 2–30 km. For all interpretation techniques, a growth of errors of retrieval of temperature in the lower troposphere is observed and is especially substantial (up to 3 K for the near-surface temperature) in thermal sensing over land. The systematic errors of temperature retrieval for the ANN technique are practically z