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In this study, we derived atmospheric profiles of temperature, moisture, and ozone, along with surface emissivity, skin temperature, and surface pressure, from infrared-sounder radiances under clear sky (cloudless) condition. Clouds were detected objectively using the Atmospheric Infrared Sounder under a relatively low spatial resolution and cloud-mask information from the Moderate Resolution Imaging Spectroradiometer under a high horizontal resolution; this detection was conducted using space matching. Newton’s nonlinear physical iterative solution technique is applied to the radiative transfer equation (RTE) to retrieve temperature profiles, relative humidity profiles, and surface variables simultaneously. This technique is carried out by using the results of an eigenvector regression retrieval as the background profile and using corresponding iterative forms for the weighting functions of temperature and water-vapor mixing ratio. The iterative forms are obtained by applying the variational principle to the RTE. We also compared the retrievals obtained with different types of observations. The results show that the retrieved atmospheric sounding profile has great superiority over other observations by accuracy and resolution. Retrieved profiles can be used to improve the initial conditions of numerical models and used in areas where conventional observations are sparse, such as plateaus, deserts, and seas.