The tipping-curve calibration method has been an important calibration technique for ground-based microwave radiometers that measure atmospheric emission at low optical depth. The method calibrates a radiometer system using data taken by the radiometer at two or more viewing angles in the atmosphere. In this method, the relationship between atmospheric opacity and viewing angle is used as a constraint for deriving the system calibration response. Because this method couples the system with radiative transfer theory and atmospheric conditions, evaluations of its performance have been difficult. In this paper, first a data-simulation approach is taken to isolate and analyze those influential factors in the calibration process and effective techniques are developed to reduce calibration uncertainties. Then, these techniques are applied to experimental data. The influential factors include radiometer antenna beam width, radiometer pointing error, mean radiating temperature error, and horizontal inhomogeneity in the atmosphere, as well as some other factors of minor importance. It is demonstrated that calibration uncertainties from these error sources can be large and unacceptable. Fortunately, it was found that by using the techniques reported, the calibration uncertainties can be largely reduced or avoided. With the suggested corrections, the tipping calibration method can provide absolute accuracy of about or better than 0.5 K.