At short wavelengths, especially C-, X-, and K-band, weather radar signals are attenuated by the precipitation along their paths. This constitutes a major source of error for radar rainfall estimation, in particular for intense precipitation. A recently developed stochastic simulator of range profiles of raindrop size distributions (DSD) provides a controlled experiment framework to investigate the accuracy and robustness of attenuation correction algorithms. The work presented here focuses on the quantification of the influence of uncertainties concerning radar calibration, the parameterization of power law relations between the integral variables (radar reflectivity Z and specific attenuation k), and total path integrated attenuation (PIA) estimations. The analysis concerns single frequency, incoherent and non-polarimetric radar systems. Two attenuation correction algorithms are studied: a forward algorithm based on the analytical solution proposed by Hitschfeld and Bordan (1954) and a backward algorithm based on the solution proposed by Marzoug and Amayenc (1994). From DSD range profiles, the corresponding profiles of integral radar variables are derived. Using a Monte Carlo approach, the accuracy and robustness of the two algorithms are quantified for the different sources of error previously mentioned.