Biases and uncertainties in large-scale radiosonde temperature trends in the troposphere are critically reassessed. Realistic validation experiments are performed on an automatic radiosonde homogenization system by applying it to climate model data with four distinct sets of simulated breakpoint profiles. Knowledge of the “truth” permits a critical assessment of the ability of the system to recover the large-scale trends and a reinterpretation of the results when applied to the real observations. The homogenization system consistently reduces the bias in the daytime tropical, global, and Northern Hemisphere (NH) extratropical trends but underestimates the full magnitude of the bias. Southern Hemisphere (SH) extratropical and all nighttime trends were less well adjusted owing to the sparsity of stations. The ability to recover the trends is dependent on the underlying error structure, and the true trend does not necessarily lie within the range of estimates. The implications are that tropical tropospheric trends in the unadjusted daytime radiosonde observations, and in many current upper-air datasets, are biased cold, but the degree of this bias cannot be robustly quantified. Therefore, remaining biases in the radiosonde temperature record may account for the apparent tropical lapse rate discrepancy between radiosonde data and climate models. Furthermore, the authors find that the unadjusted global and NH extratropical tropospheric trends are biased cold in the daytime radiosonde observations. Finally, observing system experiments show that, if the Global Climate Observing System (GCOS) Upper Air Network (GUAN) were to make climate quality observations adhering to the GCOS monitoring principles, then one would be able to constrain the uncertainties in trends at a more comprehensive set of stations. This reaffirms the importance of running GUAN under the GCOS monitoring principles.