The RHARM (Radiosounding HARMonization) algorithm is the first to provide homogenized radiosonde-based records of temperature, relative humidity and wind profiles since 1978, alongside an estimation of the observational uncertainty for each observation and pressure level. The algorithm and the dataset are presented in the companion paper. In this paper we assess the performance of the dataset through comparison with some of the most widely used climate data records. The RHARM adjustments reduce the difference with the reanalysis especially in the northern hemisphere for temperature and relative humidity. The study of temperature trends at different pressure levels reveals a good agreement between RHARM, reanalysis and existing radiosounding homogenized datasets (<0.1K per decade above 300 hPa, 0.25 K per decade below). For relative humidity, the discrepancies among the datasets are more significant, although RHARM trends are most similar to the reanalysis. For wind speed, the comparison indicates a good agreement above 300 hPa. Compared to IGRA, RHARM also improves by 50% the agreement with the estimated trends in the lower stratosphere from MSU (Microwave Sounding Unit) deep layer averages. For water vapour, the good performance of post-2004 RHARM data is quantified from the comparison of the 300 hPa monthly means in tropics between RHARM and AURA/MLS, as the absolute mean difference is 0.01 g/kg for RHARM and 0.03 g/kg for IGRA, and correlation increases from 0.95 to 0.99. A validation of the observational uncertainties of RHARM is also presented showing that they provide a good estimate or overestimate the theoretical distribution.