Can reference radiosounding measurements be used to improve historical time series?

Upper-air radiosounding observations are undoubtedly a primary data source for the study of climate and for the atmospheric reanalysis. Nevertheless, historical radiosounding time series are affected by several systematic uncertainties due to change in the measurement sensors. As an alternative to the few existing approaches, in the frame of the Copernicus Climate Change Service (C3S), a novel approach, named RHARM (Radiosounding HARMonization), has been developed to provide a homogenized dataset of temperature, humidity and wind radiosounding profiles available from the Integrated Global Radiosonde Archive (IGRA) along with an estimation of the total uncertainty for each profile. Estimation of uncertainties has never been developed in previous homogenization algorithms. The homogenization is carried out for a substantial subset of IGRA radiosounding stations. Comparisons of trends calculated at 300 hPa over Europe in the period 2000-2018 using ERA5 ECWMF atmospheric reanalysis, IGRA and RHARM datasets show a good agreement for temperature with mutual differences within 0.05 K/da. For relative humidity, ERA5 shows a trend of -0.7%/da, while the trend for IGRA. and RHARM is of 0.5%/da and 0.8%/da, respectively. The usefulness of comparing, for the first time, ERA5 and RHARM time series taking advantage of the RHARM uncertainty is also discussed.