Observational records are more often than not influenced by residual non‐climatic factors which must be detected and adjusted for prior to their usage. Moreover, measurement uncertainties should be properly quantified and validated. In this work we present a novel approach, named RHARM (Radiosounding HARMonization), to provide a homogenized dataset of temperature, humidity and wind profiles along with an estimation of the measurement uncertainties for 700 radiosounding stations globally. The RHARM method has been used to adjust twice daily (0000 and 1200 UTC) radiosonde data holdings at 16 pressure levels from 1000 to 10 hPa from 1978 to the present from the Integrated Global Radiosonde Archive (IGRA). Relative humidity (RH) data are limited to 250 hPa. The applied adjustments are interpolated to all reported significant levels. RHARM is the first dataset to provide homogenized time series of temperature, relative humidity and wind profiles alongside an estimation of the observational uncertainty for each observation at each pressure level.

The comparison of RHARM and unadjusted profiles highlights a median temperature warmer by 0.6 K in the boreal hemisphere, while in the tropics RHARM is cooler by 0.1 K. For RH, the difference is -2.1%, while in the tropics it is reduced to 0.3%. For wind speed, adjustments largely improve the data homogeneity locally. Analysis of decadal trends for temperature, RH and winds highlights increased the geographical coherency of trends.

In a companion paper, the performances of the RHARM dataset are assessed through comparison with the reanalysis, satellite and other homogenized radiosonde datasets.