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Global Navigation Satellite System Radio Occultation (GNSS-RO) refractivity climatologies for the stratosphere can be obtained from  the Abel inversion of monthly average bending-angle profiles. The averaging of large numbers of  profiles suppresses random noise and this, in combination with simple exponential extrapolation  above an altitude of 80 km, circumvents the need for a "statistical optimization" step  in the processing.  Using data from the US–Taiwanese COSMIC mission, which provides ~1500–2000  occultations per day, it has been shown that this average-profile inversion (API)  technique provides a robust method for generating stratospheric refractivity climatologies.    Prior to the launch of COSMIC in mid-2006, the data records rely on data from the CHAMP (CHAllenging Mini-satellite Payload) mission. In order to exploit the full range of available RO data, the usage of CHAMP data is also  required. CHAMP only provided ~200 profiles per day, and the measurements were noisier than  COSMIC. As a consequence, the main research question in this study was to see if the average  bending-angle approach is also applicable to CHAMP data.    Different methods for the suppression of random noise – statistical and through data quality  prescreening – were tested.  The API retrievals were compared with the more conventional  approach of averaging individual refractivity profiles, produced with the implementation of  statistical optimization used in the EUMETSAT (European Organisation for theExploitation of Meteorological Satellites) Radio Occultation Meteorology Satellite Application  Facility (ROM SAF) operational processing.    In this study it is demonstrated that the API retrieval technique works well for CHAMP data,  enabling the generation of long-term stratospheric RO climate data records from August 2001 and  onward. The resulting CHAMP refractivity climatologies are found to be practically identical to  the standard retrieval at the DMI (Danish Meteorological Institute) below altitudes of 35 km. Between 35 and 50 km, the differences between the two retrieval methods started to increase, showing  largest differences at high latitudes and high altitudes. Furthermore, in the winter hemisphere  high-latitude region, the biases relative to ECMWF (European Centre for Medium-range Weather Forecasts) were generally smaller for the new approach  than for the standard retrieval

CHAMP climate data based on the inversion of monthly average bending angles