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This study describes and evaluates a Global Navigation Satellite System(GNSS) radio occultation (RO) retrieval scheme particularly aimed atdelivering bias-free atmospheric parameters for climate monitoring andresearch. The focus of the retrieval is on the sensible use of a prioriinformation for careful high-altitude initialisation in order to maximisethe usable altitude range. The RO retrieval scheme has been meanwhileapplied to more than five years of data (September 2001 to present) from theGerman CHAllenging Minisatellite Payload for geoscientific research (CHAMP)satellite. In this study it was validated against various correlativedatasets including the Michelson Interferometer for Passive AtmosphericSounding (MIPAS) and the Global Ozone Monitoring for Occultation of Stars(GOMOS) sensors on Envisat, five different atmospheric analyses, and theoperational CHAMP retrieval product from GeoForschungsZentrum (GFZ) Potsdam.In the global mean within 10 to 30 km altitude we find that the presentvalidation observationally constrains the potential RO temperature bias tobe <0.2 K. Latitudinally resolved analyses show biases to beobservationally constrained to <0.2–0.5 K up to 35 km in most cases, andup to 30 km in any case, even if severely biased (about 10 K or more) apriori information is used in the high altitude initialisation of theretrieval. No evidence is found for the 10–35 km altitude range of residualRO bias sources other than those potentially propagated downward frominitialisation, indicating that the widely quoted RO promise of"unbiasedness and long-term stability due to intrinsic self-calibration"can indeed be realised given care in the data processing to strictly limitstructural uncertainty. The results thus reinforce that adequatehigh-altitude initialisation is crucial for accurate stratospheric ROretrievals. The common method of initialising, at some altitude in the upperstratosphere, the hydrostatic integral with an upper boundary temperature orpressure value derived from meteorological analyses is prone to introducebiases from the upper boundary down to below 25 km. Also above 30 to 35 km,GNSS RO delivers a considerable amount of observed information up to around40 km, which is particularly interesting for numerical weather prediction(NWP) systems, where direct assimilation of non-initialised observed RObending angles (free of a priori) is thus the method of choice. The resultsunderline the value of RO for climate applications

Retrieval of temperature profiles from CHAMP for climate monitoring: intercomparison with Envisat MIPAS and GOMOS and different atmospheric analyses