Global climate monitoring based on CHAMP/GPS radio occultation data

The global coverage, all-weather capability, high accuracy, and self-calibrated nature of radio occultation (RO) data suggests them as a near-ideal resource to build global climatologies of fundamental atmospheric variables such as temperature and humidity. Such climatologies are not available yet, but some heritage exists from an on-going project on a climate observing system simulation experiment using realistically simulated RO data (GNSS-CLIMATCH, a joint project of IGAM/Univ. of Graz and MPI for Meteorology, Hamburg). The CHAMP (Challenging Minisatellite Payload) RO data will provide the very first opportunity to create real RO based climatologies. We aim at using the complete CHAMP RO data flow for month-to-month, season-to-season, and year-to-year global climate monitoring via temperature, geopotential height, and humidity fields. The RO based climatologies will be built in two modes: 1) fully independent based on statistical binning and averaging techniques applied to the dataset of original profiles, 2) weakly background-dependent but higher resolved based on optimal fusion (3DVAR assimilation) of RO data into averaged ECMWT atmospheric analysis background fields. Here we describe the set-up for the first approach and show preliminary results based on realistically simulated data. These suggest that reliable season-to-season temperature climatologies resolving scales > 1000 km can be obtained even with RO data received from a single satellite.