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Abstract

The Global Navigation Satellite System (GNSS) Radio Occultation (RO) technique is based on a satellite-to-satellite limb sounding concept using GNSS microwave signals to probe the Earth’s atmosphere. Fundamental atmospheric variables such as temperature and humidity can be retrieved with high accuracy in the troposphere and stratosphere. The changing thermal structure in this height domain is a sensitive indicator of climate change. The global coverage, all-weather capability, high accuracy, and self-calibrated nature of RO data suggests them as a promising tool for global short- and long-term monitoring of atmospheric temperature change. The German research satellite CHAMP (CHAllenging Minisatellite Payload for geoscientific research) with a GPS (Global Positioning System) occultation receiver aboard continuously records about 180 RO observations per day since March 2002. The mission is currently expected to last at least until 2007, thus CHAMP data provide the first opportunity to create real RO based climatologies on a longer term. CHAMPCLIM is a joint project of the IGAM/University of Graz and the GeoForschungsZentrum (GFZ) Potsdam. The overall aim of CHAMPCLIM is to help ensure that the CHAMP RO data are exploited in the best possible manner for climate monitoring. The main objectives of the CHAMPCLIM project can be summarized in form of three areas of study as follows: (1) RO data processing advancements for optimizing climate utility of the data, (2) RO data and algorithms validation comprising the comparison of CHAMP RO profiles against temperature profiles from the GOMOS and MIPAS instruments on ENVISAT as well as against temperature and refractivity profiles of ECMWF analysis fields. (3) Creating global RO based climatologies for monitoring climate change. The latter area exploits the achievements of parts (1) and (2). The complete CHAMP RO data flow (~180 events/day) will be used for month-to-month, season-to-season, and year-to-year climate variability and change monitoring. We will build, on the one hand, direct RO-based climatologies by monitoring of climatological refractivity, temperature, geopotential height, and humidity fields. On the other hand, we will perform optimal fusion of the CHAMP RO-derived refractivity data and ECMWF analysis fields into global climate analyses by use of 3D-variational assimilation techniques. We will show a summary of the current activities and exemplary results.