GRAS SAF project and products

The GRAS SAF is part of EUMETSATs network of Satellite Application Facilities (SAFs) under the EUMETSAT Polar System. The objectives of the GRAS SAF are to deliver operational radio occultation products from the GRAS occultation instruments (Global Navigation Satellite System Receiver for Atmospheric Sounding) onboard the three Metop satellites and to supply the Radio Occultation Processing Package (ROPP) containing modules for variational assimilation. The leading entity of the GRAS SAF is the Danish Meteorological Institute (DMI) and this is also the physical location of the operational GRAS SAF processing and archiving center. The other project partners are the European Center for Medium-range Weather Forecasts (ECMWF, UK), the IEEC (L’Institut d’Estudis Espacials de Catalunya, Barcelona, Spain), and the Met Office (Exeter, UK). The GRAS SAF started the operational phase in March 2007 and will start to deliver validated GRAS products in the second half of 2008. The GRAS data products consist of profiles of refractivity, temperature, and humidity (near-real time) and bending angle, refractivity, temperature, and humidity (offline and re-processing). We present results for refractivities retrieved from bending angles from EUMETSAT and compare them to ECMWF analyses. Because raw GPS radio occultation (RO) data are based on measurements of time and the assumptions are known, RO data are also well suited for climate monitoring and climate research. The self-calibrating property should allow for relatively straight forward inter-comparison of data from different satellites and RO instruments which is required to construct long time series covering many years and even decades. Our GRAS SAF offline profiles will regularly be processed into global and regional climate data in support of these activities. We are currently undertaking studies on how to best exploit the GRAS data, both for construction of an accurate single-source climate data base with known error characteristics of the data and for provision of global climate monitoring. We discuss how to derive climate data from the RO profiles, and how to estimate the error characteristics, random observational and sampling errors, and systematic biases of such climate data.