This paper describes the design of the Advanced Diagnosis and Warning System for Aircraft Icing Environments (ADWICE) and presents results for two different icing weather situations with typical icing conditions. ADWICE has been in development since 1998 through the joint cooperation of the Institute for Atmospheric Physics at the German Aerospace Center (DLR), the German Weather Service (DWD), and the Institute for Meteorology and Climatology of the University of Hannover (IMUK). ADWICE uses information from different data sources in order to identify atmospheric environments that are potentially hazardous for aircraft icing. Forecast data from the operational Local Model (LM) of the DWD, with a horizontal grid spacing of 7 km covering the domain of central Europe, are combined with radar data and routine weather observations from the surface station network for this purpose. Algorithms developed at the National Center for Atmospheric Research (NCAR) that take into account different weather scenarios use the LM forecast fields of temperature, humidity, and pressure to provide first-guess icing information at LM grid points. This first-guess field is then subjected to a scenario correction in which a consistency check is performed through the combined use of the radar data and present weather reports. A final correction of the icing volume is achieved through surface observations of cloudiness and ceiling. For all diagnosed icing points the intensity of icing is derived from a formula that provides an adiabatic estimate of cloud liquid water from water vapor saturation mixing ratio at cloud base and forecast mixing ratios from the LM. Results are presented for a typical case of freezing rain and another one in which pilot reports (PIREPs) of icing are available for comparison. These PIREPS have been collected together with other relevant meteorological data during a testing phase from January to May 2001 in which ADWICE has been run in an operational environment at the DWD. Although ADWICE produces plausible icing fields, uncertainty remains with regard to providing an estimate of the icing intensity at a particular flight level. Taking cloud liquid water as forecast by the LM model directly as a measure of icing intensity instead of the estimate provided by the formula, however, produces poor results, as the comparison with PIREPs indicates.