Inflight icing is a serious hazard, as attested by recent crashes of aircraft. The number of world-wide known accidents and serious incidents in which icing played a major role exceeds 800. Obviously current protection systems and icing forecasting, the latter relying mostly on reported icing by pilots and the evaluation of radiosonde ascents, are inadequate to control the threat.

Aircraft inflight icing occurs when areas of supercooled liquid cloud droplets or precipitation are traversed. Ice accumulation on aerodynamic surfaces causes modification of the aerodynamics of the aircraft up to the point of uncontrolled flight. The safest way and the recommended practise would be to avoid the icing conditions. This however requires the forecast of supercooled liquid water in clouds and complete ice microphysics model scheme. Only a few numerical weather prediction models however do include ice microphysics. The forecast quality of supercooled liquid water still is insufficient to completely rely on that quality for forecasting aircraft icing. Other methods to diagnose and forecast icing conditions are under development.

These methods rely on algorithms which deduce the potential icing threat from measured (mainly radiosonde ascents) or forecast (numerical models) distributions of temperature and humidity. However, although these algorithms have a high probability of detection of icing as verified against pilot reports (PIREPS), they generally show large overforecasting, i.e. a high false alarm rate.

This situation calls for the use of additional information to reduce the overforecast areas. Data fusion concepts have therefore been introduced with the aim to localize potential icing regions from a proper combination of numerical output data, satellite and radar data as well as surface observations.

Following this concept, ADWICE, the Advanced Diagnosis and Warning System for aircraft ICing Environments, has been developed since 1998 in a joint cooperation between the Institut für Physik der Atmosphäre at DLR, the Deutscher Wetterdienst (DWD) and the Institut für Meteorologie und Klimatologie (IMUK) at the University of Hannover. To identify icing environments, ADWICE merges forecast model data of the Local Model of the DWD with SYNOP and radar data. Using a slightly modified version of the NCAR/RAP algorithm, which is based on temperature and humidity fields, a first guess icing volume is calculated.

Under certain conditions radar and SYNOP data allow corrections of the icing volume. Other data e.g. from satellites may be used in future, too.

Since January 2001 ADWICE is running in a testing phase at the DWD. Using PIREPs of inflight icing the diagnosed icing volumes of ADWICE were validated. It is intended that after this testing phase ADWICE will be implemented for operational nowcasting of aircraft icing at the DWD. In this contribution the basic structure of ADWICE will be shown, first results and a short statistical overview of the European PIREPs will be presented.