Session 8.2 Diagnosing and forecasting inflight icing environments using ADWICE

Wednesday, 6 October 2004: 1:45 PM
Christoph Leifeld, German Weather Service, Business Unit Aviation, Offenbach, Germany

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In the atmosphere supercooled liquid water (SLW) exists as droplets in clouds and precipitation at subfreezing temperatures down to -40°C. If supercooled droplets get in contact with aircraft, they freeze and the resulting ice accretion may lead to a significant modification of aircraft aerodynamics up to the point of uncontrolled flight. Supercooled large droplets (SLD) with radii greater than 30μm are extremely hazardous in that respect. The safest way and the recommended practise would be to avoid the icing conditions. This however requires the forecast of supercooled liquid water (SLW) in cloud, cloud drop-size distribution, and complete ice microphysics model scheme. Since the forecast quality of SLW as numerical model data still is insufficient to completely rely on that quality for forecasting aircraft icing, other methods are in use and still under development. They rely on algorithms which deduce the potential icing threat from measured (mainly radiosonde ascents) or forecast (numerical models) distributions of temperature and humidity. In addition to these data sources new developed methods use other model data and apply weather observations (weather type, clouds). To improve icing forecasts at the German Weather Service (DWD, Deutscher Wetterdienst), ADWICE, the Advanced Diagnosis and Warning System for aircraft ICing Environments, has been developed in joint cooperation of the DLR (Deutsches Zentrum für Luft- und Raumfahrt), the DWD and the Institut für Meteorologie und Klimatologie (IMUK) at the University of Hannover. ADWICE provides a forecast and a diagnosis of inflight-icing hazards by the newly developed algorithms using model data of the Lokal-Modell (LM) of the DWD, weather observations and radar data. The developed algorithms potentiate to classify the weather and cloud situation into four different icing scenarios, which make it possible to deduce a drop-size distribution including SLD-potential in order to determine icing severity. Going this way, ADWICE is able to identify and forecast environments with SLD potential (freezing rain, freezing drizzle and towering cumulus). ADWICE processes all available data from the radar and weather observation network using a methodology, which so far has not been used in such a complex way. To improve air traffic safety the DWD implemented the inflight icing system ADWICE for operational use. In this contribution the basic structure of ADWICE will be shown and some results will be presented.

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