1004 TAF Initialization at Météo-France: The IniTAF Project

Wednesday, 9 January 2019
Hall 4 (Phoenix Convention Center - West and North Buildings)
Thierry Kranitz, Météo-France, Noumea, New Caledonia; and P. Crispel, P. M. Jaunet, C. Delin, and A. Drouin

Handout (5.6 MB)

Within the framework of its statutory mission of air traffic meteorological support, Meteo-France provides products and services in compliance with ICAO and Single European Sky rules and regulations. Nowadays, the tasks and assignments of aviation forecasters are expected to shift from message production towards end user support. In this context, aviation forecasters should have more time to focus on forecasting the evolution of the most critical parameters in hazardous situations (i.e. horizontal visibility in case of fog forming, etc.), and helping the decision making process.

As a large part of weather information provided to airport end users lies in TAFs (Terminal Aerodrome Forecasts), the IniTAF (TAF Initialization) innovative project was launched. The objective is to provide first guesses of draft TAFs and thus improve the forecasters’ efficiency while maintaining high safety in airport operations.

Several inputs are required to draft TAFs from model data: wind (intensity and direction), cloud cover, visibility and weather, which can be provided by NWP models. Thus, the project is composed of two main phases. The first stage consists of working on NWP outputs which are required for the TAF initialization process. In particular, aeronautical ceiling and visibility, which are not yet included in Météo-France’s mesoscale model AROME-France, require further developments. The second phase is to develop an algorithm which is able to make a TAF from hourly sampled meteorological parameters. The technical complexity of drafting TAFs stems from mutual interactions between parameters. A holistic approach is required to segregate between steady and transient states making sense from a meteorological and aeronautical point of view. Thus, a new methodology for TAF generation based on states analysis is designed. Generated TAF are compared to forecasters’ ones in several meteorological situations

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