A probabilistic global turbulence nowcast and forecast system

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Wednesday, 20 January 2010: 5:30 PM
B204 (GWCC)
John K. Williams, NCAR, Boulder, CO; and C. Kessinger, R. D. Sharman, W. F. Feltz, and A. Wimmers

This paper describes the development of a global turbulence nowcast and forecast system designed to provide authoritative information for NextGen and the World Area Forecast System. Modeled on the FAA's Graphical Turbulence Guidance (GTG) and GTG Nowcast systems, the new system aims to provide 3-D, probabilistic, 0-36 hour turbulence nowcasts and forecasts globally above 10,000 feet MSL, addressing clear-air turbulence, mountain wave turbulence, and convectively-induced turbulence (CIT). The diagnosis and prediction algorithms make use of NCEP Global Forecast System model-based turbulence diagnostics and geostationary satellite-based turbulence diagnosis algorithms, and a convective nowcast module supports assessment of the near-term likelihood of CIT. Algorithm development is guided by a data mining technique called "random forests", which makes use of a database of quantitative turbulence measurements from commercial aircraft collocated with model data and satellite observations to determine relevant features and build an empirical, probabilistic data fusion model. This paper presents an overview of the system elements, the initial algorithm development, early case-study results and plans for a real-time demonstration including a web-based display and cockpit uplinks to en-route aircraft.