Real-time remote detection of convectively-induced turbulence

Although the connection between Doppler spectrum width and turbulence intensity has long been recognized, the spectrum width's sensitivity to low signal-to-noise ratios, overlaid echoes, and contamination by non-atmospheric scatterers has limited the utility of Doppler weather radars for automated turbulence detection. Under direction and funding from the FAA's Aviation Weather Research Program, these issues have been addressed through the development of the NCAR Turbulence Detection Algorithm (NTDA), a fuzzy-logic algorithm that uses radar reflectivity, radial velocity, and spectrum width to perform data quality control and compute reliable eddy dissipation rate (EDR) estimates and associated confidences. A real-time demonstration of the NTDA using Level II data from 16 NEXRADs in the upper Midwest is currently underway, producing a 3-D mosaic of turbulence intensity at five-minute intervals. This demonstration is the first step of a planned implementation that will offer turbulence detection over the entire CONUS, providing airline meteorologists, dispatchers, and air traffic controllers a new tool for identifying areas hazardous to aviation safety and helping to minimize the loss of capacity due to convective activity. Additionally, the NTDA data may be of use to forecasters, modelers, and those working to understand thunderstorm evolution. This paper presents an overview of the NTDA and its limitations, describes the operational demonstration, and discusses verification of the NTDA's performance based on comparisons with pilot reports and automated in-situ turbulence reports provided by United Airlines Boeing 757 aircraft.