Operational Doppler radar turbulence detection capability for the Taiwan AOAWS

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Tuesday, 6 January 2015: 11:45 AM
129A (Phoenix Convention Center - West and North Buildings)
John K. Williams, NCAR, Boulder, CO; and G. Meymaris, J. A. Craig, and J. Cowie

The Taiwan Advanced Operational Aviation Weather System (AOAWS) provides state-of-the-art aviation weather decision support information to the Taiwan Civil Aeronautics Administration (CAA) and airlines to help mitigate weather impacts on the safety, efficiency and capacity of aviation operations in Taiwan. The recently-completed Phase 3 of the AOAWS Technical Enhancements (AOAWS-TE) project, led by the National Center for Atmospheric Research (NCAR), added new capabilities to the AOAWS including the Current Icing Product, Airport Ceiling and Visibility Prediction Product, and NCAR Turbulence Detection Algorithm (NTDA).

The NTDA was originally developed under direction and funding from the U.S. FAA Aviation Weather Research Program as the NEXRAD Turbulence Detection Algorithm. NTDA uses Doppler radar reflectivity, radial velocity and spectrum width along with a fuzzy logic quality control and averaging procedure to compute estimates of in-cloud eddy dissipation rate (EDR). The NTDA was deployed in the NEXRAD Open Radar Products Generator Build 10 in 2007, and has run in an experimental mode at NCAR since 2008, producing 3-D mosaics of in-cloud turbulence over the CONUS, Hawaii, Alaska and Puerto Rico every 5 minutes.

Adapting the NTDA for operational use in the Taiwan AOAWS required modifications to accommodate Gematronik Doppler radar systems, which have significant differences from NEXRADs in their signal processing (e.g., spectrum width estimator, dual-PRF, quality control and clutter filtering) and data formats. To address these differences, NCAR implemented new data parsing and processing software, developed a method to estimate the radar constant and compute SNR, requested changes to the Taiwan radar operational modes to permit more accurate spectrum width estimation, created static clutter maps, and performed numerical simulations to inform optimal adaptation of the fuzzy logic quality control procedure. The result is a new, real-time operational product that enhances the AOAWS capability by portraying 3-D in-cloud turbulence intensity over Taiwan and neighboring oceanic airspace, updated every 5 minutes. This paper highlights the steps taken to adapt the NTDA for use in Taiwan, provides statistical validation via inter-radar comparisons, and shows several case studies illustrating the relevance of NTDA information to operational decision making.