Monday, 8 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Better forecasting of aviation turbulence becomes more important to the aviation industry, as turbulence encounters can cause serious in-flight injuries and structural damage. In South Korea, the regional Korean aviation Turbulence Guidance (KTG) system was developed using the Regional Data Assimilation and Prediction System (RDAPS) data of Korea Meteorological Administration (KMA) and pilot reports (PIREPs), and KTG forecasts of aviation turbulence over East Asia have been provided by the KMA/Aviation Meteorological Office (AMO) since January 2011. In response to continued demands for global turbulence forecasts from Korean commercial airlines, we developed a Global-KTG (G-KTG) system that consists of indices for clear-air turbulence (CAT) and mountain-wave induced turbulence (MWT) in the lower- (surface–FL100), middle- (FL100–FL200), and upper- (FL200–FL500) levels following the technology by Sharman and Pearson (2017). This product uses the operational Global Data Assimilation and Prediction System (GDAPS) of KMA. In the G-KTG, individual diagnostics for CAT and MWT are converted to eddy dissipation rate (EDR), which is the 1/3 power of energy dissipation rate, by calibrating against observed turbulence from in-situ flight data and GDAPS output. The performance of G-KTG is evaluated against in-situ flight data of EDR, provided by the National Center for Atmospheric Research (NCAR), for 14 months (2015.10–2016.11) for two different resolutions (dx = 25 km and 17 km) of GDAPS. The skill score of G-KTG is represented by an area under curve (AUC), where the curve is drawn by pairs of probabilities of detection for turbulence and null events. For GDAPS with 25 km horizontal grid spacing, the AUCs of G-KTG are 0.786 (lower-level), 0.829 (middle-level), and 0.846 (upper-level) for the first six months (2015.10-2016.3). Additional performance tests of G-KTG with 17 km GDAPS is underway. More detailed statistical evaluation results of G-KTG using longer periods of data will be shown and possible ways to improve G-KTG will be discussed in the conference.
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