Development of Diagnostics of Near-Cloud Aviation Turbulence based on Convective Gravity Wave Drag Parameterization

Near-cloud turbulence (NCT) occurs above deep convection under the clear-air weather conditions, due to breakdown of convective gravity waves (CGWs). Nevertheless, current operational forecasting systems of aviation turbulence do not include diagnostics related to NCT. In the present study, we develop NCT diagnostics utilizing the parameterization scheme of CGWs proposed by Chun and Baik that has been used in global weather forecasting and climate models. We propose eight NCT diagnostics based on (i) drag of CGWs (CGWD) and (ii) minimum Richardson number including the effect of CGWs (Rim_CGW). The diffusion coefficients, turbulent kinetic energy, and eddy dissipation rate (EDR) derived from the CGWD and Rim_CGW, respectively, lead to eight NCT diagnostics, together with CGWD and Rim_CGW as the diagnostics. The feasibility of the approach is examined using the numerical simulation result for a real case occurred over the area between eastern Missouri and southwestern Illinois on 9-10 March 2006. The numerical simulation is conducted using the Advanced Research Weather Research and Forecasting model with three domains with horizontal grid spacings of 30, 10, and 3.3 km, respectively. The regions of non-zero NCT diagnostics in each domain are well matched with those of the observed NCT outside shallow convection. The results demonstrate that the eight NCT diagnostics represent well the turbulence related to breaking of CGWs in clear air condition for the current case. The skill score of the eight NCT diagnostics are also examined from the global Korean aviation Turbulence Guidance (G-KTG) system that has been developed recently using operational global weather forecasting model of Korean Meteorological Administration, Global Data Assimilation and Prediction Systems (GDAPS) and global in-situ turbulence observations for six months from October 2015 to March 2016. The convective heating rates (CHR), which is required for calculation of NCT diagnostics but is not provided from GDAPS, are estimated from the convective precipitation rates (CPR) using Ricciardulli and Garcia’s formulation, along with a relationship between CPR and CHR that is obtained from the NCEP reanalysis data for 32 years (1979-2010). The performance of the individual NCT diagnostics against in-situ observation of aviation turbulence for the six months will be presented in the conference.