# A Probabilistic Forecast Algorithm of Nonconvective Turbulence over the Tibetan Plateau
## 3 Results  
### Thresholds of the Turbulence Indices  
Table 1 shows the threshold percentile of -Ri divided according to the above method. Table 2 shows the intensity thresholds of the other five turbulence indices, which are subdivided according to the threshold percentiles in Table 1. Figure 1 presents some turbulence indices with the threshold used in previous studies [16] (Figure 1a,b) and the redivided threshold (Figure 1c-e). The calculation of the CP index is related to the vertical grid spacing. The CP index divided by the empirical threshold shows that in the Qinghai Tibet Plateau region, the turbulence is moderate (Figure 1a). NCSU1 shows light turbulence across the whole region (Figure 1b). These results using empirical thresholds are unlikely to occur in reality. The division of the Richardson number turbulence intensity threshold is more reasonable, showing the contrast of turbulence intensity in the region (Figure 1e). Turbulence occurs in the southern Qinghai-Tibet Plateau, where there is moderate-severe turbulence in the southwest and moderate turbulence in the southeast. Figure 1c,d are the CP and NCSU1 redivided according to the threshold percentiles of -Ri. Their distribution is similar to that of Ri (Figure 1a). In Section 4, a turbulence probability index was generated by aggregating the 17 turbulence indices, and its effectiveness was confirmed through validation with turbulence events. This further supports the necessity and correctness of the threshold reclassification mentioned earlier in the section. Therefore, instead of individually  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Index Name** & **Units** & **T1** & **T2** & **T3** & **T4** & **T5** \\ \hline GRDT & K m\({}^{-1}\) & \(5.3\times 10^{-6}\) & \(1.1\times 10^{-5}\) & \(1.9\times 10^{-5}\) & \(3.2\times 10^{-5}\) & \(3.8\times 10^{-5}\) \\ CP & m\({}^{2}\) s\({}^{-2}\) & \(-24.6\) & \(-13.3\) & \(-5.3\) & \(-0.4\) & \(-14\) \\ MOSCAT & m\({}^{-8}\) s\({}^{-2}\) & \(1.0\times 10^{-3}\) & \(2.6\times 10^{-3}\) & \(4.1\times 10^{-3}\) & \(5.9\times 10^{-3}\) & \(6.8\times 10^{-3}\) \\ TI1 & s\({}^{-2}\) & \(5.3\times 10^{-8}\) & \(1.5\times 10^{-7}\) & \(3.0\times 10^{-7}\) & \(5.1\times 10^{-7}\) & \(6.2\times 10^{-7}\) \\ NCSU1 & s\({}^{-3}\) & \(5.1\times 10^{-16}\) & \(2.3\times 10^{-14}\) & \(2.0\times 10^{-13}\) & \(1.5\times 10^{-12}\) & \(2.3\times 10^{-8}\) \\ VENS & s\({}^{-2}\) & \(8.6\times 10^{-10}\) & \(3.4\times 10^{-9}\) & \(7.8\times 10^{-9}\) & \(1.6\times 10^{-8}\) & \(2.1\times 10^{-8}\) \\ CCAT & s\({}^{-2}\) & \(2.8\times 10^{-10}\) & \(2.5\times 10^{-9}\) & \(7.6\times 10^{-9}\) & \(1.8\times 10^{-8}\) & \(2.4\times 10^{-8}\) \\ S & m s\({}^{-1}\) & 21.9 & 40.8 & 50.3 & 56.7 & 58.8 \\ SV & s\({}^{-1}\) & \(1.1\times 10^{-3}\) & \(2.0\times 10^{-3}\) & \(2.9\times 10^{-3}\) & \(3.9\times 10^{-3}\) & \(4.3\times 10^{-3}\) \\ BI & s\({}^{-1}\) & \(9.7\times 10^{-5}\) & \(1.3\times 10^{-4}\) & \(1.8\times 10^{-4}\) & \(2.5\times 10^{-4}\) & \(3.0\times 10^{-4}\) \\ MWT1 & m\({}^{3}\) s\({}^{-3}\) & 0.55 & 15.0 & 154.7 & 5335.2 & 2.62 \(\times 10^{7}\) \\ MWT4 & m\({}^{2}\) s\({}^{-2}\) & \(4.7\times 10^{5}\) & \(2.2\times 10^{6}\) & \(4.5\times 10^{6}\) & \(6.5\times 10^{6}\) & \(7.1\times 10^{6}\) \\ MWT5 & m s\({}^{-2}\) & 0.7 & 3.2 & 8.4 & 16.4 & 20.6 \\ MWT6 & m s\({}^{-2}\) & 21.4 & 115.7 & 285.7 & 498.5 & 598.3 \\ MWT12 & K s\({}^{-1}\) & 0.1 & 0.5 & 1.3 & 2.4 & 3.0 \\ MWT13 & m s\({}^{-2}\) & \(7.6\times 10^{-5}\) & \(4.4\times 10^{-4}\) & \(1.3\times 10^{-3}\) & \(3.4\times 10^{-3}\) & \(4.9\times 10^{-3}\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Thresholds (T1, T2, T3, T4, and T5) corresponding to light, light–moderate, moderate–severe, and severe turbulence categories for individual diagnostics according to the percentile in Table 1.  
evaluating the ability of each turbulence index to describe turbulence, the focus of this work was on the performance analysis of the turbulence index set by determining if turbulence events were detected.