# A Method to Reduce Non-Nominal Troposphere Error
## 3 Non-Nominal troposphere Model and Error Bounding Method  
Under non-nominal troposphere, the troposphere delay differentials between the GBAS ground facility and the aircraft are relatively larger, i.e., the residual troposphere uncertainty in current GBAS standards cannot bound the corresponding sigma troposphere. To study non-nominal troposphere, the wedge model was proposed by [PERSON] of the University of Newcastle in 1998; this model considers only the effect of weather front on troposphere propagation delays, as shown in Figure 7[11]. In 2008, researchers from Ohio State University proposed the weather wall model, which is based on the observation that local or nearby heavy rainfall is strongly correlated with the observed troposphere delay variations, as shown in Figure 8[12]. After discussions \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Time** & **Station** & \begin{tabular}{c} **Maximum Change in** \\ **Temperature (\({}^{\circ}\)C/h)** \\ \end{tabular} & \
\begin{tabular}{c} **Maximum Change in** \\ **Pressure (hPa/h)** \\ \end{tabular} &
\begin{tabular}{c} **Maximum Change in** \\ **Relative Humidity (\%/h)** \\ \end{tabular} \\ \hline
19 July 2015 & kun1 & 10.7 & 13.4 & 26.8 \\
23 July 2015 & lhaz1 & 9.4 & 10.9 & 26.7 \\
19 June 2015 & sha1 & 9.2 & 9.6 & 30.1 \\
21 June 2015 & xia1 & 10.8 & 11.9 & 33.4 \\
24 July 2016 & bjf1 & 11.4 & 14.8 & 28.1 \\
31 June 2016 & canb & 10.9 & 13.3 & 29.7 \\
24 June 2016 & chu1 & 12.3 & 15.7 & 30.9 \\
31 July 2016 & cptn & 11.6 & 14.8 & 31.7 \\
27 July 2016 & kun1 & 10.7 & 12.7 & 29.5 \\
30 July 2016 & lhaz1 & 8.7 & 10.2 & 29.8 \\
15 June 2016 & sha1 & 9.6 & 10.2 & 32.4 \\
17 July 2016 & xia1 & 10.8 & 11.5 & 33.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Cont. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Time** & **Station** & \begin{tabular}{c} **Maximum Change in** \\ **Temperature (\({}^{\circ}\)C/h)** \\ \end{tabular} & \
\begin{tabular}{c} **Maximum Change in** \\ **in Pressure (Pa/h)** \\ \end{tabular} &
\begin{tabular}{c} **Maximum Change in** \\ **Relative Humidity (\%/h)** \\ \end{tabular} \\ \hline
20 July 2015 & bjnm & 11.3 & 14.1 & 28.7 \\
9 July 2015 & chan & 10.2 & 13.2 & 28.4 \\
16 July 2015 & bjfs & 11.1 & 13.8 & 27.5 \\
19 July 2015 & kunm & 10.8 & 13.6 & 27.1 \\
23 July 2015 & lhaz & 9.1 & 10.7 & 26.5 \\
19 June 2015 & shao1 & 9.7 & 10.3 & 32.8 \\
22 July 2015 & urum & 10.9 & 13.7 & 31.1 \\
17 July 2015 & wuhn & 11.2 & 14.5 & 29.8 \\
21 June 2015 & xian & 10.5 & 11.5 & 32.8 \\
26 July 2015 & guao & 11.3 & 13.2 & 27.4 \\
23 July 2016 & bjnm & 11.6 & 14.2 & 29.4 \\
16 July 2016 & chan & 10.7 & 13.8 & 28.7 \\
24 July 2016 & bjfs & 11.1 & 15.0 & 27.9 \\
27 July 2016 & kunm & 10.6 & 12.7 & 26.7 \\
30 July 2016 & lhaz & 8.8 & 10.1 & 25.5 \\
15 June 2016 & shao1 & 9.4 & 9.8 & 32.2 \\
30 July 2016 & urum & 10.5 & 13.5 & 30.2 \\
11 July 2016 & wuhn & 11.7 & 14.9 & 30.4 \\
17 June 2016 & xian & 10.3 & 11.2 & 32.5 \\
17 July 2016 & guao & 10.6 & 12.7 & 26.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The most serious troposphere anomalies at 10 IGS stations in China. involving an expert panel, the researchers from Ohio State University finally chose the weather wall model as the non-nominal troposphere model. In Figures 7 and 8, the parameters T, P and RH are the meteorological parameters representing temperature, pressure and relative humidity, respectively. Additionally, the parameter 0 indicates the nominal troposphere and w denotes the non-nominal troposphere. The weather wall model represents discrete weather conditions. On the left side of the wall, the weather conditions are described by T\({}_{0}\), P\({}_{0}\), and RH\({}_{0}\), whereas the conditions within the weather wall are given by T\({}_{\text{w}}\), P\({}_{\text{w}}\), and RH\({}_{\text{w}}\).