# Comparing Winds near Tropical Oceanic Precipitation Systems with and without Lightning
## 3 Results
### Lightning Analysis
#### 3.2.1 Overall Statistics
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Variable** & **Mean** & **99\% Conf. Int. (\(\pm\))** & **Samples** & **RCG \textgreater{} 10** & **Rain \textless{} 6 mm h\textless{}1** \\  & & & **(Mean)** & **(Mean)** \\ \hline CYGNSS FDS with & & & & \\ WWLLN (m s\({}^{-1}\)) & 8.44 & 0.01 & 1,184,585 & 8.61 & 8.34 \\ \hline CYGNSS FDS without & & & & \\ WWLLN (m s\({}^{-1}\)) & 8.62 & 0.00 & 15,227,308 & 8.85 & 8.59 \\ \hline CYGNSS YSLF with & & & & \\ WWLLN (m s\({}^{-1}\)) & 9.14 & 0.01 & 1,176,396 & 8.91 & 9.00 \\ \hline CYGNSS YSLF without & & & & \\ WWLLN (m s\({}^{-1}\)) & 9.25 & 0.00 & 15,075,239 & 8.96 & 9.19 \\ \hline ASCAT with & & & & \\ WWLLN (m s\({}^{-1}\)) & 8.52 & 0.03 & 97,220 & N/A & 8.14 \\ \hline ASCAT without & & & & \\ WWLLN (m s\({}^{-1}\)) & 8.12 & 0.01 & 1,273,200 & N/A & 8.05 \\ \hline IMERG with & & & & \\ WWLLN (mm h\({}^{-1}\)) & 2.95 & 0.01 & 1,184,585 & N/A & N/A \\ \hline IMERG without & & & & \\ WWLLN (mm h\({}^{-1}\)) & 0.89 & 0.00 & 15,227,308 & N/A & N/A \\ \hline CYGNSS Std. Dev. with & & & & \\ WWLLN (m s\({}^{-1}\)) & 1.13 & 0.01 & 28,853 & N/A & N/A \\ \hline CYGNSS Std. Dev. & & & & \\ without WWLLN (m s\({}^{-1}\)) & 1.44 & 0.00 & 294,024 & N/A & N/A \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary statistics for winds and precipitation both associated and not associated with WWLLN lightning. GLM appeared to confirm that some misidentification of thunderstorms was occurring within the \"without lightning\" categories. In general, differences between the \"with\" and \"without\" categories were magnified, but the same basic trends were observed: CYGNSS winds were stronger and more variable in precipitation without lightning (by \(\sim\)0.4-0.5 m s\({}^{-1}\)), while ASCAT winds were stronger in precipitation with lightning by \(\sim\)0.6 m s\({}^{-1}\)). However, the CYGNSS differences were robust when controlling for heavy precipitation (\(>\) 6 mm h\({}^{-1}\)), while ASCAT differences between the categories were reduced (to \(<\) 0.4 m s\({}^{-1}\)). The one exception to this intensified pattern was IMERG precipitation rate. This was still significantly stronger in precipitation with lightning than without, but the overall difference was slightly reduced compared to WWLLN (by \(\sim\)0.15-0.20 mm h\({}^{-1}\)). Finally, ISS LIS statistics are shown in Table 4. The ISS LIS analysis covered 32 months during 2017-2019, and also provided global coverage, but, despite this, the number of samples was greatly reduced compared to the WWLLN or GLM-16 analyses. Regardless, the overall trends were very similar--CYGNSS FDS winds were stronger when ISS LIS-detected lightning was not present than when it was, while the opposite was observed for ASCAT. CYGNSS YSLF winds also followed this trend, but the difference was smaller, and it decreased when controlling for RCG but not for precipitation. However, CYGNSS winds appeared to be more slightly more variable when lightning was present. Note, however, that the available number of samples for several of the \"with lightning\" categories was much smaller than for the other two lightning instruments, so caution is warranted in interpreting these statistics.