# Comparing Winds near Tropical Oceanic Precipitation Systems with and without Lightning
## 5 Conclusions  
In order to examine how robust updraft strength and ice-based microphysical processes aloft in storms may affect convective outflows near the surface, ocean winds were compared between tropical maritime precipitation systems with and without lightning. The analysis focused on CYGNSS specular point tracks, using straightforward spatiotemporal matching criteria to pair CYGNSS-measured wind speeds with IMERG precipitation, ASCAT-A and -B wind speeds, and lightning flash data from WWLLN, GLM-16, and ISS LIS. Based on the results, thunderstorms over the tropical oceans are clearly associated with significantly heavier rain rates (~200% greater) than non-lightning-producing showers. This is consistent with past work on relationships between lightning and rainfall [45; 46]. However, wind speeds near either type of precipitation system do not differ much (~0.5 m s\({}^{-1}\) or less). Moreover, the sign of the difference depends on the wind instrument used, with CYGNSS suggesting non-thunderstorm winds are (counterintuitively) slightly stronger, while ASCAT suggests the opposite. These observed wind differences are likely related to remaining uncertainties in the comparison of CYGNSS/ASCAT in precipitation (e.g., GMF uncertainties when winds are variable, rain impacts on measurement accuracy, etc.). If ASCAT observations are considered more accurate in rainfall than CYGNSS, then the hypothesis that thunderstorms are associated with stronger surface outflows (suggesting also stronger cold pools) is supported by the available evidence. However, if this is not the case and CYGNSS winds are more accurate than ASCAT in rainfall, then there is not enough evidence to support the thunderstorm outflow hypothesis (indeed, the opposite argument might be made), which would be unexpected. However, it is possible that the dataset was well-populated with relatively weak, low-flash-rate thunderstorms (this is supported by the greater uncertainty in the Figure 6 curves when flash rates exceeded 1-2 min\({}^{-1}\)), which indeed may not feature significantly stronger surface winds than non-thunderstorms. In that case, the CYGNSS observations may be consistent with expectations. Another complicating factor to consider is that thunderstorms over the global ocean tend to be larger and more organized than those over land [47; 48]. Thus, CYGNSS overpasses may sample stratiform precipitation in lightning-producing systems more often, where winds would be expected to be weaker than near, e.g., the leading-edge gust front. Regardless, both CYGNSS and ASCAT find winds near precipitation (whether lightning-producing or not) to be stronger than background by at least 1 m s\({}^{-1}\), consistent with prior studies [3; 4]. Future work will focus on a longer period of record, improved CYGNSS wind datasets, and incorporating ASCAT into the analysis in a manner that preserves its swath-based observations. In addition, IMERG data are expected to improve with time. These changes may enable more accurate characterization of wind variability near precipitation systems. Moreover, future improvements to the GLM and ISS LIS datasets are expected to increase their effective detection efficiencies and reduce their false alarm rates [32; 33]. This will mitigate remaining uncertainty in whether a precipitation system is a thunderstorm or not. This research was funded by the CYGNSS, Ocean Vector Winds Science Team (OVWST), and Earth from ISS programs within the Science Mission Directorate (SMD) of the National Aeronautics and Space Administration (NASA). This research benefited from fruitful conversations about the various datasets used with the following people: [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] The Physical Oceanography Distributed Active Archive Center (PO.DAC) supplied the CYGNSS and ASCAT data. IMERG data were obtained from Goddard Space Flight Center. University of Washington supplied the WWLLN data.