# Assessment of CYGNSS Wind Speed Retrievals in Tropical Cyclones
## 7 Summary and Conclusions
One of the weaknesses of CCMP is the relative paucity of satellite observations in the tropics (and in tropical storms) due to the presence of moderate to heavy rain. As the CYGNSS observations are only minimally affected by rain, they present the possibility of filling data gaps in the measurements made by other satellites. A choice had to be made to select the CYGNSS dataset to be assimilated, which needs to meet the following requirements: have good spatial coverage within 40S-40N (smaller number of flagged data); be free of major regional biases; have smaller bias and standard deviation at all wind speeds, particularly at 0-20 m/s; and have a realistic wind-speed probability distribution function. Additionally, while not high priority, it is also desirable that the CYGNSS dataset to be assimilated displays a realistic representation of high winds (wind speed \(>\) 20 m/s), globally and in TCs. Our analysis emphasized that the most suitable dataset for an L4 gridded product and potential assimilation in CCMP is the NOAA V1.1, as it is superior to the others in all aspects listed above. The NOAA V1.1 dataset also has the advantage of using only one algorithm valid at all wind speeds, which helps to avoid the ambiguity of having to choose different wind products at different wind regimes. Our analysis showed that the addition of CYGNSS measurements to CCMP resulted in changes in the analyzed wind field, particularly in the vicinity of tropical cyclones. More analysis is needed to determine if these changes represent a significant improvement in CCMP winds, both near cyclones, and in the tropical oceans in general. The CCMP_CYGNSS wind analysis is designed for air-sea interaction studies and provides insight into the wind structure in convective regions such as investigations into the Madden-Julian Oscillation [59], genesis of TCs [60], and diurnal wind variability [63; 64]. CCMP_CYGNSS for the period 2017-2020 is freely available to the public at [[https://data.remss.com/research/cygnss](https://data.remss.com/research/cygnss)]([https://data.remss.com/research/cygnss](https://data.remss.com/research/cygnss)) (accessed on 15 November 2021). The following are available online at [[https://www.mdpi.com/article/10.3390/rs13245110/s1](https://www.mdpi.com/article/10.3390/rs13245110/s1)]([https://www.mdpi.com/article/10.3390/rs13245110/s1](https://www.mdpi.com/article/10.3390/rs13245110/s1)), Figure S1: Wind speed bias for CYGNSS NOAA V1.1 winds compared to WindSat all-weather winds, WindSat rain-free only, and SMAP, all wind regimes; Table S1: List of storms and sample days included in the database built for the assessment of CYGNSS winds in TCs. Conceptualization, L.R. and T.M. ; methodology, L.R., T.M. and C.M. ; software, L.R. and C.M. ; validation, L.R. and A.M.; formal analysis, L.R. ; investigation, L.R., T.M., C.M. and A.M.; resources, L.R. ; data curation, L.R. ; writing--original draft preparation, L.R. ; writing--review and editing, L.R., T.M., C.M. and A.M.; visualization, L.R., A.M. and C.M. ; supervision, L.R. and T.M. ; project administration, L.R. ; funding acquisition, L.R., C.M. and T.M. All authors have read and agreed to the published version of the manuscript. This research was funded by NASA Earth Science, grant number: NASA 80 HQTR18C0033 (CYGNSS Competed Science Team). All the CYGNSS datasets used here are available to the public at the NASA PO.DAAC [[https://podaac.jpl.nasa.gov/CYGNSS](https://podaac.jpl.nasa.gov/CYGNSS)]([https://podaac.jpl.nasa.gov/CYGNSS](https://podaac.jpl.nasa.gov/CYGNSS)).