# Assessment of CYGNSS Wind Speed Retrievals in Tropical Cyclones
## 6 Assimilation of CYGNSS Winds in CCMP  
As detailed in Section 2.4, the CCMP is a satellite-based wind variational analysis which assimilates many radiometer datasets as well as the QuikSCAT/ASCAT scatterometer winds. The analysis results in 6-hourly, 0.25\({}^{\circ}\) maps for the wind components (\(u\), \(v\)) extending from 1988-present. In regions within the satellite gaps, a numerical model serves as a background wind field. Before the assimilation, the radiometer and scatterometer wind retrievals need to be flagged in rainy areas to avoid ingesting satellite observations affected by rain contamination. For this reason, particularly in the tropical regions, the CCMP analysis corresponds more closely with the background field and thus is not improved by satellite measurements. CYGNSS provides wind measurements that are not, or only slightly, affected by rain at low wind speeds [17].  
The assessment presented in Sections 3-5 indicates that _the most suitable dataset for assimilation into an L4 gridded product such as CCMP is the NOAA V1.1_, as it meets the following requirements: good data coverage within 40S-40N; no significant regional biases; good accuracy in the wind speed range 0-20 m/s and in storms.  
The assimilation of the CYGNSS retrievals within tropical latitudes therefore provides an opportunity to investigate the impact of filling the radiometer/scatterometer gaps with actual satellite observations from CYGNSS, rather than a numerical model wind. The impact of assimilating the NOAA CYGNSS V1.1 into a version of CCMP_CYGNSS (years 2017-2020) can be assessed with comparisons with the control version CCMP V2 (available at [[https://www.remss.com/measurements/ccmp/](https://www.remss.com/measurements/ccmp/)]([https://www.remss.com/measurements/ccmp/](https://www.remss.com/measurements/ccmp/)), accessed on 15 August 2021).  
An example of the CCMP wind field with and without CYGNSS data is presented in Figure 18, for Hurricane Florence in the Atlantic, during the early stage of development, on September 2, 2018. The hope is that by filling the radiometer/scatterometer observation gaps in the wind analysis we can improve the representation of the CCMP wind vectors in these regions. These changes may have important impacts on the wind divergence and vorticity. In the early stages of tropical cyclone formation, the wind fields under tropical disturbances from radiometers/scatterometers often cannot be ingested because of the presence of rain in the nascent tropical system.  
Figure 17: Comparison of CYGNSS storm-centric for Hurricane Leslie on 3 September 2018 (06:00 UTC scene, panel (**a**)), compared to AMSR2 pass at 4:55 UTC (**b**), and on 11 October 2018 (06:00 UTC, (**d**)), compared with SMAP pass at 09:36 UTC (**e**). Panels (**c**,**f**) display the respective scatterplots.  
Figure 18: The effect of the assimilation of CYGNSS measurements in CMP for Hurricane Florence on 2 September 2018. Panels (**a**,**b**) show the location of assimilated measurements without and with the additional CYGNSS retrievals. Panels (**c**,**d**) show the wind speed and (**e**,**f**) the zonal wind fields without and with the inclusion of CYGNSS. Panels (**g**,**h**) display the difference in wind speed and zonal wind component caused by assimilating the CYGNSS data.  
Changes to the final product were usually subtle. In Figure 18, we show an example of the typical results for a TC early in the formation process. In this case, the main effect of including CYGNSS observations was to increase the CCMP wind speeds to west of the storm center in the gap between satellite observations, but with little change in the location of the storm. It is not yet known whether these subtle changes in the CCMP results represent an improvement in accuracy--determining this will require a comprehensive study that is beyond the scope of this paper.