# Assessment of CYGNSS Wind Speed Retrievals in Tropical Cyclones
## 5 Wind Assessment in Tropical Cyclones  
### L2 CYGNSS Wind Products  
We performed comparisons of L2 CYGNSS in TC-winds with wind measurements in storms from the SMAP L-band radiometer, and with the newly released TC-wind datasets for WindSat and AMSR2 which were created using algorithms specifically developed for tropical cyclone conditions. Figure 8 displays the NOAA V1.1, CDR V1.0 YSLF, and SDR V3.0 YSLF wind fields in Hurricane Laura on 26 August 2020, each colocated with SMAP within 4 h to facilitate a visual comparison. The CDR V1.0 is not able to provide much information on the structure of a storm due to its aggressive quality control. The V3.0 YSLF winds display a very noisy and biased field and cannot be used to determine any important feature of the storm, e.g., intensity or the radii of gale (17 m/s)-, storm (25 m/s)-, or hurricane-force (33 m/s) winds, which are all fundamental parameters for hurricane forecasts. On the other hand, the NOAA wind field displays a realistic distribution of the gale- and storm-force winds, but, in this specific example, underestimates the hurricane-force winds. On this day, Hurricane Laura underwent a very rapid intensification, going from barely Cat 1 to Cat 4 within 24 h ([[https://www.weather.gov/lch/2020](https://www.weather.gov/lch/2020) Laura]([https://www.weather.gov/lch/2020](https://www.weather.gov/lch/2020) Laura) accessed on 4 October 2021); therefore, a significant mismatch between satellite observations separated by 4 h is to be expected. A shorter colocation window (not displayed) greatly reduced the number of colocations to just a few tracks within the storm. As we discuss later, this will be useful for building statistics over a large number of storms rather than looking at the 2D wind field of a specific storm. Figure 8: Hurricane Laura surface wind fields on 26 August 2020 from different CYGNSS datasets (**a–c**), respectively colocated within 4 h with SMAP (**d–f**): NOAA V1.1 (**a**), CDR V1.0 YSLF (**b**), and SDR V3.0 YSLF (**c**). The SMAP pass displayed here is at 12 UTC. A similar example is displayed in Figure 9 for the NOAA V1.1 (panels a-c) and V3.0 YSLF winds (d-f), compared to AMSR2 TC-winds colocated within 4 h for Hurricane Dorian, on 4 September 2019. The NOAA V1.1 wind field (panel a) is overall consistent with the one observed by AMSR2 (b) and is able to capture the eye of the hurricane which is missed by AMSR2 due to its lower spatial resolution. The statistical analysis of the colocations (c) confirms the very good correlation (0.83) between the NOAA V1.1 winds and the radiometer AMSR2 and an overall small bias of 0.4 m/s with a standard deviation of 4.8 m/s. A bias appears at wind speeds above 30 m/s, where the NOAA winds are about 10-20% lower than those from AMSR2. On the other hand, the V3.0 YSLF wind displays a very noisy wind field, with a significant bias of 4.8 m/s, standard deviation of 6.9 m/s, and low correlation coefficient (about 0.65). The final example (Figure 10) from Typhoon Hagibis in the Western Pacific on 11 October 2019 shows results similar to the other storms: a high correlation and no significant bias between the NOAA V1.1 winds and AMSR2 up to 35 m/s, but a lack of correlation and significant biases with the SDR V3.0 YSLF winds. Figures 8-10 provide a qualitative comparison between the 2D wind fields in some sample storms, as observed by CYGNSS and the radiometers. For a quantitative assessment, we built a database of 86 such storm scenes between 2017 and 2020 and colocated the CYGNSS observations with the radiometers within a narrower time window of 1 h. The resulting statistics for the NOAA V1.1 versus SMAP, AMSR2, and WindSat TC-winds are shown in Figure 11. When compared to these radiometers, the NOAA V1.1 winds are consistent with the radiometer TC-winds, but they display a negative bias at wind speeds  
Figure 9: Hurricane Dorian on September 4, 2019, in NOAA V1.1 **(a)**, and SDR V3.0 YSLF (**d**), colocated within 4 h with the AMSR2 TC-winds (**b** and **e**, respectively).