# A Study on Assimilation of CYGNSS Wind Speed Data for Tropical Convection during 2018 January MJO
## 3 Results
### CYGNSS Data Assimilation
The track error in DA_cyg_fd was generally smaller than those of either CTRL or DA_cyg_lf, except at 1800 UTC on 7 January and in the last 6 h of the forecast period. For example, at 0000 UTC on 8 January,  
Figure 8: (**a**) TC Irving track from JTWC best track data, CTRL, DA_cyg_fd, DA_cyg_lf, and DA_com and (**b**) track error from CTRL, DA_cyg_fd, DA_cyg_lf, and DA_com at 0000 UTC on 6–9 January 2018. Figure 7: Time series of TC Irving intensity for (**a**) MSLP and (**b**) maximum surface wind speed from JTWC best track data, CTRL, DA_cyg_fd, DA_cyg_lf, and DA_com at 0000 UTC on 6–9 January 2018.  
the center location of TC Irving in DA_cyg_fd (the track error of 100 km) was much closer to the observed location when compared with the one in CTRL (the track error of 175 km) and the one in DA_cyg_lf (the track error of 137 km). Figure 9 displays IMERG precipitation, CYGNSS FDS and YSLF wind speed, ASCAT wind speed and model simulated wind from DA_cyg_lf and CTRL over the region of the WWB event when ASCAT captured a portion of the event near 1500 UTC on 8 January 2018. IMERG (Figure 9a) shows the convection related to the WWB event produced a maximum precipitation over 10 mm h\({}^{-1}\). ASCAT (Figure 9b) indicates a large area with wind speed over 12 m s\({}^{-1}\) and a maximum of 20 m s\({}^{-1}\). CYGNSS FDS (Figure 9c) detected weaker winds for the WWB with \(<\) 10 m s\({}^{-1}\) at most points, and a maximum value of 12 m s\({}^{-1}\), while in YSLF data (Figure 9d), many points in the three tracks across the observed WWB region had wind speed \(>\) 12 m s\({}^{-1}\) with a maximum of 27 m s\({}^{-1}\). The assimilation of high winds in YSLF data explains the apparent increase in the analysis wind field. Surface wind speed in DA_cyg_lf (Figure 9f) exceeded 14 m s\({}^{-1}\) over the storm area, while the surface wind speed in CTRL (Figure 9e) was generally below 12 m s\({}^{-1}\). Figure 9: (**a**) IMERG precipitation for the WWB event at 1500 UTC on 8 January 2018, (**b**) ASCAT wind speed around 1436 UTC on 8 January 2018, (**c**) CYGNSS FDS and (**d**) YSLF wind speed around 1500 UTC on 8 January 2018, and surface wind speed from (**e**) CTRL and (**f**) DA_cyg_lf at 1500 UTC on 8 January 2018. The overall impacts of the CYGNSS observation on surface wind and precipitation fields are shown in Tables 2 and 3. Table 2 lists the domain averaged RMS of surface wind speed difference between different experiments and ASCAT wind speed within the model domain available around 0302 and 1448 UTC on 7 January and 0239 and 1436 UTC on 8 January 2018. As shown in the table, the assimilation of both CYGNSS FDS and YSLF data led to smaller RMS values at all times. At 1500 UTC on 8 January, the RMS reduced by up to 0.7 m s\({}^{-1}\) in DA_cyg_lf when comparing with CTRL. Table 3 lists the threat scores (TS) of precipitation forecast with a threshold value of 2 mm h\({}^{-1}\) from different experiments. The IMERG data were used as the reference dataset. The TS was calculated using the equation from [PERSON] et al. (2019):  
\[TS=\frac{C}{F+R+C} \tag{1}\]  
where C is the number of correct forecast events (points with precipitation exceeding the threshold value), R is the number of events in observation, and F is the number of events in forecast. As indicated in Table 3, the differences in TSs between CTRL and the data assimilation experiments DA_cyg_fd and DA_cyg_lf were as small as 0.01-0.02, which indicates that the influence from assimilation of CYGNSS data only was not significant. This could be attributed to the continuous correction of model dynamics, which commonly occurs when only surface data are assimilated. Another possible reason is the lack of dynamic support from the convective and thermodynamic fields for convection to grow. This was the motivation for the DA_com data assimilation experiment, as described next.