# A Study on Assimilation of CYGNSS Wind Speed Data for Tropical Convection during 2018 January MJO
## 3 Results
### Assimilation of the Combined Satellite Datasets  
The above results indicate the positive impacts of CYGNSS data, as well as the limitations of the CYGNSS data when being assimilated into the initial conditions of NWP simulations. Since the IMERG data can measure the precipitation of tropical convection, the ASCAT data can describe the cyclonic circulation of TCs, and the CYGNSS data can provide wind speed observations under heavy precipitation, it would be of great interest to examine how the combined datasets would help with TC and tropical convection intensity and structure. The overall performance of DA_com is compared with other experiments in Tables 2 and 3. As shown in Table 2, DA_com produced the lowest RMS values at all times among all experiments. Specifically, the domain averaged RMS values in DA_com ranged from 1.47 to 2.08 m s\({}^{-1}\). When comparing to CTRL, the RMS values reduced by 1.09 to 1.59 m s\({}^{-1}\), indicating a 41-49% \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Experiment** & **0300 UTC on 7** & **1500 UTC on 7** & **0300 UTC on 8** & **1500 UTC on 8** \\  & **January 2018** & **January 2018** & **January 2018** & **January 2018** \\ \hline CTRL & 2.63 & 2.92 & 3.12 & 3.67 \\ DA\_cyg\_fd & 2.55 & 2.43 & 2.85 & 3.08 \\ DA\_cyg\_lf & 2.45 & 2.37 & 2.70 & 2.97 \\ DA\_com & 1.54 & 1.47 & 1.70 & 2.08 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Domain averaged RMS difference of surface wind speed between ASCAT observation and different numerical experiments. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Experiment** & **0000 UTC on 8** & **0600 UTC on 8** & **1200 UTC on 8** & **1800 UTC on 8** & **0000 UTC on 9** \\  & **January 2018** & **January 2018** & **January 2018** & **January 2018** & **January 2018** \\ \hline CTRL & 0.18 & 0.19 & 0.17 & 0.14 & 0.15 \\ DA\_cyg\_fd & 0.19 & 0.18 & 0.17 & 0.15 & 0.16 \\ DA\_cyg\_lf & 0.19 & 0.19 & 0.18 & 0.16 & 0.15 \\ DA\_com & 0.38 & 0.35 & 0.34 & 0.32 & 0.33 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Threat Score of precipitation forecast with threshold value of 2 mm h\({}^{-1}\) 0000 UTC on 8–9 January 2018 for different experiments with IMERG rainfall as the reference dataset. relative reduction. From Table 3, it is shown that the precipitation forecast skill in DA_com was apparently higher than the rest of the experiments. For example, the TS in CTRL was only 0.15 at 0000 UTC on 9 January 2018, while the value in DA_com was 0.33, which is a relative improvement of 120%. These results indicate large positive impacts with the assimilation of the combined datasets. To illustrate the prediction of intensity and structure of TC Irving, Figure 10 shows a comparison of the sea level pressure (SLP) over-plotted on surface wind from DA_com and CTRL near TC Irving from around 0300 UTC on 7 January and 1500 UTC on 8 January 2018, when ASCAT observation was available. At both times, DA_com produced better intensity estimates than CTRL compared to the best track data. At 0300 UTC on 7 January, the best track data showed that TC Irving had a MSLP between 986 hPa (0000 UTC) and 981 hPa (0600 UTC) and a maximum surface wind speed between 31 m s\({}^{-1}\) (0000 UTC) and 36 m s\({}^{-1}\) (0600 UTC). ASCAT (Figure 10a) missed the strong wind in the core region due to contamination by heavy precipitation. Therefore, the wind asymmetry of TC Irving is unclear. CTRL (Figure 10b) produced a weak storm with a MSLP of 995 hPa and maximum wind of 20 m s\({}^{-1}\), while DA_com (Figure 10c) was able to generate a stronger cyclone with a MSLP of 992 hPa and maximum wind of 30 m s\({}^{-1}\). The strongest wind appeared at the front left quadrant of TC Irving in DA_com and at the front in CTRL, respectively. At 1500 UTC on 8 January, the best track data shows that the intensity of the storm was between 967 hPa (1200 UTC) and 970 hPa (1800 UTC) in MSLP, and 47 m s\({}^{-1}\) (1200 UTC) to 44 m s\({}^{-1}\) (1800 UTC) in maximum surface wind speed.