# Significant Wave Height Estimation from Space-Borne Cyclone-GNSS Reflectometry
## 4 Conclusions  
In this paper, the SWH in April 2017 is estimated based on the linear relationship between the square root of SNR and the SWH based on the SNR data of CYGNS DDM, and the reliability of SWH based on CYGNSS space-borne GNSS-R observations is verified. The standard deviation between CYGNSS SWH and ECMWF SWH model reached 0.2153 m, the bias was \(-0.0137\) m, and the correlation coefficient reached 0.9752, which was well fitted. Compared with the SWH product of AVISO, the standard deviation value reached 0.3080 m, the bias reached 0.0238 m, and the correlation coefficient reached 0.9473. Due to the impact of land pollution and near-shore shallow water, the satellite radar altimeter data has a large error within 50 km of the near-shore, and the deviation between the CYGNSS estimate and the ECMWF is also larger in the near-shore area, which is influenced by the precipitation on the north and south coasts of the mainland. Therefore, the estimated SWH accuracy in the near-shore area is low.  
The correlation coefficient between the estimated value and the SWH observation of buoy is 0.9539, the bias is \(-0.0496\) m, and the standard deviation is 0.2761 m. As the buoy stations used in this paper are not globally distributed, most of them are concentrated in the Atlantic Ocean, only regional high matching can be verified. More significant buoy stations in other regions are needed to verify the global CYGNSS SWH estimates.  
The SNR-based CYGNSS SWH estimation method requires high spatial resolution, and the time required for the grid to produce high-precision SNR data is also long, so the time resolution of the  
Figure 13: Discrete distribution of CYGNSS SWH estimates and buoy SWH measurements on 1 April 2017.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Precision** & **Bias** & **RMSE** & **R** \\ \hline
**Value** & \(-0.0496\)m & 0.2761m & 0.9539 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Accuracy analysis of CYGNSS SWH estimates versus buoy SWH.  
obtained estimation value is low. In this paper, the influence of satellite parameters on SNR has not been deeply analyzed. The influence of other satellite parameters such as satellite orbits on SNR should be analyzed in order to reduce these effects. Due to the covering limitation of the CYGNSS observation area, this method can only estimate the SWH of the area within 40 degrees north and south latitude. The accuracy of the estimation results depends on the accuracy of the estimation coefficients, so the prior information is important.  
At present, CYGNSS is mainly used to estimate the sea surface wind field. If the parameters, such as sea surface wind speed and direction, are brought into the function, it may improve the accuracy of the estimation coefficient and improve the accuracy of SWH estimation.  
Data curation, Q.P.; Funding acquisition, S.J.; Methodology, Q.P. and S.J.; Resources, Q.P.; Software, Q.P.; Supervision, S.J.; Writing--original draft, Q.P.; Writing--review and editing, S.J.  
Funding: This study is supported by the National Key R & D Program of China under contract #2017 YFB0502800 and #2017 YFB0502802, Chinese Academy of Sciences Pilot A Special Project under contract #XDA23040100 and #XDA23040102, Aerospace Pre-research Technology Project under contract #30508020214, Jiangsu Province Distinguished Professor Project under contact #R2018T20 and Startup Foundation for Introducing Talent of NUIST.  
Acknowledgments: We thank the following organizations for providing the data used in this work: the Cyclone-GNSS (CYGNSS) and European Centre for Medium-Range Weather Forecasts (ECMWF) model.