# Ocean Wind Retrieval Models for RADARSAT Constellation Mission Compact Polarimetry SAR
## 5 Conclusions  
The estimation of ocean surface winds by SAR is an important research field of satellite remote sensing. Because RCM will provide CP products which differ from the conventional polarimetry SAR, the establishment of new specific models for potential wind retrieval from CP SAR parameters is an urgent need. In this paper, we propose two wind retrieval models for C-band RCM SAR CP model: (1) CoVe-Pol model for RV polarization data, and (2) CoHo-Pol model for RH polarization data. The two models are derived from collected data consisting of 267 RADARSAT-2 SAR quad-polarized images and collocated buoy data. These two models can be applied to the real CP data when RCM will have been launched and succeeds in providing data. The CP-polarized data sets are generated from quad-polarized SAR data by a RCM simulator. We have divided these data randomly into two data groups: one for building new models and the other reserved for model testing. To develop CoVe-Pol model, we carried out a sensitivity analysis in the process of creating the new GMF coefficients. We separate the derivation process for the coefficients into several steps. These steps are designed according to a sequence determined by the orders of magnitude of the CMOD coefficients, in order to reduce the required computations, so that the numerical process can be possible in terms of available computer resources. Utilizing sensitivity analysis factors (_SAFs_) for the coefficients provides an efficient methodology for building a new GMF for the RV polarization data, by adjustment of  
Figure 11: The comparsion of wind speed estimation results between using the linear realtionships with CMOD5.N and using CoVe-Pol model: (**a**) wind speed estimation through the linear relationships with CMOD5.N vs. wind speed measured by buoys; (**b**) wind speed retrieved by CoVe-Pol model vs. wind speed measured by buoys. these coefficients. In this approach, when the new GMF is derived, the correlation coefficient between RV-polarized computed NRCSs and simulated NRCSs reaches 97.1%, and the RMSE is only 1.29 dB. The wind retrieval by the associated CoVe-Pol model parameterization is shown to have a good performance based on the RV polarized SAR data. The RMSE is 2.48 m/s, and the bias is 0.07 m/s. To produce the RH model for wind retrieval, we use a quadratic function in a regression model to relate buoy wind speed to the RH NRCS data along with the radar incidence angles. Comparing results with the winds measured by buoys, the RH model, denoted CoHo-Pol, is shown to behave well in wind retrievals, with RMSE of 2.37 m/s. The model results indicate that the RH model is a useful way to retrieve wind speed as a fast inversion methodology. We test the two new models, CoVe-Pol and CoHo-Pol, with the reserved test data set, and show that there is strong agreement between both the models and the data. Thus, these two new models can potentially be applied to retrieve wind from CP C-band SAR measurements. In February 2019, the three satellites of RCM are scheduled for launching together. Compared to what we have now with the separated single SAR satellite (e.g., RADARSAT-2 or Sentinel-1), the three continuous observations make the temporal studies of oceanography and/or atmosphere possible. Therefore, the ocean wind retrieval models developed here would be important for temporal oceanography or atmosphere dynamic research based on RCM SAR data. Writing-Original Draft Preparation and processing datasets, T.S. ; Designing methodology, proposing the model and designing this study, G.Z. ; Supervision, writing-Review and editing, W.P. ; Validation, B.Z. ; Formal Analysis, C.G. ; Resources, S.K. ; Data Curation, K.W; Software, J.S.