Intelligent Correction of CFOSAT Significant Wave Height Measurement Error Based on Credible Radius

In the study of the matching correction of buoy and satellite data, the matching error is mainly composed of two parts : measurement error and representative error. In order to reduce the interference of wave representative error and accurately correct the measurement error, this study proposes a joint correction method combining ' credible radius ' and ' confidence interval screening '. Based on the buoy observation of the National Data Buoy Center (NDBC), the significant wave height (SWH) data of China-France Oceanography Satellite (CFOSAT) are corrected. Through the systematic analysis of the matching error, the concept and judgment method of ' credible radius ' are proposed, and the credible radius is determined to be 9 km. The deep neural network correction model is constructed by using the trusted radius matching data. The experimental results show that the model trained by the joint correction method of ' credible radius ' and ' confidence interval screening ' has the best performance. The average absolute error of the verification set is reduced by 16.2%, and the MAE of the test set is reduced by 14.8%. In addition, there is a stable error reduction in all matching radius distance intervals and wave height ranges. This method effectively enhances the accuracy and reliability of CFOSAT inversion data, and provides a new technical path for the fine correction of marine remote sensing data.