A Statistical Quality-Control Framework for Sentinel-1 SAR Wind Speed Retrieval Based on First- and Second-Order Moments - Yan Wang; Xupu Geng; Yan Li; Xiaohui Li; Chenghan Luo; Shaoping Shang; Feng Zhang (Journal of Marine Science and Engineering, 2026)
Synthetic Aperture Radar (SAR) enables high-resolution sea-surface wind speed retrieval. However, the enhanced spatial resolution of SAR imagery introduces substantial challenges, from small-scale contamination sources that significantly degrade retrieval accuracy. Particularly in coastal regions, non-wind-related backscatter signals, such as ships and oil slicks, can severely bias wind speed estimates at sub-kilometer scales. In this study, the first-order moment (average, m1) and second-order moment (variance, m2) are computed from the normalized radar cross-section (NRCS) within sub-images of Sentinel-1 SAR data acquired in Interferometric Wide (IW) mode. Analysis reveals that clean-sea-surface signals in both VV and VH polarizations cluster around an approximately linear empirical trend, m2 = 2m1 + b, in the m1-m2 statistical feature space, whereas the examined contamination types deviate from this trend and occupy separable regions. Based on this characteristic, a quality-control framework is proposed for the systematic separation of clean sea surface from image noise (border noise and inter-swath stripe noise) and non-ocean targets (land contamination, bright targets, and dark spots). Validation using independent SAR data from the Taiwan Strait was conducted separately for native 10 m and height-adjusted 3 m buoy observations. For the native 10 m observations, the RMSE and MBE were essentially unchanged at 1.5 m/s and −0.3 m/s, respectively. For the height-adjusted nearshore observations, the RMSE decreased from 3.2 m/s to 2.1 m/s and the MBE changed from −1.5 m/s to −1.1 m/s.

WaveCastNet-C: Forecasting the significant wave height in the China Sea with a fully convolutional neural network - Hao Dai; Zhihan Xie; Famei Lei; Xining Zhang; Guomei Wei; Rui Lin; Weijie Zhang; Shaoping Shang (Ocean Engineering, 2026)

A Study on the Impact of Vertical Grid Parameter Perturbations in the Regional Ocean Modeling System - Lei Wang; Feng Zhang; Chongwei Zheng; Yaozhao Zhong; Tianxiu Lu; Shaoping Shang; Siyu Pu; Guodong Xia; Huafei Chen; Wei Leng (Journal of Marine Science and Engineering, 2024)
In this study, the Regional Ocean Modeling System (ROMS) is employed to construct a three-dimensional barotropic ocean model with a monodirectional upper boundary and homogeneous and steady wind covering the entire computation area. Eight perturbation experiments are designed to determine the vertical grid distribution difference with high resolution at the surface and bottom. Two types are considered in the model, including removing the Coriolis force (type 1) and employing a different Coriolis force (type 2). According to the experiments, the velocity of the current in type 1 yields uncertainty, and wind energy could penetrate the upper ocean and reach the abyss. The surface velocity in type 2 is fundamentally compatible with the empirical relationship constructed by Ekman, and the curved lines of the vertical distribution of horizontal currents nearly match. For type 1, the velocity is very strong from the sea surface to the bottom. When comparing type 1 and type 2 cases, the Coriolis force obstructs the wind energy transfer into the deep ocean. In addition, the European Centre for Medium-Range Weather Forecasts (ECMWF)’s global surface wind distribution indicates that the realistic ocean upper wind boundary is similar to the numerical experiment in the Pacific and Atlantic oceans, where the wind direction is along the latitude line at the equator. In order to make the experimental situation as close as possible to the real ocean, validation experiments are conducted in this study to consider the uncertainty in the current profile at the equator. The simulation results of type 1 differ significantly from the data obtained from the real ocean. This uncertainty may transfer the signal to higher latitudes, causing incorrect simulation results, especially in the critical region. Overall, this research not only makes discoveries in physical ocean theory but also guides predictive and forecasting techniques for ocean modeling.

Sea surface temperature prediction by stacked generalization ensemble of deep learning - Hao Dai; Famei Lei; Guomei Wei; Xining Zhang; Rui Lin; Weijie Zhang; Shaoping Shang (Deep Sea Research Part I: Oceanographic Research Papers, 2024)

Energy analysis of wind-induced wave and current during typhoon kalmaegi - Feng Zhang; Lei Wang; Chongwei Zheng; Kenny Thiam Choy Lim Kam Sian; Shaoping Shang; Hengyou Lan; Zhijie Jiang; Yundong Li; Han Zhang; Zhigang He; Guomei Wei; Yanshuang Xie; et al. (Estuarine, Coastal and Shelf Science, 2023)

Analysis of the dynamic mechanisms of upwelling in deep ocean water caused by typhoons - Famei Lei; Hao Dai; Shaoping Shang; Zhigang He; Shuai Yang (Ocean Dynamics, 2023)

Risk Assessment of Wave Over-Topping Based on Smoothed-Particle Hydrodynamics Method - Lei Wang; Li Zhang; Yanshuang Xie; Yaozhao Zhong; Yuan Sun; Zhiyuan Wang; Feng Zhang; Shaoping Shang (Journal of Marine Science and Engineering, 2022)
FETSWCM-SWAN and DualSPHysics models are used to study the storm flooding process of Dazuo Seawall in Quanzhou city, Fujian province, China. Firstly, a storm over-topping assessment method is proposed. Secondly, the water level and storm wave at the foot of Dazuo Seawall calculated by FETSWCM-SWAN during the process of Typhoon Usagi in 2013 and Typhoon Dujuan in 2015. Finally, the typical wave and storm run-up processes at Dazuo Seawall are modeled by DualSPHysics. The results show that the typical wave run-up of Dazuo Seawall is less than 2 m, but the storm wave run-up can reach 6.85 m under Usagi. The risk is high when high tide is encountered. The risk of storm flooding is classified into three grades. This risk assessment could provide decision-making support to government departments in warning against storm flooding threats.