一个中国边缘海的风-浪-流预报系统

海洋预报是进行海上活动的安全保障，海洋预报系统技术已经成为现代海洋气象业务的技术支撑。海洋观测、数据同化、数值模拟和高性能计算机等技术的进步极大地推动着海洋业务化预报的发展。采用大气数值模式（WRF）、海洋数值模式（CROCO）和海浪数值模式（SWAN）的多模式高分辨率离线耦合方式，添加南京信息工程大学“海洋数值模拟与观测实验室”团队自主研发的一系列海洋模式参数化方案，包括浪致混合参数化方案、亚中尺度参数化方案、海山诱导混合参数化方案以及涡旋诱导的沿等密度面和跨等密度面混合参数化方案，并通过同化技术和最新的人工智能技术与观测资料相结合，构建一种面向中国边缘海的风浪流多参数耦合预报系统，用于海上风电功率的预报和其他海洋灾害预警。实际观测资料的验证表明，该预报系统能较准确地模拟海上风场、海流、海温、波浪、潮汐等海洋气象要素。同时实现了按需实时可视化全景展示。

A Wind-Wave-Current Forecast System for China's Marginal Seas

Marine forecasting is essential for human activities at sea. Marine forecasting system technology supports modern marine meteorological services. Advances in oceanic observation, data assimilation, numerical simulation and high-performance computing also drive the development of marine operational forecasting. The present study uses the Weather Research and Forecasting (WRF) atmospheric model, the Coastal and Regional Ocean Community (CROCO) model and the Simulating Wave Nearshore (SWAN) model to develop a multi-model high-resolution offline coupled forecasting system over China''s marginal seas, for offshore wind power forecast and marine disaster warning. This forecasting system integrates a series of ocean model parameterization schemes, including wave mixing parameterization, mesoscale parameterization, and seamount- and eddy-induced parameterization developed by the Oceanic Modeling and Observation Laboratory of the Nanjing University of Information Science and Technology. Furthermore, observation data are assimilated using data assimilation and artificial intelligence technology in this system. The comparison and analysis of forecast and observation results show that the forecast system can accurately simulate the marine meteorological elements such as surface wind, ocean surface current, sea surface temperature, wave and tide. At the same time, on-demand real-time visual panorama display is realized.