人工智能海浪预报的发展与挑战  

Progress and challenges of artificial intelligence wave forecasting

作　　者：陆钰婷 郭文康 丁骏[3] 王林峰[2] 李晓辉 王久珂 LU Yuting;GUO Wenkang;DING Jun;WANG Linfeng;LI Xiaohui;WANG Jiuke(School of Artificial Intelligence,Sun Yat-sen University,Zhuhai 528478,China;Shengli Oilfield Company,SINOPEC,Dongying 257051,China;Zhejiang Marine Monitoring and Forecasting Center,Hangzhou,310007,China;Second Institute of Oceanography,MNR,Hangzhou 310012,China)

机构地区：[1]中山大学人工智能学院,广东珠海528478 [2]中国石油化工股份有限公司胜利油田分公司,山东东营257051 [3]浙江省海洋监测预报中心,浙江杭州310007 [4]自然资源部第二海洋研究所,浙江杭州310012

出　　处：《海洋学研究》2024年第3期28-37,共10页Journal of Marine Sciences

基　　金：青岛海洋科技中心区域海洋动力学与数值模拟功能实验室开放基金(2019B03);中石化胜利油田分公司科研项目(YG2203);国家自然科学基金项目(4230200)。

摘　　要：海浪是海洋中最为重要的现象之一,快速准确的海浪预报对于保障海上生产、生活安全具有重要意义。该文回顾了海浪预报方法的发展历程,包括传统统计预报、数值模式预报以及目前快速发展的人工智能预报。基于人工智能的海浪预报模型表现出计算速度快、预报精度自适应优化等优势,已经开始从研究阶段逐步应用于实际海浪预报业务之中,但同时该方法也存在预报要素有限、极端海况预报值偏低以及预报泛化能力弱的局限。该文根据人工智能海浪预报的特点,提出了人工智能海浪预报目前亟需解决的观测数据高效利用、先验知识引入、人工智能模型安全性与泛化能力提升等关键科学技术问题。Waves are one of the most important phenomena in the ocean.The accurate and quick updated wave forecasting is of crucial significance for ensuring marine activities safety.The development of wave forecast is presented,including the traditional statistical wave forecasting methods,numerical wave prediction models,and the rapidly developing artificial intelligence(AI)wave forecasting methods.Currently,AI wave forecast models have been demonstrated unique advantages in terms of computational efficiency and adaptive forecasting accuracy,and they are gradually being applied in practical wave forecasting operations,transitioning from the research stage.However,they also have limitations,including limited forecasting elements,underestimation of extreme wave conditions,and weak forecasting generalization ability.Based on the characteristics of AI wave prediction,key scientific and technological issues that need to be addressed in current AI wave forecasting are proposed.These include efficient utilization of observational data,incorporation of prior physical knowledge,and enhancement of AI model safety and generalization ability.

关 键 词：人工智能 海浪预报 发展历程 数值模式 智能预报 数据驱动 难点挑战 未来趋势 

分 类 号：P731.33[天文地球—海洋科学] P714