Toward digital twin of the ocean: from digitalization to cloning

Abstract

The forthcoming wave of progress in oceanographic technology is the digital twin of the ocean, a concept that integrates marine big data and artificial intelligence (AI). This development is a logical consequence of combining data science and marine science and is considered superior to previous models, such as the digital ocean, transparent ocean, and smart ocean. Amid the swift advancement of next-generation information technology, the conditions are favorable for developing a prototype digital twin of the ocean, which will integrate various functionalities—data fusion, situation presentation, phenomenon mining, autonomous learning, and intelligent prediction. The salient distinction between a digital twin of the ocean and traditional forms of virtual or augmented reality is because of the intelligence beyond digitalization exhibited by the former, primarily facilitated by AI-based cloning. Hence, herein, we initially propose a structured architecture for the generative digital twin ocean, encompassing elements from real-time data pools to key technologies and proof-of-concept applications. The core components of this prototype system include a data pool, an AI-based oceanographic model, and three-dimensional visualization interactions. Future research and objectives for the digital twin ocean will principally focus on the following: four-dimensional (comprising three-dimensional space along with time) digital cloning and real-time mapping of global ocean parameters, cooperative observation coupled with human–computer interactions, and intelligent prediction along with cutting-edge applications. Prospectively, this transformative technology holds the potential to considerably enhance our understanding of the ocean, yielding groundbreaking discoveries that will profoundly influence the marine economy and sustainable development.