Martin Visbeck

Martin Visbeck, GEOMAR Helmholtz Centre for Ocean Research Kiel and Kiel University, Germany

Martin is head of the research unit Physical Oceanography at GEOMAR Helmholtz Centre for Ocean Research Kiel and a Professor at Kiel University, Germany. His research interests revolve around the ocean’s role in the climate system, integrated global ocean observation, digital twins of the ocean and the ocean dimension of sustainable development. Under the UN Ocean Decade, he has co-launched the Decade Action “Digital Twins of the Ocean” (DITTO). Martin also serves on a number of national and international advisory committees including the WMO Research Board, Joint Scientific Committee of the World Climate Research Programme (WCRP), leadership council of the Sustainable Development Solutions Network (SDSN), Interim Decade Advisory Board for the UN Decade of Ocean Science Decade for Sustainable Development 2021-2030 and the Assembly supporting the development of the EU Horizon Europe Ocean Mission. He is the past President of The Oceanography Society (TOS), and was elected fellow of the AGU, AMS, TOS, ISC and the European Academy of Sciences.

The ocean remains largely under discovered and systematically observed. However, over the recent decade, more advanced robot-based observations and a significant improvement in ocean models allows to build digital replicas of the ocean with increasing realism. At the same time, human use and interference with the ocean is increasing, in particular in coastal regimes. One of the key challenges is how to best govern human interactions with the ocean. Such decisions should be science-supported and Digital Twins of the Ocean (DTO) provide an interesting framework. 

Digital Twins are digital replicas of real-world objects that have a two-way connection between the digital twin and the real ocean. Ocean observations provide an update on the state of the ocean and changes in human behavior are expected to alter the ocean. DTOs rely on an adequate ocean observing system where satellites and robots provide increasing capabilities. They require a prediction system that will be based on dynamical ocean circulation models enhanced with component representations of the chemistry, biology, and ecology. In particular the latter elements benefit from machine learning approaches. Finally, the DTOs allow users to get answers to ‘what it’ questions and should have the capability to visualize future ocean states depending on human actions. 

Thus, an accurate real-time ocean observing system supplemented by a state-of-the-art data sharing system is central to the success of a DTO. Whilst the network of marine observing systems has made great advances in recent years, there are still oceanic regions that remain under-observed, and large observational gaps for many essential ocean variables (EOVs) exist. Marine robotics provide an opportunity to fill this gap, as they can collect data from regions inhospitable to humans, e.g., the Abyssal Ocean and supplement the more expensive human operated ships. 

In addition to natural ocean phenomena, DTOs can include socio-economic factors (e.g. cost of action, ocean-use, pollution). By illustrating different possible mitigation or adaptation scenarios, for example the construction of a dike to mitigate sea level rise, the DTO allows its users to answer concrete ‘what if’ questions that inform development decisions. DTs thus enable the anticipation of desired outcomes or undesirable consequences of human-environment interactions, greatly facilitating policy and decision-making processes. The challenge is to ensure that DTOs are interoperable and become easily accessibility. Then DTOs can be used by a variety of stakeholders: by scientists to understand the ocean, by policymakers to make well-informed decisions, and by citizens to improve ocean literacy. As such, DTOs present a valuable opportunity to future-proof sustainable ocean development.