MAS-DT

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The National Oceanography Centre (NOC) operates ocean gliders for the Met Office and Royal Navy to collect earth observations, driving ocean forecast models. These models, in turn, underpin operational weather forecasts. Currently, observations are targeted at ocean model grid boxes in high-impact areas of UK waters. An extension of this approach is to optimise ocean glider observations to maximise their impact on ocean models and, thus, weather forecasts using the concept of an interoperable Digital Twin (DT) building on recent IMFe recommendations. We propose a demonstrator digital twin which combines earth observations with sub-surface ocean glider data and operational ocean model. The resulting novel four-dimensional picture will be presented through a User interface (UI), allowing scientists to identify the potential observations which could have the most impact, and allowing the definition of operational objectives to be achieved those observations. The objectives will feed a mission planning service that will take account of glider capabilities (such as battery life and speed) to re-task the glider, thus optimising the observations for most impact, creating a virtuous feedback circle between the observing capability and the ocean model data assimilation. This feedback between scientists, earth observation data, and glider operations in near real-time will maximise the value of the observations collected and their impact on ocean forecasting. This in turn will maximise the societal value of these publicly funded ocean observations. While this project will assemble and demonstrate the digital twin around Met Office operations, this DT will be a generic framework that will support plug-and-play interoperability of different models and autonomy engines to drive observations to optimise models. It is envisaged the applicability of the results will scale to the piloting operations for marine autonomous systems spanning a wide range of vehicle operations including the NERC research community. The work will build on, and directly contribute to further development of the Information Management Framework for environmental digital twins (IMFe), focusing on the interfaces between existing components via a communities of practice approach with best practices being included in community outputs (such as the Turing way and the TWINE community). This will enable the reuse of project outputs by the broader digital twin community. The project also aims to sustain the NERC Digital Twins senior stakeholder forum under the umbrella of the TWINE grouping of projects.