MAS-DT

国家海洋学中心(NOC)为气象局和皇家海军运营海洋滑翔机，以收集地球观测数据，推动海洋预报模型。这些模型反过来又为业务天气预报提供了基础。目前，观测的目标是英国水域高影响区域的海洋模型网格箱。这一方法的一个扩展是优化海洋滑翔机观测，以最大限度地提高它们对海洋模型的影响，从而使用基于最近IMFe建议的可互操作的数字双胞胎(DT)的概念来进行天气预报。我们提出了一个结合了地球观测、次表层海洋滑翔机数据和业务海洋模型的演示器数字孪生。由此产生的新颖的四维图将通过用户界面(UI)呈现，使科学家能够确定可能产生最大影响的潜在观测，并允许定义实现这些观测的操作目标。这些目标将提供一个任务规划服务，该服务将考虑到滑翔机的能力(如电池寿命和速度)来重新安排滑翔机的任务，从而优化观测以获得最大的影响，在观测能力和海洋模型数据同化之间建立一个良性反馈循环。科学家、地球观测数据和滑翔机操作之间的这种近乎实时的反馈将使收集到的观测数据的价值最大化，并对海洋预报产生影响。这反过来将最大化这些公共资助的海洋观测的社会价值。虽然这个项目将围绕Met Office的操作组装和演示数字孪生兄弟，但这个DT将是一个通用框架，将支持不同模型和自主引擎的即插即用互操作性，以驱动观察以优化模型。预计结果的适用性将扩大到海洋自主系统的试点业务，包括包括NERC研究界在内的广泛的车辆业务。这项工作将在环境数字双胞胎信息管理框架(IMFe)的基础上开展，并直接促进这一框架的进一步发展，重点放在现有组成部分之间的接口上，采用实践社区的办法，并将最佳做法纳入社区产出(如图灵路和TWINE社区)。这将使更广泛的数字双胞胎社区能够重复使用项目产出。该项目还旨在在项目组合的保护伞下维持NERC数字双胞胎高级利益攸关方论坛。

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.