MAS-DT

国家海洋学中心（NOC）为英国气象局和皇家海军运营海洋滑翔机，收集地球观测数据，驱动海洋预报模型。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。该方法的延伸是优化海洋滑翔机观测，以最大限度地提高其对海洋模型的影响，从而利用基于IMFe最近建议的可互操作数字孪生（DT）概念进行天气预报。我们提出了一个结合地球观测数据、水下海洋滑翔机数据和实际海洋模型的数字孪生模型。由此产生的新的四维图像将通过用户界面（UI）呈现，使科学家能够确定可能产生最大影响的潜在观测结果，并允许定义实现这些观测结果的操作目标。这些目标将提供给一个任务规划服务，该服务将考虑滑翔机的能力（如电池寿命和速度）来重新分配滑翔机的任务，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的反馈循环。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所收集的观测值及其对海洋预报的影响最大化。反过来，这将使这些公共资助的海洋观测的社会价值最大化。虽然该项目将围绕气象局的操作组装和演示数字孪生，但该DT将是一个通用框架，将支持不同模型的即插即用互操作性和自主引擎，以驱动观测以优化模型。预计研究结果的适用性将扩展到船舶自主系统的试航操作，包括NERC研究社区的广泛车辆操作。这项工作将建立在环境数字孪生（IMFe）信息管理框架的基础上，并直接促进其进一步发展，通过实践社区方法，将最佳实践纳入社区产出（如图灵方法和TWINE社区），重点关注现有组件之间的接口。这将使更广泛的数字孪生社区能够重用项目产出。该项目还旨在在TWINE项目分组的保护下维持NERC数字孪生高级利益相关者论坛。

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.