Environment-aware digital twins: incorporating weather and climate information to support risk-based decision-making.

Kirstine I. Dale, Edward C. D. Pope, Aaron R. Hopkinson, Theo McCaie, Jason A. Lowe
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Abstract

Abstract Digital twins are a transformative technology that can significantly strengthen climate adaptation and mitigation decision-making. Through provision of dynamic, virtual representations of physical systems, making intelligent use of multidisciplinary data, and high-fidelity simulations they equip decision-makers with the information they need, when they need it, marking a step change in how we extract value from data and models. While digital twins are commonplace in some industrial sectors, they are an emerging concept in the environmental sciences and practical demonstrations are limited, partly due to the challenges of representing complex environmental systems. Collaboration on challenges of mutual interest will unlock digital twins’ potential. To bridge the current gap between digital twins for industrial sectors and those of the environment, we identify the need for “environment aware” digital twins (EA-DT) that are a federation of digital twins of environmentally sensitive systems with weather, climate, and environmental information systems. As weather extremes become more frequent and severe, the importance of building weather, climate, and environmental information into digital twins of critical systems such as cities, ports, flood barriers, energy grids, and transport networks increases. Delivering societal benefits will also require significant advances in climate-related decision-making, which lags behind other applications. Progress relies on moving beyond heuristics, and driving advances in the decision sciences informed by new theoretical insights, machine learning and artificial intelligence. To support the use of EA-DTs, we propose a new ontology that stimulates thinking about application and best practice for decision-making so that we are resilient to the challenges of today’s weather and tomorrow’s climate.
环境意识数字孪生:结合天气和气候信息,支持基于风险的决策。
数字孪生是一种变革性技术,可以显著加强气候适应和减缓决策。通过提供物理系统的动态虚拟表示,智能地使用多学科数据和高保真度模拟,他们为决策者提供了他们需要的信息,当他们需要它时,标志着我们如何从数据和模型中提取价值的一个步骤变化。虽然数字孪生在一些工业部门很常见,但它们在环境科学中是一个新兴概念,实际演示有限,部分原因是代表复杂的环境系统存在挑战。在共同关心的挑战上进行合作将释放数字孪生的潜力。为了弥合目前工业部门的数字孪生与环境部门的数字孪生之间的差距,我们确定需要“环境意识”数字孪生(EA-DT),这是具有天气、气候和环境信息系统的环境敏感系统的数字孪生联盟。随着极端天气变得越来越频繁和严重,将天气、气候和环境信息构建到城市、港口、防洪屏障、能源网和交通网络等关键系统的数字孪生中的重要性日益增加。实现社会效益还需要在与气候相关的决策方面取得重大进展,而这方面的进展落后于其他应用。进步依赖于超越启发式,并通过新的理论见解、机器学习和人工智能推动决策科学的进步。为了支持ea - dt的使用,我们提出了一个新的本体,它可以激发对应用和决策最佳实践的思考,从而使我们能够适应今天天气和明天气候的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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