Opportunities and Challenges for Digital Twins in Atmospheric and Climate Sciences Proceedings of a Workshop—in Brief (2023) / Chapter Skim
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Opportunities and Challenges for Digital Twins in Atmospheric and Climate Sciences: Proceedings of a Workshop - in Brief
Opportunities and Challenges for Digital Twins in Atmospheric and Climate Sciences: Proceedings of a Workshop - in Brief
Pages 1-13
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More realistic simulations at the global scale will inform a National Academies consensus study on could translate to information at the regional scale that research gaps and future directions to advance the better supports decision-making for climate adaptation mathematical, statistical, and computational foundations and mitigation through tight integration and interaction of digital twins in applications across science, medicine, with impact sector models. Now in the first phase (2021– engineering, and society.1 2024)
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Modigliani explained that Earth system digital twins Venkatramani Balaji, Schmidt Futures, the plenary require unprecedented simulation capabilities––for session's second speaker, presented a brief overview of example, ECMWF aspires to have a simulation on the the history of climate modeling, starting with a oneorder of 1–4 km at the global scale, which could enable dimensional model response to carbon dioxide doubling the modeling of small scales of sea ice transformation in 1967. This early work revealed that studying climate and the development of more accurate forecasts.
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Ruby Leung, Pacific Northwest National Laboratory, He suggested that ML offers systematic methods for moderated a discussion among the plenary speakers. She calibration and emulation in a formal mathematical way posed a question about what distinguishes a digital twin to achieve traceable model hierarchies.
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Transportation data Jean-François Lamarque, consultant and formerly of and social media data could also be integrated to enhance the National Center for Atmospheric Research's Climate the representation of building occupant behavior. He and Global Dynamics Laboratory, shared the definition of a digital twin, as used in the digital twin Wikipedia 7 The Internet of Things is the "networking capability that allows information to be sent to and received from objects and devices using the entry: "a high-fidelity model of the system, which can Internet" (Merriam-Webster)
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strength of the communication channel between the He stressed that no "digital twin for climate" exists, physical and digital representations, and the usefulness of but digital twin technology could be used to strengthen the digital twin for climate research. climate models; for example, systematic biases could be reduced via ML-driven calibration, new physicsGavin A
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Jablonowski encouraged investments that that although some things will not change much in the improve access to extreme-scale computing resources next 10 years, confidence is lacking in the accuracy of and broaden community engagement in the digital twin boundary force problems at that timescale. At the 20- endeavor.
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Phase 69 library, and he described the potential engines that consume energy and produce gases) require value of pretraining digital twins to regenerate missing detailed modeling to be operated more sustainably and detail in between sparsely stored checkpoints at short efficiently; better weather and climate models are also intervals.
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He summarized that because want to predict, use a Bayesian framework to infer the physical engineering systems and Earth systems interact uncertainties of the models, and equip the predictions with each other, their corresponding digital twins should with uncertainty systematically and rationally. Bayesian work in conjunction to best reflect the behaviors of these model selection enables one to attribute probabilities physical systems and subsequently optimize operations that different models are consistent with the data in aided by these digital twins toward sustainability.
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Hub's10 initial brief presentations from experts in polar climate, AI modeling and forecasting capabilities provide water-level algorithms, ocean science, carbon cycle science, and information at the scale where people live. A network applied mathematics; they discussed how digital twins of ~65 sensors that are distributed and interconnected could be useful in their research areas and where digital wirelessly along the coast around critical infrastructure twins could have the greatest future impacts.
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He emphasized that the fundamental success understood, quantified, and communicated. Anandkumar of digital twins depends on their ability to compensate responded that ML has great potential, although it is for the modeling error that causes incompatibility still an emerging approach; with its increased speed, of numerical weather prediction models and climate thousands of ensemble members could be created -- prediction models.
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In response to with local community knowledge is a key part of model a question from Ye about unique approaches to visualize development, and social scientists could facilitate that uncertainty, McGovern described an initiative where process. Di Lorenzo urged researchers to include social those creating visualizations are conducting interviews dimensions in digital twin platforms, as thinking only with end users to understand how uncertainty affects about the physical world is an obsolete approach.
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Asch described work in the Philippines to model the spread of stressed that transparency and reproducibility are key viral epidemics. He noted that creating dashboards is an to increasing digital twin acceptance, and users should effective way for end users to interact with a complicated be able to follow a digital twin's reasoning as well as problem; however, more work remains to model social understand how to use and exploit it.
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COMMITTEE ON FOUNDATIONAL RESEARCH GAPS AND FUTURE DIRECTIONS FOR DIGITAL TWINS Karen Willcox (Chair) , Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin; Derek Bingham, Simon Fraser University; Caroline Chung, MD Anderson Cancer Center; Julianne Chung, Emory University; Carolina Cruz-Neira, University of Central Florida; Conrad J
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