The National Academies hosts a workshop on the use of digital twins in atmospheric, climate, and sustainability science on February 1st and 2nd, 2023. Speakers and panelists include Mike Goodchild (University of California – Santa Barbara), Venkatramani Balaji (Schmidt Futures), Amy McGovern (University of Oklahoma), Anima Anandkumar (California Institute of Technology), and many others, to discuss the definition of a digital twin and its applications.
An emerging technology with the potential to revolutionize atmospheric, climate, and sustainability science, digital twins can be used to create global-scale interactive models of Earth, and enhance climate and weather predictions. Further, Digital Twins in Atmospheric, Climate, and Sustainability Science focuses on key technical challenges for developing and utilizing digital twins, including issues related to artificial intelligence (AI), machine learning (ML), big data, and data assimilation.
(Source: The National Academies of Sciences, Engineering, and Medicine)
ClimaTwin® is a leading climate risk intelligence solution for infrastructure assets and the built environment.
We empower infrastructure stakeholders to mitigate climate risks and assess adaptation actions across the total asset lifecycle. By connecting complex climate models and infrastructure digital twins, our solution enables engineers, owner-operators, and governments to aggregate, visualize, and analyze disparate datasets, revealing site-specific insights at a hyper-local scale. Benefits include 5-10x near-term returns and lifetime cost-avoidance by mitigating risks to systems, services, and societies.
To learn more about climate risk intelligence for your infrastructure assets, please visit www.climatwin.com today.
The National Academies hosts a workshop on the use of digital twins in atmospheric, climate, and sustainability science on February 1st and 2nd, 2023. Speakers and panelists include Mike Goodchild (University of California – Santa Barbara), Venkatramani Balaji (Schmidt Futures), Amy McGovern (University of Oklahoma), Anima Anandkumar (California Institute of Technology), and many others, to discuss the definition of a digital twin and its applications.
An emerging technology with the potential to revolutionize atmospheric, climate, and sustainability science, digital twins can be used to create global-scale interactive models of Earth, and enhance climate and weather predictions. Further, Digital Twins in Atmospheric, Climate, and Sustainability Science focuses on key technical challenges for developing and utilizing digital twins, including issues related to artificial intelligence (AI), machine learning (ML), big data, and data assimilation.
(Source: The National Academies of Sciences, Engineering, and Medicine)
ClimaTwin® is a leading climate risk intelligence solution for infrastructure assets and the built environment.
We empower infrastructure stakeholders to mitigate climate risks and assess adaptation actions across the total asset lifecycle. By connecting complex climate models and infrastructure digital twins, our solution enables engineers, owner-operators, and governments to aggregate, visualize, and analyze disparate datasets, revealing site-specific insights at a hyper-local scale. Benefits include 5-10x near-term returns and lifetime cost-avoidance by mitigating risks to systems, services, and societies.
To learn more about climate risk intelligence for your infrastructure assets, please visit www.climatwin.com today.
Continued from the previous news post: Weather and Climate Models Serve Destination Earth — Digital Twin of Earth…
Profiting from artificial intelligence
The authors also see great potential in artificial intelligence (AI). It can be used, for example, for data assimilation or the processing of observation data, the representation of uncertain physical processes in the models, and data compression. AI thus makes it possible to speed up the simulations and filter out the most important information from large amounts of data. Additionally, the researchers assume that the use of machine learning not only makes the calculations more efficient but also can help to describe the physical processes more accurately.
The scientists see their strategy paper as a starting point on the path to a digital twin of the Earth. Among the computer architectures available today and those expected in the near future, supercomputers based on graphics processing units (GPU) appear to be the most promising option. The researchers estimate that operating a digital twin at full scale would require a system with about 20,000 GPUs, consuming an estimated 20MW of power. For both economic and ecological reasons, such a computer should be operated at a location where CO2-​neutral generated electricity is available in sufficient quantities.
ClimaTwin™ empowers infrastructure stakeholders to mitigate climate risks and assess adaptation actions across the total asset lifecycle.
