1. Developing Digital Twins for Earth Systems: Purpose, Requisites, and Benefits
- Author
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Rao, Yuhan, Redmon, Rob, Dale, Kirstine, Haupt, Sue E., Hopkinson, Aaron, Bostrom, Ann, Boukabara, Sid, Geenen, Thomas, Hall, David M., Smith, Benjamin D., Niyogi, Dev, Ramaswamy, V., and Kihn, Eric A.
- Subjects
Physics - Physics and Society ,Physics - Atmospheric and Oceanic Physics ,Statistics - Applications - Abstract
The accelerated change in our planet due to human activities has led to grand societal challenges including health crises, intensified extreme weather events, food security, environmental injustice, etc. Digital twin systems combined with emerging technologies such as artificial intelligence and edge computing provide opportunities to support planning and decision-making to address these challenges. Digital twins for Earth systems (DT4ESs) are defined as the digital representation of the complex integrated Earth system including both natural processes and human activities. They have the potential to enable a diverse range of users to explore what-if scenarios across spatial and temporal scales to improve our understanding, prediction, mitigation, and adaptation to grand societal challenges. The 4th NOAA AI Workshop convened around 100 members who are developing or interested in participating in the development of DT4ES to discuss a shared community vision and path forward on fostering a future ecosystem of interoperable DT4ES. This paper summarizes the workshop discussions around DT4ES. We first defined the foundational features of a viable digital twins for Earth system that can be used to guide the development of various use cases of DT4ES. Finally, we made practical recommendations for the community on different aspects of collaboration in order to enable a future ecosystem of interoperable DT4ES, including equity-centered use case development, community-driven investigation of interoperability for DT4ES, trust-oriented co-development, and developing a community of practice., Comment: This whitepaper is an outcome of the 4th NOAA AI Workshop
- Published
- 2023