Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.
ESSI3.7 | Open-Source Digital Twins for the Earth
EDI
Open-Source Digital Twins for the Earth
Convener: Thomas Huang | Co-conveners: Simon Baillarin, Jacqueline Le Moigne
With increasing global temperature and growing human population, our home planet is suffering from extreme weather events such as intense rain, floods and droughts and related landslides, rising sea level, and an ever-increasing stress on freshwater availability. While there is a significant body of work on the sources and implications of climate change, analyzing and predicting the impacts and effects on water resources and localized flooding events is still non-trivial. Water resources science is multidisciplinary in nature, and it not only assesses the impact from our changing climate using measurements and modeling, but it also offers science-guided, data-driven decision support. While there have been many advances in the collection of observations, reflected in the fast increase in the Earth Observations archive, as well as in forecast modeling, there is no one measurement or method that can provide all the answers.

The idea behind Digital Twins of the Earth is to establish a virtual representation of a system that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making. Digital Twins for Earth System is an emerging concept that mirrors the Earth Science System to not only understand the current condition of our environment or climate, but also to be able to learn from the environment by analyzing changes and automatically acquire new data to improve its prediction and forecast (Fuller et al. 2020). This session welcomes presentations on current efforts, standards, open-source frameworks and enabling technologies.