Working towards a Digital Twin of Earth

In the coming decades, population growth and human activities are expected to amplify the current pressures on critical resources such as fresh water and food, intensify the stress on land and marine ecosystems, as well as increase environmental pollution and its impacts on health and biodiversity.

These threats, comprising rising sea levels, increasing ocean acidification and more intense extreme events like floods and heatwaves, will need to be closely monitored, especially for our most vulnerable populations.

Responding to these challenges, ESA came together at the 2020 edition of Φ-week to discuss how Earth observation can contribute to the creation of a digital twin of Earth – a dynamic, digital replica of our planet which accurately mimics Earth’s behaviour.

Constantly fed with Earth observation data, combined with in situ measurements and artificial intelligence, Digital Twin Earth will help visualise and forecast natural and human activity on the planet. The model will be able to monitor the health of the planet, perform simulations of Earth’s interconnected system with human behaviour, and help support European environmental policies.

In September 2020, ESA launched several Digital Twin Earth Precursor Activities to explore some of the main scientific and technical challenges in building a digital twin of Earth. These activities included: Forest, Hydrology, Antarctica, Food Systems, Ocean and Climate Hot Spots.

Each activity addressed a different scientific, technical and operational challenge regarding Digital Twin Earth including the role of artificial intelligence and consistent data, stakeholder engagement scientific credibility and role of sectorial models and Information and Communication Technology (ITC) infrastructure.

At this year’s Φ-week, experts from the community came forward with the results of the activities over the last year.

Digital Twin Antarctica

Antarctica is a major reservoir of freshwater in the word, with a huge potential to contribute to sea level rise in the future. Current ice sheet models present major differences and deviations among models, as well as strong variability in unstable areas.

Therefore, a digital twin of Antarctica is necessary. Noel Gourmelen, from the University of Edinburgh commented, “By harnessing satellite observations, numerical simulations, and Artificial Intelligence, we have built a twin of the Antarctic ice sheet system, its hydrology, surrounding ocean, atmosphere, and biosphere. We have used the Antarctic twin to track the whereabouts of melt water on and under the ice sheet, and to explore how fringing ice shelves melt under various hydrology scenarios.”

Digital Twin Food Systems

The Food Systems digital twin simulates agricultural activities and interactions within ecosystems on a daily basis. Different models can be run separately for each simulation unit, depending on crop, water and irrigation management system.  

Chandra Taposea, from CGI IT UK Lt, said, “Digital Twin Earths and the scope we are trying to achieve is vital in helping us reach the next step in sense-making and decision-making, and be able to help both individual users and large-scale policy makers. Our Food Systems Digital Twin has managed to integrate models from different domains, looking at how extreme precipitation would affect global crop models, but not without its trials and tribulations.”

Digital Twin Hydrology

Luca Brocca, from the National Research Council, Italy, explains what the Hydrology Digital Twin entails, “In the ESA Digital Twin Earth Hydrology project, we have developed a 4D reconstruction of dynamic hydrology at unprecedented resolution through the integration of Earth observation and an advanced modelling system. The DTE Hydrology Prototype has been used for water resources management and for identifying locations and times of risk for landslides and flooding in the Po River Basin, in northern Italy.”

Digital Twin Climate Impacts

The Climate Impacts Digital Twin will enable decision makers, without expert technical knowledge, to generate and visualise, in real-time, decision-relevant information related to regionalised impacts of climate change.

Robert Parker, from the University of Leicester, said, “Our Climate Impact Explorer Digital Twin, initially focused on African drought, utilises an innovative combination of Earth observation, environmental modelling and Machine Learning to bring enhanced decision support capabilities directly to our stakeholders.

“By emulating these complex models and deploying them as fast and simple cloud-based tools, our prototype helps democratise access to these expert systems, giving stakeholders the capability to explore potential climate-driven drought responses.”

Digital Twin Forest

Matti Motus, Principal Scientist at VTT, explains how the Forest Digital Twin works: “This digital twin will be a specialised Digital Twin of Earth, providing a reconstruction of the forest system at levels of detail not possible with generic land surface models. Satellite-based Earth observation, especially the high-quality Copernicus Sentinel data, allows us to get unique and uniform information for all forests of the globe.

“Translating this into understanding on forest structure and to drive models of forest functioning requires local measurements, which are far more scattered and heterogeneous. In the precursor project, we have learned how to overcome these obstacles and provide growth and carbon balance predictions for different forests in Europe. We know now that we have the basic tools and the computing power to build a fully functioning digital twin of forests. It has been a very exciting, yet demanding journey, especially considering that it was fully implemented during the Covid-related restrictions.”

Digital Twin Ocean

This Digital Twin Ocean will focus on exploring the potential of artificial intelligence to learn directly from its data, from the past and the behaviour of the Earth system to predict the future to forecast oceanic events.

Betrand Chapron, from IFREMER, said, “The Digital Twin Ocean project addresses two very distinct phenomena in two very contrasting ocean basins: machine heatwaves in the Mediterranean Sea, and sea ice dynamics to help assess the Arctic amplification. Put simply, two strategies were followed.

“The first was the data-driven approach, where data augmented by regularly sampled numerical operational model assimilating data, are used to drive capabilities to visualise and analyse the recurrences of the ocean-atmosphere dynamical systems, and the model-driven approach, where very high numerical simulations, augmented by irregularly sampled data, are used to assess the large scales and long-term consequences of small scales.”