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The concept of a digital twin of the Earth’s climate, leveraging geospatial data, climate sensors, and artificial intelligence (AI), presents a transformative potential for our understanding and management of the planet’s climate system. This digital twin, a high-fidelity virtual model of Earth’s climate, could revolutionize our approach to environmental stewardship, disaster response, and climate resilience.
The integration of AI-driven modeling and simulation has already shown promise in enhancing federal responses to crises…
Integrating geospatial data and climate sensors into a digital twin framework would enable unprecedented precision in climate monitoring. By synthesizing real-time data from a global network of sensors, satellites, and other observational technologies, we could achieve a granular understanding of climate dynamics at both macro and micro levels. This would enhance our ability to model current climate conditions and improve the accuracy of predictive models. As seen through the inclusion of human systems and biogeochemical processes, the evolution of climate models underscores the potential for such a digital twin to incorporate complex interactions within the Earth system.
Artificial intelligence stands to play a pivotal role in this endeavor, offering the computational prowess needed to process vast datasets and identify patterns that would be imperceptible to human analysts. AI’s machine learning and predictive analytics capacity could transform raw data into actionable insights, enabling more effective climate interventions and policy decisions. The integration of AI-driven modeling and simulation has already shown promise in enhancing federal responses to crises, suggesting its applicability to managing climate-related disasters.
“An AI-driven supercomputer dubbed Earth’s ‘digital twin’ could help us avoid the worst impacts of climate catastrophes headed our way.”
Scientists have created a “digital twin” of our planet that can be used to predict weather far faster than traditional services. The technology could help prevent some of the catastrophic impacts of disasters such as typhoons and flooding. The intensive data-crunching system could also give us a more detailed view of the future effects of climate change and reveal clues about how to mitigate them. The system is built by Nvidia, a multinational company that builds graphics processing units (GPUs) and electronic circuits that can carry out high-speed mathematical equations that enable activities such as machine learning, a type of artificial intelligence (AI).
The platform, called Earth-2, contains a suite of machine learning technologies developed by Nvidia, all of it driven by supercomputers to provide the immense processing power needed to do the job. Combined, these create “a virtual replica of a physical object or system, in this case, Earth’s climate,” Dion Harris, head of data center product marketing at Nvidia, told Live Science. The system takes the form of an interactive interface that runs simulations of weather and climate across the planet, allowing users to set different parameters and simulate weather in different locations at a highly detailed 1.2-mile (2 kilometers) scale.
The AI technology has been trained on global datasets that provide hourly estimates of land, atmospheric, and ocean climate variables. This system “synthesizes hundreds of observations and reconstructs Earth’s weather and climate over the last 50 years or so,” Harris said. This can make the difference between life and death in places like Taiwan, where frequent typhoons are catastrophic.
“Artificial intelligence has the power to extract valuable sustainability insights at scale from the torrent of data captured by an expanding constellation of Earth observation satellites.”
From a tool that distinguishes methane leaks caused by pipeline leaks from those associated with livestock herds to software that tracks changes in every individual tree to monitor changing levels of carbon storage in the forests of the Congo Basin, artificial intelligence (AI) is already being employed to turn the vast streams of raw data produced by 1,200-plus Earth observation (EO) satellites circling our planet into actionable insights that can help achieve climate goals.
“Dramatic improvements in advanced sensor resolution allow us to make new types of measurements at scale from space,” says Brett Loubert, principal at Deloitte Space and a contributor to a briefing paper co-authored by the World Economic Forum and Deloitte that explores the AI’s potential to extract insights from EO that can be used to catalyze progress on a wide array of climate action and sustainability priorities. “Moreover, with many more EO satellites expected to launch in coming years, the volume of data—already in the hundreds of terabytes— seems highly likely to grow in the years ahead,” he says.
There is no practical way for humans to analyze this gushing data stream manually and mine useful insights. That’s why geospatial analysts and data scientists have long relied on AI and machine learning tools to sift EO data for answers to complex questions.
“Until recently, only government agencies, academics, and non-profit organizations had access to the resources needed to run these analyses and extract valuable insights,” says Nes Parker, who leads Sustainability, Climate, and Equity for Deloitte’s Government & Public Services Practice. “But now, advances in AI modeling have converged with low-cost, high-performance computing to make it feasible for a much broader array of public and private sector actors to apply AI to make sense of EO data.”
A digital twin of the Earth’s climate could serve as a sandbox for testing geoengineering scenarios and climate interventions in a controlled virtual environment. This would allow scientists and policymakers to evaluate various strategies’ potential impacts and unintended consequences before their real-world implementation. Given geoengineering’s complexities and ethical considerations, such a tool could prove invaluable in guiding responsible decision-making.
The potential applications of a digital twin extend beyond scientific research and policy formulation. For instance, it could enhance disaster preparedness and response by providing real-time, scenario-based simulations of extreme weather events, thereby improving the effectiveness of emergency planning and resource allocation. Additionally, it could support efforts to mitigate climate change by modeling the outcomes of different carbon reduction strategies, informing both global negotiations and local sustainability initiatives.
Realizing the full potential of a digital twin of the Earth’s climate will require overcoming significant technical, financial, and governance challenges. These include ensuring the interoperability of diverse data sources, scaling AI algorithms to process global datasets, and establishing international data sharing and privacy frameworks.
In contemplating the future of a digital twin of the Earth’s climate, one must consider the technological and scientific advancements it would entail and the broader societal implications. As we strive to harness the power of digital and AI technologies for climate monitoring and intervention, we must also navigate the ethical, security, and equity issues that accompany such a profound tool. The goal should be to leverage this technology to promote global collaboration, enhance resilience to climate impacts, and foster sustainable development for all.
Given the complexity of climate systems and the critical role of accurate data in shaping effective responses, how do you envision leveraging a digital twin of the Earth’s climate to address specific challenges or opportunities in your work or research?
For additional OODA Loop News Briefs and Original Analysis on this topic, go to OODA Loop | Digital Twins
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About the Author
Daniel Pereira is research director at OODA. He is a foresight strategist, creative technologist, and an information communication technology (ICT) and digital media researcher with 20+ years of experience directing public/private partnerships and strategic innovation initiatives.
Informing your decisions with actionable intelligence
Informing your decisions with actionable intelligence