NASA climate records moved to Swiss AI supercomputer marks a significant step in protecting decades of critical Earth observation data while accelerating the next generation of artificial intelligence-powered climate forecasting. Researchers at ETH Zurich have copied approximately 100 petabytes of publicly available climate and environmental data, equivalent to nearly six billion files or around 20 million feature-length films from NASA to the Swiss National Supercomputing Centre (CSCS) in Lugano. The year-long effort aims to preserve invaluable climate datasets and train advanced AI models capable of delivering faster and more accurate forecasts for weather, climate change, and natural disasters.

The initiative also comes amid growing concerns over recent US federal funding cuts affecting climate science and Earth observation programs, although researchers emphasized that all the copied data remains publicly accessible.

Swiss Supercomputer to Power Next-Generation Climate AI

The transferred datasets contain decades of observations collected by NASA, covering essential components of Earth’s climate system, including:

• Greenhouse gas concentrations
• Cloud formations
• Rainfall and precipitation patterns
• Ice sheets and glaciers
• Atmospheric and ocean conditions

Researchers also plan to expand the archive by copying large datasets from the US National Oceanic and Atmospheric Administration (NOAA) in the future.

The data will be integrated with Alps, one of the world’s most powerful supercomputers housed at CSCS, enabling scientists to train advanced AI models capable of analyzing enormous climate datasets at unusual speeds.

NASA Climate Records Moved to Swiss AI Supercomputer Amid Funding Concerns

Although the project had scientific objectives from the outset, researchers acknowledged that uncertainty surrounding US climate science funding added urgency to the initiative.

• ETH professor and former NASA Chief Scientist Thomas Zurbuchen, who initiated the transfer, emphasized the enormous contribution NASA and NOAA have made to global Earth observation over several decades.
• Without these long-term measurement programs, scientists would know far less about climate change and planetary systems today.
• Since returning to office, US President Donald Trump has pursued significant reductions in federal funding for climate science and Earth observation programs.
• While researchers stressed that NASA has not restricted public access to its datasets, they noted that policy changes can happen quickly, making independent preservation efforts increasingly valuable.

Professor Reto Knutti, head of ETH’s Center for Climate Systems Modeling (C2SM), described the archive as an essential scientific resource, saying, “Data is the new gold.“

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AI Is Transforming Climate Forecasting

The project is expected to dramatically improve AI-driven weather and climate prediction.

Unlike traditional forecasting systems that rely on complex physical equations and require hours of computing time, modern AI foundation models can produce highly accurate forecasts up to 1,000 times faster.

According to Knutti, global weather forecasts that previously took hours can now be generated within about a minute, allowing scientists and emergency agencies to respond more rapidly to floods, storms, heatwaves, landslides, and other natural hazards.

Faster climate analysis will also benefit sectors such as agriculture, hydropower, disaster preparedness, and water resource management.

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Preserving Climate Knowledge for the Future

The integration of NASA’s extensive observational records with one of the world’s fastest supercomputers represents a major advancement for climate research. By combining decades of environmental data with cutting-edge AI and high-performance computing, researchers hope to identify climate patterns more efficiently and improve long-term forecasting accuracy.

As NASA climate records moved to Swiss AI supercomputer, the initiative demonstrates how international scientific collaboration can strengthen global climate resilience while ensuring that invaluable environmental datasets remain accessible for future generations of researchers.