Breaking the satellite trade-off: AI creates near real-time 3D cloud maps

Clouds play a critical role in Earth’s climate system and are a major source of uncertainty in climate projections. The vertical distribution of ice and water particles in clouds impacts their radiative properties and with that Earth’s energy balance. Recent research also showed that the internal properties of clouds in tropical cyclones influence how storms intensify. Yet satellites face a fundamental trade-off: systems that measure vertical structure lack continuous coverage, while those with continuous coverage cannot see inside clouds.

Now, research conducted through the Earth Systems Lab research programme, funded through the ESA Φ-lab and involving former ESA research fellow, Dr Anna Jungbluth, has developed a breakthrough machine learning framework that translates two-dimensional geostationary satellite imagery into detailed three-dimensional cloud maps in near real-time. Published in November 2025, the study demonstrates for the first time the ability to create global instantaneous 3D cloud reconstructions, with particular success in mapping the internal structure of intense tropical cyclones.

Read the full article on www.climate.esa.int.

Photo courtesy of Unsplash/Zbynek Burival