Global monitoring of volcanic clouds: A Synergistic Approach Using GOES, Meteosat, and Himawari Geostationary Satellites

Volcanic eruptions are significant sources of atmospheric pollutants, releasing vast quantities of silicate ash and gases, particularly sulfur dioxide (SO₂), into the atmosphere. These emissions form complex volcanic clouds that pose immediate risks to aviation safety and public health and have profound long-term environmental implications. When SO₂ is injected into the stratosphere, it converts into sulfate aerosols that scatter solar radiation, altering the Earth's radiative balance and influencing global climate patterns.

Consequently, the continuous monitoring of volcanic activity is essential for both immediate hazard mitigation and long-term climate studies. To achieve a comprehensive global vision of volcanic activity and ensure the rapid detection of eruptive events, geostationary Earth orbit (GEO) satellites are indispensable. Unlike polar-orbiting platforms, GEO satellites provide high temporal resolution, enabling near real-time tracking of volcanic cloud dispersion. This work highlights the synergistic potential of geostationary satellites, utilizing the Advanced Baseline Imager (ABI) on the GOES series, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) and the new Flexible Combined Imager (FCI) on Meteosat, and the Advanced Himawari Imager (AHI) on Himawari. Machine Learning (ML) approaches are employed to process these diverse satellite datasets, extracting high-dimensional spectral and spatial features to robustly monitor volcanic clouds across various input imagery. The use of geostationary satellite data and ML approaches ensures global coverage and fast response capabilities, allowing for precise monitoring of volcanic cloud evolution worldwide.