Advancing Volcanic Crisis Management through Satellite Data Assimilation in FALL3D within the ESA GET-it Digital Twin Framework

Hernandez, E.¹, Folch, A¹, Mingari, L.¹, Stramondo, S.², Trasatti, E.², Ganci, G.², Corradini, S.², Gonçalves, P.³, Brenot, H.⁴, Pacini, F. ³

• Geociencias Barcelona (GEO3BCN), CSIC, Barcelona, Spain
• Instituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione di Bologna, Bologna, Italy
• Terradue, Roma, Italy
• Royal Belgian Institute for Space Aeronomy (BIRA), Brussels, Belgium

The ESA Geohazards Early Digital Twin Component (GET-it) project aims to deliver interactive, scenario-based tools for decision-making during geohazard crises. Within this framework, we present recent advancements in volcanic ash and gas dispersion modeling through the integration of satellite data assimilation into the FALL3D model. The main innovation consists of assimilating SEVIRI-derived SO₂ mass loading during the 2021 Cumbre Vieja eruption (La Palma) and volcanic ash during the 2018 Mount Etna eruption. These enhancements significantly improve the accuracy of quantitative forecasts of volcanic clouds, which are critical for aviation safety and public health.

The assimilation system implemented in FALL3D is based on the Local Ensemble Transform Kalman Filter (LETKF), an ensemble-based technique with localization designed to run efficiently on parallel computing platforms. The observation operator maps the model state to satellite retrievals, enabling sequential assimilation cycles. After each cycle, the corrected 3D concentration field initializes a new forecast, reducing uncertainty in cloud position and concentration. For La Palma, three assimilation steps were performed at 3-hour intervals using SEVIRI SO₂ retrievals, improving consistency with independent observations of cloud height.

To enable operational use, these simulations have been deployed on the Geohazards Thematic Exploitation Platform (TEP) by Terradue. The implementation leverages Common Workflow Language (CWL) workflows and Docker containers, ensuring reproducibility and scalability. The platform provides interactive visualization of eruption scenarios, including maps and time series, and allows users to modify key eruption source parameters (e.g., column height, intensity) through predefined scenarios (low, medium, high).

This work demonstrates the potential of combining Earth observation data with advanced numerical modeling in a cloud-based environment to deliver actionable information for crisis management. Future developments will focus on extending these capabilities to other geohazards and enhancing real-time operational readiness.