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Monitoring ash-laden plumes using geodetic remote sensing techniques

Hugues Brenot1, Riccardo Biondi2, Flavio Cannavò3, Samuel Nahmani4, Eric Pottiaux5, and Rohm Witold6

  • Affiliations: 1Royal Belgian Institute for Space Aeronomy (BIRA), Brussels, Belgium; 2International Centre for Environmental Monitoring (CIMA), Savona, Italy; 3National Institute of Geophysics and Volcanology -- Etna Observatory (INGV-OE), Catania, Italy; 4Paris Institute of Earth Physics (IPGP), France; 5Royal Observatory of Belgium (ROB), Brussels, Belgium; 6Wrocłav University of Environment and Life Sciences (WUELS), Poland

  • Presentation type: Poster

  • Presentation time: Thursday 16:30 - 18:30, Room Poster Hall

  • Poster Board Number: 96

  • Programme No: 3.12.22

  • Theme 3 > Session 12

Abstract

Climate changes affect all regions of Earth's neutral atmosphere, from the equator to the poles, driven primarily by human activities and volcanic eruptions. The rise in severe weather events and hazardous clouds from volcanic activity or industrial explosions poses serious threats to public health and can cause widespread damage. Additionally, both convective and volcanic clouds present significant risks to aviation safety. In this context, the aim of this work --- which is part of the Convective and Volcanic Cloud (CVC) sub-workgroup of the IAG Commission 4 on "Positioning and applications", section "Atmospheric remote sensing --- is to enhance the detection of hazardous atmospheric structures by analysing disruptions in GNSS radio wave signals received by ground stations or polar low Earth orbit (LEO) polar satellites (radio-occultation). Three benchmark campaigns/sites are considered to enhance risk detection, warnings, and mitigation strategies for extreme CVC events. This presentation focusses on two volcanoes: Etna (eruptions in 2015, 2018 and 2021) and Ruang (eruption in 2024). Results from GNSS techniques on the 3D structure and height of volcanic ash-laden plumes are obtained by integrating data from other remote sensing methods, including sensors on LEO and GEO (geostationary) satellites. Detecting and monitoring extreme clouds involves quantifying atmospheric refractivity and delay propagation of radio signal to identify anomalies relative to reference data. Developing tropospheric parameters from multi-GNSS data is crucial for reconstructing 3D structures through tomography and creating diagnostic tools based on slant delay observations, aiming to characterise the vertical profiles of CVCs.