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Remote Sens. 2016, 8(1), 58; doi:10.3390/rs8010058

A Multi-Sensor Approach for Volcanic Ash Cloud Retrieval and Eruption Characterization: The 23 November 2013 Etna Lava Fountain

1
Istituto Nazionale di Geofisica e Vulcanologia (INGV), CNT, 00143 Rome, Italy
2
Department of Information Engineering, Electronics and Telecommunications (DIET), Sapienza University, 00184 Rome, Italy
3
Center of excellence CETEMPS, University of L’Aquila, 67100 L’Aquila, Italy
4
Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy
5
Istituto Nazionale di Geofisica e Vulcanologia, OE, 95123 Catania, Italy
6
National Centre for Earth Observation, Atmospheric, Oceanic and Planetary Physics, University of Oxford, Parks Road, OX1 3PU Oxford, UK
7
COMET, Atmospheric, Oceanic and Planetary Physics, University of Oxford, Parks Road, OX1 3PU Oxford, UK
8
National Department of Civil Protection (DPC), 00189 Rome, Italy
Current address: Institute of Atmospheric Sciences and Climate (ISAC) of the National Research Council of Italy (CNR), 00133 Rome, Italy
*
Author to whom correspondence should be addressed.
Academic Editors: Zhong Lu and Prasad S. Thenkabail
Received: 6 September 2015 / Revised: 18 December 2015 / Accepted: 30 December 2015 / Published: 12 January 2016
(This article belongs to the Special Issue Volcano Remote Sensing)

Abstract

Volcanic activity is observed worldwide with a variety of ground and space-based remote sensing instruments, each with advantages and drawbacks. No single system can give a comprehensive description of eruptive activity, and so, a multi-sensor approach is required. This work integrates infrared and microwave volcanic ash retrievals obtained from the geostationary Meteosat Second Generation (MSG)-Spinning Enhanced Visible and Infrared Imager (SEVIRI), the polar-orbiting Aqua-MODIS and ground-based weather radar. The expected outcomes are improvements in satellite volcanic ash cloud retrieval (altitude, mass, aerosol optical depth and effective radius), the generation of new satellite products (ash concentration and particle number density in the thermal infrared) and better characterization of volcanic eruptions (plume altitude, total ash mass erupted and particle number density from thermal infrared to microwave). This approach is the core of the multi-platform volcanic ash cloud estimation procedure being developed within the European FP7-APhoRISM project. The Mt. Etna (Sicily, Italy) volcano lava fountaining event of 23 November 2013 was considered as a test case. The results of the integration show the presence of two volcanic cloud layers at different altitudes. The improvement of the volcanic ash cloud altitude leads to a mean difference between the SEVIRI ash mass estimations, before and after the integration, of about the 30%. Moreover, the percentage of the airborne “fine” ash retrieved from the satellite is estimated to be about 1%–2% of the total ash emitted during the eruption. Finally, all of the estimated parameters (volcanic ash cloud altitude, thickness and total mass) were also validated with ground-based visible camera measurements, HYSPLIT forward trajectories, Infrared Atmospheric Sounding Interferometer (IASI) satellite data and tephra deposits. View Full-Text
Keywords: volcanic ash retrieval; volcano monitoring; multi-sensor approach; Etna lava fountains; satellite and ground-based remote sensing volcanic ash retrieval; volcano monitoring; multi-sensor approach; Etna lava fountains; satellite and ground-based remote sensing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Corradini, S.; Montopoli, M.; Guerrieri, L.; Ricci, M.; Scollo, S.; Merucci, L.; Marzano, F.S.; Pugnaghi, S.; Prestifilippo, M.; Ventress, L.J.; Grainger, R.G.; Carboni, E.; Vulpiani, G.; Coltelli, M. A Multi-Sensor Approach for Volcanic Ash Cloud Retrieval and Eruption Characterization: The 23 November 2013 Etna Lava Fountain. Remote Sens. 2016, 8, 58.

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