Dualeh, EW orcid.org/0000-0003-2933-3039, Ebmeier, SK orcid.org/0000-0002-5454-2652, Wright, TJ et al. (6 more authors) (2023) Rapid pre-explosion increase in dome extrusion rate at La Soufrière, St. Vincent quantified from synthetic aperture radar backscatter. Earth and Planetary Science Letters, 603. 117980. ISSN 0012-821X
Abstract
The extrusion rate of a lava dome is a critical parameter for monitoring silicic eruptions and forecasting their development. Satellite radar backscatter can provide unique information about dome growth during a volcanic eruption when other datasets (e.g., optical, thermal, ground-based measurements, etc.) may be limited. Here, we present an approach for estimating volcanic topography from individual backscatter images. Using data from multiple SAR sensors we apply the method to the dome growth during the 2021 eruption at La Soufrière, St. Vincent. We measure an average extrusion rate of 1.8 m³s¯¹ between December 2020 and March 2021 before an acceleration in extrusion rate to 17.5 m³s¯¹ in the 2 days prior to the explosive eruption on 9 April 2021. We estimate a final dome volume of 19.4 million m³, extrapolated from the SAR sensors, with approximately 15% of the total extruded volume emplaced in the last 2 days. A possible explanation for the acceleration in extrusion rate could be the combined emptying of a conduit and reservoir of older material before the ascent of gas-rich magma in April 2021.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | volcano remote sensing; Synthetic Aperture Radar (SAR) backscatter; dome growth; La Soufrière; St. Vincent |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst of Geophysics and Tectonics (IGT) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 26 Jan 2023 16:40 |
Last Modified: | 26 Jan 2023 16:40 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.epsl.2022.117980 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:195632 |