New Insights Into the Relationship Between Mass Eruption Rate and Volcanic Column Height Based On the IVESPA Data Set

Aubry, Thomas J.; Engwell, Samantha L.; Bonadonna, Costanza; Mastin, Larry G.; Carazzo, Guillaume; Van Eaton, Alexa R.; Jessop, David E.; Grainger, Roy G.; Scollo, Simona; Taylor, Isabelle A.; Jellinek, A. Mark; Schmidt, Anja; Biass, Sébastien; Gouhier, Mathieu. 2023 New Insights Into the Relationship Between Mass Eruption Rate and Volcanic Column Height Based On the IVESPA Data Set. Geophysical Research Letters, 50 (14), e2022GL102633. https://doi.org/10.1029/2022GL102633

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Official URL: http://dx.doi.org/10.1029/2022GL102633

Abstract/Summary

Rapid and simple estimation of the mass eruption rate (MER) from column height is essential for real-time volcanic hazard management and reconstruction of past explosive eruptions. Using 134 eruptive events from the new Independent Volcanic Eruption Source Parameter Archive (IVESPA, v1.0), we explore empirical MER-height relationships for four measures of column height: spreading level, sulfur dioxide height, and top height from direct observations and as reconstructed from deposits. These relationships show significant differences and highlight limitations of empirical models currently used in operational and research applications. The roles of atmospheric stratification, wind, and humidity remain challenging to detect across the wide range of eruptive conditions spanned in IVESPA, ultimately resulting in empirical relationships outperforming analytical models that account for atmospheric conditions. This finding highlights challenges in constraining the MER-height relation using heterogeneous observations and empirical models, which reinforces the need for improved eruption source parameter data sets and physics-based models.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1029/2022GL102633
ISSN:	0094-8276
Date made live:	31 Oct 2023 15:33 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/536196

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1029/2022GL102633

ISSN:

0094-8276

Date made live:

31 Oct 2023 15:33 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/536196