Building a Better Forecast: Reformulating the Ensemble Kalman Filter for Improved Applications to Volcano Deformation.

ABSTRACT: As the volume of data collected at monitored volcanoes continues to expand, researchers will need quick, reliable, and automated methods of inverting those data into useful models of the underlying magma systems. Recently adapted from other fields for use in volcanology, the Ensemble Kalman Filter (EnKF) is one such inversion technique that has been used to produce several successful forecasts and hind-casts of volcanic unrest, correlating geodetic deformation with mechanical stresses around the magma reservoir. However, given the similarity in which changes to a reservoir's size and pressure are expressed at the surface, the filter can have trouble fully resolving magmatic conditions. In this study, we therefore test several different published variations of the EnKF workflow to produce a

SUBMITTER: Albright JA 

PROVIDER: S-EPMC10078308 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature