A Data-Based Minimal Model of Episodic Inflation Events at Volcanoes

Space geodetic time series, be they ground-based or space-based, have increased in length and accuracy. These series can now mined for information on the qualitative dynamics of volcanic systems directly from surface deformation data. Here, we study three volcanoes: Akutan Okmok that are part Aleutian arc, Piton de la Fournaise Reunion Island. All continuously monitored by Global Positioning System (GPS) exhibit common stair step–shaped inflation cycles sometimes referred to as “episodic events”. Here seek characterize corresponding dynamical regime pressure build-up within their plumbing system. To do so, make use Multichannel Singular Spectrum Analysis (M-SSA), a data-adaptive, non-parametric analysis methodology allows 1) reliable detection extraction such patterns even when signal lies close to, below, data scatter; 2) relevant underlying without priori assumptions physical mechanisms. For our volcanoes, find resemble relaxation oscillations simple oscillator involves nonlinear dissipative mechanism. This finding provides important guidelines physics-based models episodic cycles. In fact, volcanoes share system composed several interconnected storage bodies. Guided M-SSA–inferred dynamics, formulate model two magma bodies connected conduit which viscosity fluid varies with temperature crystallization. We show possesses internal similar those oscillator. correspond repetitive events sharp variations rate transport account bodies, no need time-dependent flux into out also model’s number degrees freedom is consistent amount extracted M-SSA analysis. The approach presented here relies robust statistical constrain phenomenology system; it novel framework understanding systems.