A Multivariate Space‐Time Dynamic Model for Characterizing the Atmospheric Impacts Following the Mt. Pinatubo Eruption

Garrett, Robert C.; Shand, Lyndsay; Huerta, Jose Gabriel

doi:10.1002/env.70030

A Multivariate Space‐Time Dynamic Model for Characterizing the Atmospheric Impacts Following the Mt. Pinatubo Eruption

Journal Article · Tue Aug 12 00:00:00 EDT 2025 · Environmetrics

DOI:https://doi.org/10.1002/env.70030· OSTI ID:2587539

^[1]; Shand, Lyndsay ^[1]; ^[2]

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of Illinois at Urbana-Champaign, IL (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of New Mexico, Albuquerque, NM (United States)

The June 1991 Mt. Pinatubo eruption resulted in a massive increase of sulfate aerosols in the atmosphere, absorbing radiation and leading to global changes in surface and stratospheric temperatures. A volcanic eruption of this magnitude serves as a natural analog for stratospheric aerosol injection, a proposed solar radiation modification method to combat a warming climate. The impacts of such an event are multifaceted and region-specific. Our goal is to characterize the multivariate and dynamic nature of the atmospheric impacts following the Mt. Pinatubo eruption. We developed a multivariate space-time dynamic linear model to understand the full extent of the spatially- and temporally-varying impacts. Specifically, spatial variation is modeled using a flexible set of basis functions for which the basis coefficients are allowed to vary in time through a vector autoregressive (VAR) structure. This novel model is cast in a Dynamic Linear Model (DLM) framework and estimated via a customized MCMC approach. We demonstrate how the model quantifies the relationships between key atmospheric parameters prior to and following the Mt. Pinatubo eruption with reanalysis data from MERRA-2 and highlight when such a model is advantageous over univariate models.

View Accepted Manuscript (DOE)

Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: NA0003525

OSTI ID:: 2587539

Report Number(s):: SAND--2025-11009J; 1754793

Journal Information:: Environmetrics, Journal Name: Environmetrics Journal Issue: 6 Vol. 36; ISSN 1099-095X; ISSN 1180-4009

Publisher:: WileyCopyright Statement

Country of Publication:: United States

Language:: English

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