A Multivariate Space-Time Dynamic Model for Characterizing the Atmospheric Impacts Following the Mt Pinatubo Eruptio

Robert Garrett, Lyndsay Shand, J. Gabriel Huerta
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Abstract

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 the 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 climate 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 caste 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 following the Mt. Pinatubo eruption with reanalysis data from MERRA-2 and highlight when such model is advantageous over univariate models.
表征皮纳图博火山爆发后大气影响的多变量时空动态模型
1991 年 6 月皮纳图博火山爆发导致大气中的硫酸气溶胶大量增加,吸收辐射并导致全球地表和平流层温度的变化。这种规模的火山爆发是平流层气溶胶注入的自然类似物,而平流层气溶胶注入是为应对气候变暖而提出的太阳辐射修正方法。这种事件的影响是多方面的,而且因地区而异。我们的目标是描述皮纳图博火山爆发后气候影响的多元性和动态性。我们建立了一个多变量时空动态线性模型,以全面了解时空变化的影响。具体来说,空间变化是通过一组灵活的基函数来建模的,而基函数的系数是通过向量自回归(VAR)结构允许随时间变化的。这种新型模型采用动态线性模型 (DLM) 框架,并通过定制的 MCMC 方法进行估计。我们利用 MERRA-2 的再分析数据演示了该模型如何量化皮纳图博火山爆发后关键大气参数之间的关系,并强调了这种模型何时比单变量模型更具优势。
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