{"title":"Tracing the impacts of Mount Pinatubo eruption on global climate using spatially-varying changepoint detection","authors":"Samantha Shi-Jun, Lyndsay Shand, Bo Li","doi":"arxiv-2409.08908","DOIUrl":null,"url":null,"abstract":"Significant events such as volcanic eruptions can have global and long\nlasting impacts on climate. These global impacts, however, are not uniform\nacross space and time. Understanding how the Mt. Pinatubo eruption affects\nglobal and regional climate is of great interest for predicting impact on\nclimate due to similar events. We propose a Bayesian framework to\nsimultaneously detect and estimate spatially-varying temporal changepoints for\nregional climate impacts. Our approach takes into account the diffusing nature\nof the changes caused by the volcanic eruption and leverages spatial\ncorrelation. We illustrate our method on simulated datasets and compare it with\nan existing changepoint detection method. Finally, we apply our method on\nmonthly stratospheric aerosol optical depth and surface temperature data from\n1985 to 1995 to detect and estimate changepoints following the 1991 Mt.\nPinatubo eruption.","PeriodicalId":501425,"journal":{"name":"arXiv - STAT - Methodology","volume":"74 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Methodology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08908","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Significant events such as volcanic eruptions can have global and long
lasting impacts on climate. These global impacts, however, are not uniform
across space and time. Understanding how the Mt. Pinatubo eruption affects
global and regional climate is of great interest for predicting impact on
climate due to similar events. We propose a Bayesian framework to
simultaneously detect and estimate spatially-varying temporal changepoints for
regional climate impacts. Our approach takes into account the diffusing nature
of the changes caused by the volcanic eruption and leverages spatial
correlation. We illustrate our method on simulated datasets and compare it with
an existing changepoint detection method. Finally, we apply our method on
monthly stratospheric aerosol optical depth and surface temperature data from
1985 to 1995 to detect and estimate changepoints following the 1991 Mt.
Pinatubo eruption.