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Bayesian inference of spatio-temporal changes of arctic sea ice

Journal Article


Abstract


  • Arctic sea ice extent has drawn increasing interest and alarm from geoscientists, owing to its rapid decline. In this article, we propose a Bayesian spatio-temporal hierarchical statistical model for binary Arctic sea ice data over two decades, where a latent dynamic spatio-temporal Gaussian process is used to model the data-dependence through a logit link function. Our ultimate goal is to perform inference on the dynamic spatial behavior of Arctic sea ice over a period of two decades. Physically motivated covariates are assessed using autologistic diagnostics. Our Bayesian spatio-temporal model shows how parameter uncertainty in such a complex hierarchical model can influence spatio-temporal prediction. The posterior distributions of new summary statistics are proposed to detect the changing patterns of Arctic sea ice over two decades since 1997.

Publication Date


  • 2020

Citation


  • Zhang, B., & Cressie, N. (2020). Bayesian inference of spatio-temporal changes of arctic sea ice. Bayesian Analysis, 15(2), 605-631. doi:10.1214/20-BA1209

Scopus Eid


  • 2-s2.0-85086443336

Start Page


  • 605

End Page


  • 631

Volume


  • 15

Issue


  • 2

Abstract


  • Arctic sea ice extent has drawn increasing interest and alarm from geoscientists, owing to its rapid decline. In this article, we propose a Bayesian spatio-temporal hierarchical statistical model for binary Arctic sea ice data over two decades, where a latent dynamic spatio-temporal Gaussian process is used to model the data-dependence through a logit link function. Our ultimate goal is to perform inference on the dynamic spatial behavior of Arctic sea ice over a period of two decades. Physically motivated covariates are assessed using autologistic diagnostics. Our Bayesian spatio-temporal model shows how parameter uncertainty in such a complex hierarchical model can influence spatio-temporal prediction. The posterior distributions of new summary statistics are proposed to detect the changing patterns of Arctic sea ice over two decades since 1997.

Publication Date


  • 2020

Citation


  • Zhang, B., & Cressie, N. (2020). Bayesian inference of spatio-temporal changes of arctic sea ice. Bayesian Analysis, 15(2), 605-631. doi:10.1214/20-BA1209

Scopus Eid


  • 2-s2.0-85086443336

Start Page


  • 605

End Page


  • 631

Volume


  • 15

Issue


  • 2