Bayesian Inference of Spatio-Temporal Changes of Arctic Sea Ice

Bohai Zhang; Noel Cressie

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arXiv · 2003.06843

Bayesian Inference of Spatio-Temporal Changes of Arctic Sea Ice

Bohai Zhang·Noel Cressie

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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.

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BibTeX RIS

Bohai Zhang, Noel Cressie. 2020-03-15. Bayesian Inference of Spatio-Temporal Changes of Arctic Sea Ice. https://arxiv.org/abs/2003.06843

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