June 2024 Spatial predictions on physically constrained domains: Applications to Arctic sea salinity data
Bora Jin, Amy H. Herring, David Dunson
Author Affiliations +
Ann. Appl. Stat. 18(2): 1596-1617 (June 2024). DOI: 10.1214/23-AOAS1850


In this paper we predict sea surface salinity (SSS) in the Arctic Ocean based on satellite measurements. SSS is a crucial indicator for ongoing changes in the Arctic Ocean and can offer important insights about climate change. We particularly focus on areas of water mistakenly flagged as ice by satellite algorithms. To remove bias in the retrieval of salinity near sea ice, the algorithms use conservative ice masks, which result in considerable loss of data. We aim to produce realistic SSS values for such regions to obtain more complete understanding about the SSS surface over the Arctic Ocean and benefit future applications that may require SSS measurements near edges of sea ice or coasts. We propose a class of scalable nonstationary processes that can handle large data from satellite products and complex geometries of the Arctic Ocean. Barrier overlap-removal acyclic directed graph GP (BORA-GP) constructs sparse directed acyclic graphs (DAGs) with neighbors conforming to barriers and boundaries, enabling characterization of dependence in constrained domains. The BORA-GP models produce more sensible SSS values in regions without satellite measurements and show improved performance in various constrained domains in simulation studies compared to state-of-the-art alternatives. An R package is available at https://github.com/jinbora0720/boraGP.

Funding Statement

This work was partially supported by the National Institute of Environmental Health Sciences through grants R01ES027498 and R01ES028804 and from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 856506).


The authors are grateful to the Editor, Associate Editor, and reviewers for their constructive comments that have helped to improve our manuscript.


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Bora Jin. Amy H. Herring. David Dunson. "Spatial predictions on physically constrained domains: Applications to Arctic sea salinity data." Ann. Appl. Stat. 18 (2) 1596 - 1617, June 2024. https://doi.org/10.1214/23-AOAS1850


Received: 1 October 2022; Revised: 1 November 2023; Published: June 2024
First available in Project Euclid: 5 April 2024

Digital Object Identifier: 10.1214/23-AOAS1850

Keywords: Arctic Ocean , barriers , directed acyclic graphs , sea surface salinity , SMAP , spatial statistics

Rights: Copyright © 2024 Institute of Mathematical Statistics


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Vol.18 • No. 2 • June 2024
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