Open Access
Translator Disclaimer
December 2010 A bivariate space–time downscaler under space and time misalignment
Veronica J. Berrocal, Alan E. Gelfand, David M. Holland
Ann. Appl. Stat. 4(4): 1942-1975 (December 2010). DOI: 10.1214/10-AOAS351

Abstract

Ozone and particulate matter, PM2.5, are co-pollutants that have long been associated with increased public health risks. Information on concentration levels for both pollutants comes from two sources: monitoring sites and output from complex numerical models that produce concentration surfaces over large spatial regions. In this paper, we offer a fully-model-based approach for fusing these two sources of information for the pair of co-pollutants which is computationally feasible over large spatial regions and long periods of time. Due to the association between concentration levels of the two environmental contaminants, it is expected that information regarding one will help to improve prediction of the other. Misalignment is an obvious issue since the monitoring networks for the two contaminants only partly intersect and because the collection rate for PM2.5 is typically less frequent than that for ozone.

Extending previous work in Berrocal, Gelfand and Holland (2010), we introduce a bivariate downscaler that provides a flexible class of bivariate space–time assimilation models. We discuss computational issues for model fitting and analyze a dataset for ozone and PM2.5 for the ozone season during year 2002. We show a modest improvement in predictive performance, not surprising in a setting where we can anticipate only a small gain.

Citation

Download Citation

Veronica J. Berrocal. Alan E. Gelfand. David M. Holland. "A bivariate space–time downscaler under space and time misalignment." Ann. Appl. Stat. 4 (4) 1942 - 1975, December 2010. https://doi.org/10.1214/10-AOAS351

Information

Published: December 2010
First available in Project Euclid: 4 January 2011

zbMATH: 1220.62148
MathSciNet: MR2829942
Digital Object Identifier: 10.1214/10-AOAS351

Keywords: Co-kriging , coregionalization , dynamic model , kriging , multivariate spatial process , spatially varying coefficients

Rights: Copyright © 2010 Institute of Mathematical Statistics

JOURNAL ARTICLE
34 PAGES


SHARE
Vol.4 • No. 4 • December 2010
Back to Top