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Improved space-time forecasting of next day ozone concentrations in the eastern U.S.

Sahu, Sujit K., Yip, Stan and Holland, David (2009) Improved space-time forecasting of next day ozone concentrations in the eastern U.S. Atmospheric Environment, 43, (3), pp. 494-501. (doi:10.1016/j.atmosenv.2008.10.028).

Record type: Article


There is an urgent need to provide accurate air quality information and forecasts to the general public and environmental health decision-makers. This paper develops a hierarchical space–time model for daily 8-h maximum ozone concentration (O3) data covering much of the eastern United States. The model combines observed data and forecast output from a computer simulation model known as the Eta Community Multi-scale Air Quality (CMAQ) forecast model in a very flexible, yet computationally fast way, so that the next day forecasts can be computed in real-time operational mode. The model adjusts for spatio-temporal biases in the Eta CMAQ forecasts and avoids a change of support problem often encountered in data fusion settings where real data have been observed at point level monitoring sites, but the forecasts from the computer model are provided at grid cell levels. The model is validated with a large amount of set-aside data and is shown to provide much improved forecasts of daily O3 concentrations in the eastern United States

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Published date: January 2009
Keywords: bayesian modeling, data fusion, hierarchical model, markov chain monte carlo, spatial interpolation
Organisations: Statistics


Local EPrints ID: 147699
ISSN: 1352-2310
PURE UUID: a254027b-807a-4ce0-9275-b7bb9303c8e7
ORCID for Sujit K. Sahu: ORCID iD

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Date deposited: 26 Apr 2010 12:14
Last modified: 18 Jul 2017 19:33

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Author: Sujit K. Sahu ORCID iD
Author: Stan Yip
Author: David Holland

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