A hierarchical Bayesian model to estimate and forecast ozone through space and time

A Bayesian hierarchical regime switching model describing the spatial–temporal behavior of ozone (O3) within a domain covering Lake Michigan during spring–summer 1999 is developed. The model incorporates linkages between ozone and meteorology. It is specifically formulated to identify meteorological regimes conducive of high ozone levels and allow ozone behavior during these periods to be different from typical ozone behavior. The model is used to estimate or forecast spatial fields of O3 conditional on observed (or forecasted) meteorology including temperature, humidity, pressure, and wind speed and direction. The model is successful at forecasting the onset of periods of high ozone levels, but more work is needed to also accurately identify departures from these periods. r 2004 Elsevier Ltd. All rights reserved.