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

Atmospheric Environment

Volumn 39, Issue 8, 2005, Pages 1373-1382

  McMillan, Nancy ^a   Bortnick, Steven M ^a   Irwin, Mark E ^b   Berliner, L Mark ^c  

^a BATTELLE MEMORIAL INSTITUTE   (United States)

^b HARVARD UNIVERSITY   (United States)

^c OHIO STATE UNIVERSITY   (United States)

Author keywords

Air pollution; Meteorology; Ozone; Space time models; Statistical model

Indexed keywords

ATMOSPHERIC HUMIDITY; ATMOSPHERIC PRESSURE; LAKES; MATHEMATICAL MODELS; METEOROLOGY; WEATHER FORECASTING;

LAKE MICHIGAN; SPATIAL-TEMPORAL BEHAVIOR; WIND SPEED;

OZONE;

OZONE;

AIR QUALITY; BAYESIAN ANALYSIS; FORECASTING METHOD; OZONE; SPATIOTEMPORAL ANALYSIS;

ARTICLE; ATMOSPHERIC PRESSURE; BAYES THEOREM; ENVIRONMENTAL TEMPERATURE; FORECASTING; HUMIDITY; LAKE; METEOROLOGY; PRIORITY JOURNAL; SPACE; SPRING; STATISTICAL MODEL; SUMMER; WIND;

GREAT LAKES; LAKE MICHIGAN; NORTH AMERICA; WESTERN HEMISPHERE; WORLD;

EID: 13844267702     PISSN: 13522310     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.atmosenv.2004.10.047     Document Type: Article

References (8)

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8. C.K. Wikle, L.M. Berliner, and R.F. Milliff Hierarchical Bayesian approach to boundary value problems with stochastic boundary conditions Monthly Weather Review 131 2003 1051 1062