Open AccessImpacts of meteorological uncertainties on ozone pollution predictability estimated through meteorological and photochemical ensemble forecasts
Author(s) -
Zhang Fuqing,
Bei Naifang,
NielsenGammon John W.,
Li Guohui,
Zhang Renyi,
Stuart Amy,
Aksoy Altug
Publication year - 2007
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2006jd007429
Subject(s) - cmaq , environmental science , mm5 , ozone , predictability , air quality index , mesoscale meteorology , meteorology , atmospheric sciences , climatology , geography , geology , physics , quantum mechanics
This study explores the sensitivity of ozone predictions from photochemical grid point simulations to small meteorological initial perturbations that are realistic in structure and evolution. Through both meteorological and photochemical ensemble forecasts with the Penn State/NCAR mesoscale model MM5 and the EPA Community Multiscale Air Quality (CMAQ) Model‐3, the 24‐hour ensemble mean of meteorological conditions and the ozone concentrations compared fairly well against the observations for a high‐ozone event that occurred on 30 August during the Texas Air Quality Study of 2000 (TexAQS2000). Moreover, it was also found that there were dramatic uncertainties in the ozone prediction in Houston and surrounding areas due to initial meteorological uncertainties for this event. The high uncertainties in the ozone prediction in Houston and surrounding areas due to small initial wind and temperature uncertainties clearly demonstrated the importance of accurate representation of meteorological conditions for the Houston ozone prediction and the need for probabilistic evaluation and forecasting for air pollution, especially those supported by regulating agencies.