Impacts of meteorological uncertainties on ozone pollution predictability estimated through meteorological and photochemical ensemble forecasts

Fuqing Zhang, Naifang Bei, John W. Nielsen-Gammon, Guohui Li, Renyi Zhang, Amy Stuart, Altug Aksoy

Research output: Contribution to journalArticlepeer-review

59 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article numberD04304
JournalJournal of Geophysical Research Atmospheres
Volume112
Issue number4
DOIs
StatePublished - Feb 27 2007

All Science Journal Classification (ASJC) codes

  • Geophysics
  • Forestry
  • Oceanography
  • Aquatic Science
  • Ecology
  • Water Science and Technology
  • Soil Science
  • Geochemistry and Petrology
  • Earth-Surface Processes
  • Atmospheric Science
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science
  • Palaeontology

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