
Analysis of regional meteorology and surface ozone during the TexAQS II field program and an evaluation of the NMM‐CMAQ and WRF‐Chem air quality models
Author(s) -
Wilczak James M.,
Djalalova Irina,
McKeen Stuart,
Bianco Laura,
Bao JianWen,
Grell Georg,
Peckham Steven,
Mathur Rohit,
McQueen Jeff,
Lee Pius
Publication year - 2009
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 - 10.1029/2008jd011675
Subject(s) - cmaq , weather research and forecasting model , ozone , air quality index , environmental science , mesoscale meteorology , atmospheric sciences , climatology , meteorology , geography , geology
This study examines meteorological conditions associated with regional surface ozone using data collected during the summer Second Texas Air Quality Experiment, and the ability of the Nonhydrostatic Mesoscale Model–Community Multi‐scale Air Quality Model (NMM‐CMAQ) and the Weather Research and Forecast (WRF) model coupled with Chemistry (WRF‐Chem) models to simulate the observed meteorology and surface ozone. The surface ozone data consist of 118 sites that are part of the U.S. Environmental Protection Agency Aerometric Information Retrieval Now (AIRNow) network, while the meteorological data came from a network of eleven 915‐MHz wind profilers with RASS temperatures and supporting surface meteorological stations. High and low 8‐h maximum ozone occurrences most frequently develop as regional events, with similar ozone concentration patterns across all of east Texas, allowing for a separate analysis of high‐ and low‐ozone day conditions. The ability of the NMM‐CMAQ and WRF‐Chem models to simulate the meteorologically distinct high‐ and low‐ozone events is analyzed. Histograms of surface ozone show that both the NMM‐CMAQ and WRF‐Chem models underpredict the full range found in the observations. For low ozone values, the analysis indicates that the models have a positive bias because of too large of an ozone inflow boundary condition value over the Gulf of Mexico. In contrast, the models have a negative bias for very high ozone values that occur mostly in Houston and Dallas, which suggests that the urban emissions and/or chemistry is misrepresented in the models.