A comprehensive evaluation of seasonal simulations of ozone in the northeastern US during summers of 2001–2005

Abstract

Abstract. Regional air quality simulations were conducted for summers [2001][2002][2003][2004][2005] in the eastern US and subjected to extensive evaluation using various ground and airborne measurements. A brief climate evaluation focused on transport by comparing modeled dominant map types with ones from reanalysis. Reasonable agreement was found for their frequency of occurrence and distinctness of circulation patterns. The two most frequent map types from reanalysis were the Bermuda High (22%) and passage of a Canadian cold frontal over the northeastern US (20%). The model captured their frequency of occurrence at 25% and 18% respectively. The simulated five average distributions of 1-h ozone (O 3 ) daily maxima using the Community Multiscale Air Quality (CMAQ) modeling system reproduced salient features in observations. This suggests that the ability of the regional climate model to depict transport processes accurately is critical for reasonable simulations of surface O 3 . Comparison of mean bias, root mean square error, and index of agreement for CMAQ summer surface 8-h O 3 daily maxima and observations showed −0.6±14 nmol/mol, 14 nmol/mol, and 71% respectively. CMAQ performed best in moderately polluted conditions and less satisfactorily in highly polluted ones. This highlights the common problem of overestimating/underestimating lower/higher modeled O 3 levels. Diagnostic analysis suggested that significant overestimation of inland nighttime low O 3 mixing ratios may be attributed to underestimates of nitric oxide (NO) emissions at night. The absence of the second daily peak in simulations for the Appledore Island marine site possibly resulted from coarse grid resolution misrepresentation of land surface type. CompariCorrespondence to: H. Mao (hmao@gust.sr.unh.edu) son with shipboard measurements suggested that CMAQ has an inherent problem of underpredicting O 3 levels in continental outflow. Modeled O 3 vertical profiles exhibited a lack of structure indicating that key processes missing from CMAQ, such as lightning produced NO and stratospheric intrusions, are important for accurate upper tropospheric representations.

Characterization of an eastern U.S. severe air pollution episode using WRF/Chem

“…WRF/ Chem overestimates low O 3 values and underestimates high values. Previous studies evaluating other regional models, such as CMAQ, HYSPLIT, and MM5-Chem produced similar agreement with observations [e.g., Kang and Elder, 2005, Mao et al, 2010, Godowitch et al, 2008, Castellanos et al, 2011. Figure 7 shows the distribution frequency of observed and simulated 8 h O 3 daily maxima.…”

“…Mean biases on individual days are also small ranging from 2.9 ppbv on 6 July to −2.3 ppbv on 7 July. In terms of error, average WRF/Chem RMSE and NME values (11.0 ppbv and 16.2%) are on the lower end of previous studies (12–18 ppbv and 18–25%), respectively [e.g., Kang and Elder , 2005; Eder et al , 2009; Mao et al , 2010; Zhang et al , 2006]. Low domain‐wide biases often mask larger regional biases.…”

A comparison of atmospheric composition using the Carbon Bond and Regional Atmospheric Chemistry Mechanisms

“…However, nighttime predicted values obtained with CB05TU are 6-8 ppbv greater than the observed values. Nighttime O 3 overpredictions by atmospheric chemical transport models arise from model resolution artifacts and have been reported by other investigators (e.g., Arnold et al, 2006;and Mao et al, 2010b). CB05TU predicted peak value exceeds the observed value by ∼8 ppbv.…”

Influence of Climate Change and Meteorological Factors on Houston’s Air Pollution: Ozone a Case Study

“…Air masses with CO mixing ratios below the 25th percentile value are commonly considered background air [27]. In this study, we used the 20th percentile ofconcurrently measured carbon monoxide (CO) and O3 to ascertain background O3 [28]. These measurements were performed atop Moody Tower on the University of Houston campus over the time period of January 2008 to January 2014.…”