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Improving regional ozone modeling through systematic evaluation of errors using the aircraft observations during the International Consortium for Atmospheric Research on Transport and Transformation
Center for Global and Regional Environmental Research, University of Iowa, Iowa City, Iowa, USA
Center for Global and Regional Environmental Research, University of Iowa, Iowa City, Iowa, USA
Center for Global and Regional Environmental Research, University of Iowa, Iowa City, Iowa, USA
Center for Global and Regional Environmental Research, University of Iowa, Iowa City, Iowa, USA
Department of Chemical Engineering, Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand
Center for Global and Regional Environmental Research, University of Iowa, Iowa City, Iowa, USA
Center for Global and Regional Environmental Research, University of Iowa, Iowa City, Iowa, USA
Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, New Jersey, USA
Institute for the Environment, University of North Carolina, Chapel Hill, North Carolina, USA
NASA Langley Research Center, Hampton, Virginia, USA
Department of Earth Sciences, Pennsylvania State University, University Park, Pennsylvania, USA
Institute for the Study of Earth, Ocean, and Space, University of New Hampshire, Durham, New Hampshire, USA
Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, Colorado, USA
Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, Colorado, USA
NASA Langley Research Center, Hampton, Virginia, USA
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, Colorado, USA
Institute for the Study of Earth, Ocean, and Space, University of New Hampshire, Durham, New Hampshire, USA
Argonne National Laboratory, Argonne, Illinois, USA
Chemical Sciences Division, Earth System Research Laboratory, NOAA, Boulder, Colorado, USA
Department of Chemistry, University of California, Irvine, California, USA
During the operational phase of the ICARTT field experiment in 2004, the regional air quality model STEM showed a strong positive surface bias and a negative upper troposphere bias (compared to observed DC-8 and WP-3 observations) with respect to ozone. After updating emissions from NEI 1999 to NEI 2001 (with a 2004 large point sources inventory update), and modifying boundary conditions, low-level model bias decreases from 11.21 to 1.45 ppbv for the NASA DC-8 observations and from 8.26 to −0.34 for the NOAA WP-3. Improvements in boundary conditions provided by global models decrease the upper troposphere negative ozone bias, while accounting for biomass burning emissions improved model performance for CO. The covariances of ozone bias were highly correlated to NOz, NOy, and HNO3 biases. Interpolation of bias information through kriging showed that decreasing emissions in SE United States would reduce regional ozone model bias and improve model correlation coefficients. The spatial distribution of forecast errors was analyzed using kriging, which identified distinct features, which when compared to errors in postanalysis simulations, helped document improvements. Changes in dry deposition to crops were shown to reduce substantially high bias in the forecasts in the Midwest, while updated emissions were shown to account for decreases in bias in the eastern United States. Observed and modeled ozone production efficiencies for the DC-8 were calculated and shown to be very similar (7.8) suggesting that recurring ozone bias is due to overestimation of NOx emissions. Sensitivity studies showed that ozone formation in the United States is most sensitive to NOx emissions, followed by VOCs and CO. PAN as a reservoir of NOx can contribute to a significant amount of surface ozone through thermal decomposition.
Received 6 July 2006; accepted 5 April 2007; published 9 June 2007.
Citation: (2007), Improving regional ozone modeling through systematic evaluation of errors using the aircraft observations during the International Consortium for Atmospheric Research on Transport and Transformation, J. Geophys. Res., 112, D12S19, doi:10.1029/2006JD007762.
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