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Application of satellite data in a regional model to improve long-term ozone simulations

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Abstract

To investigate an alternative technique of providing background and transboundary transport inputs for ozone (O3) simulations on a regional scale, the EPA’s Community Multi-scale Air Quality (CMAQ) model was integrated with high spectral resolution data from the Tropospheric Emission Spectrometer (TES) aboard the NASA’s Aura satellite. This study presents a comprehensive model evaluation of O3 for the entire year of 2009 over the contiguous United States with a focus on the State of Texas using both ozonesonde and ground measurements. While improving model performance in the upper atmosphere, CMAQ’s initial and boundary conditions (IC/BC) derived from the original TES data do not improve model performance in the troposphere because the satellite data exaggerated concentration of tropospheric O3. With a 10-ppb deduction of O3 concentration from TES, the IC/BC derived from the adjusted TES improves model performance from ground level through the upper atmosphere. The mean bias of daily maximum 8-h average concentration of O3 (MDA8) from the ground monitored in Texas decreased from 7 ppb to 4 ppb. Model results also show small influences of O3 from the upper troposphere on the concentrations at the ground level. With a complete exclusion of stratospheric layers, changes of annual mean MDA8 of O3 concentrations at ground-level were smaller than 1.1 % in Dallas and Houston. In addition, limitations of satellite data are discussed and recommendations are provided regarding the future application of satellite data in regional O3 simulations.

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Acknowledgments

This work was performed under the Texas Air Research Center (TARC) award 312LUB0121A. The input data of the meteorological model for this study are from the Research Data Archive (RDA) which is maintained by the Computational and Information Systems Laboratory (CISL) at the National Center for Atmospheric Research (NCAR). NCAR is sponsored by the National Science Foundation (NSF). The original data are available from the RDA (http://rda.ucar.edu) in dataset number ds083.2. The Tropospheric Emission Spectrometer data are from the NASA Langley Research Center Atmospheric Science Data Center. The author would like to thank people who shared emission and measurement data used in this study (RCP, EPA’s AQS, NOAA’s ESRL, NASA’s TES, TOPP, and WOUDC). The author thanks Thomas C. Ho and Hsing-wei Chu for providing computer cluster and financial support, and Che-Jen Lin and Amber Huddle for helpful discussions. The author thanks Robert B. Schmunk for data visualization software (NASA’s Panoply). For data processing tools, the author thanks Uwe Schulzweida, Luis Kornblueh, and Ralf Quast for the Climate Data Operators (CDO), and Charles Zender for the netCDF Operator (NCO).

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  1. Department of Mechanical Engineering, Lamar University, PO Box 10024, Beaumont, TX, 77710, USA

    Pruek Pongprueksa

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Correspondence to Pruek Pongprueksa.

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Pongprueksa, P. Application of satellite data in a regional model to improve long-term ozone simulations. J Atmos Chem 70, 317–340 (2013). https://doi.org/10.1007/s10874-013-9270-9

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