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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 18, issue 15
Atmos. Chem. Phys., 18, 11007-11030, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Chem. Phys., 18, 11007-11030, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 07 Aug 2018

Research article | 07 Aug 2018

Evaluating high-resolution forecasts of atmospheric CO and CO2 from a global prediction system during KORUS-AQ field campaign

Wenfu Tang1, Avelino F. Arellano1, Joshua P. DiGangi2, Yonghoon Choi2,3, Glenn S. Diskin2, Anna Agustí-Panareda4, Mark Parrington4, Sebastien Massart4, Benjamin Gaubert5, Youngjae Lee6, Danbi Kim6, Jinsang Jung7, Jinkyu Hong8, Je-Woo Hong8, Yugo Kanaya9, Mindo Lee6, Ryan M. Stauffer10,11, Anne M. Thompson11, James H. Flynn12, and Jung-Hun Woo13 Wenfu Tang et al.
  • 1Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
  • 2NASA Langley Research Center, Hampton, VA, USA
  • 3Science Systems and Applications, Inc., Hampton, VA, USA
  • 4European Centre for Medium-Range Weather Forecasts, Reading, UK
  • 5Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
  • 6National Institute of Environmental Research, Incheon, South Korea
  • 7Korea Research Institute of Standards and Science, Daejeon, South Korea
  • 8Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea
  • 9Japan Agency for Marine-Earth Science and Technology, Yokohama, Kanagawa, Japan
  • 10Universities Space Research Association, Columbia, MD, USA
  • 11Earth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 12Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA
  • 13Department of Advanced Technology Fusion, Konkuk University, Seoul, South Korea

Abstract. Accurate and consistent monitoring of anthropogenic combustion is imperative because of its significant health and environmental impacts, especially at city-to-regional scale. Here, we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) global prediction system using measurements from aircraft, ground sites, and ships during the Korea-United States Air Quality (KORUS-AQ) field study in May to June 2016. Our evaluation focuses on CAMS CO and CO2 analyses as well as two higher-resolution forecasts (16 and 9km horizontal resolution) to assess their capability in predicting combustion signatures over east Asia. Our results show a slight overestimation of CAMS CO2 with a mean bias against airborne CO2 measurements of 2.2, 0.7, and 0.3ppmv for 16 and 9km CO2 forecasts, and analyses, respectively. The positive CO2 mean bias in the 16km forecast appears to be consistent across the vertical profile of the measurements. In contrast, we find a moderate underestimation of CAMS CO with an overall bias against airborne CO measurements of −19.2 (16km), −16.7 (9km), and −20.7ppbv (analysis). This negative CO mean bias is mostly seen below 750hPa for all three forecast/analysis configurations. Despite these biases, CAMS shows a remarkable agreement with observed enhancement ratios of CO with CO2 over the Seoul metropolitan area and over the West (Yellow) Sea, where east Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul (dCO∕dCO2 = 9ppbvppmv−1) compared to the West Sea (dCO∕dCO2 = 28ppbvppmv−1). This combustion signature contrast is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 8–12ppbvppmv−1, the West Sea:  ∼ 30ppbvppmv−1) regardless of forecast/analysis configurations. The correlation of CAMS CO bias with CO2 bias is relatively high over these two regions (Seoul: 0.64–0.90, the West Sea: ∼ 0.80) suggesting that the contrast captured by CAMS may be dominated by anthropogenic emission ratios used in CAMS. However, CAMS shows poorer performance in terms of capturing local-to-urban CO and CO2 variability. Along with measurements at ground sites over the Korean Peninsula, CAMS produces too high CO and CO2 concentrations at the surface with steeper vertical gradients (∼ 0.4ppmvhPa−1 for CO2 and 3.5ppbvhPa−1 for CO) in the morning samples than observed (∼ 0.25ppmvhPa−1 for CO2 and 1.7ppbvhPa−1 for CO), suggesting weaker boundary layer mixing in the model. Lastly, we find that the combination of CO analyses (i.e., improved initial condition) and use of finer resolution (9km vs. 16km) generally produces better forecasts.

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