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

Date

2018-08-07

Department

Program

Citation of Original Publication

Tang, Wenfu, Avelino F. Arellano, Joshua P. DiGangi, Yonghoon Choi, Glenn S. Diskin, Anna Agustí-Panareda, Mark Parrington, et al. “Evaluating High-Resolution Forecasts of Atmospheric CO and CO2 from a Global Prediction System during KORUS-AQ Field Campaign.” Atmospheric Chemistry and Physics 18, no. 15 (August 7, 2018): 11007–30. https://doi.org/10.5194/acp-18-11007-2018.

Rights

This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Public Domain

Subjects

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 9 km 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 0.3 ppmv for 16 and 9 km CO₂ forecasts, and analyses, respectively. The positive CO₂ mean bias in the 16 km 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 (16 km), −16.7 (9 km), and −20.7 ppbv (analysis). This negative CO mean bias is mostly seen below 750 hPa 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=9ppbv ppmv⁻¹) compared to the West Sea (dCO/dCO₂=28 ppbv ppmv⁻¹). This “combustion signature contrast” is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 8–12 ppbv ppmv⁻¹, the West Sea: ∼30 ppbv ppmv⁻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 (∼0.4 ppmv hPa⁻¹ for CO₂ and 3.5 ppbv hPa⁻¹ for CO) in the morning samples than observed (∼0.25 ppmv hPa⁻¹ for CO₂ and 1.7 ppbv hPa⁻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 (9 km vs. 16 km) generally produces better forecasts.