TY - JOUR
T1 - Evaluating high-resolution forecasts of atmospheric CO and CO2 from a global prediction system during KORUS-AQ field campaign
AU - Tang, Wenfu
AU - Arellano, Avelino F.
AU - DiGangi, Joshua P.
AU - Choi, Yonghoon
AU - Diskin, Glenn S.
AU - Agustí-Panareda, Anna
AU - Parrington, Mark
AU - Massart, Sebastien
AU - Gaubert, Benjamin
AU - Lee, Youngjae
AU - Kim, Danbi
AU - Jung, Jinsang
AU - Hong, Jinkyu
AU - Hong, Je Woo
AU - Kanaya, Yugo
AU - Lee, Mindo
AU - Stauffer, Ryan M.
AU - Thompson, Anne M.
AU - Flynn, James H.
AU - Woo, Jung Hun
N1 - Funding Information: Acknowledgements. This work is supported by NASA KORUS-AQ (NNX16AE16G and NNX16AD96G). We thank the KORUS-AQ team for observational data, the CAMS global production team for the model products of CO and CO2, MOPITT, IASI, OCO-2, and GOSAT data teams for satellite data. IASI CO is provided by LATMOS/CNRS and ULB. We acknowledge NASA and the OCO-2 project for OCO-2 CO2 data. We thank the DIAL-HSRL team for the mixed layer heights product. The authors thank Cenlin He and Kazuyuki Miyazaki for helpful comments on improving the paper. NCAR is sponsored by the National Science Foundation. Yugo Kanaya was supported by the Environment Research and Technology Development Fund (2-1505 and 2-1803) of the Ministry of the Environment, Japan. The authors thank the anonymous reviewers for their comments and suggestions. The CAMS data were generated using Copernicus Atmosphere Monitoring Service Information (2016). Publisher Copyright: © Author(s) 2018.
PY - 2018/8/7
Y1 - 2018/8/7
N2 - 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 Combining double low line 9ppbvppmv-1) compared to the West Sea (dCO dCO2 Combining double low line 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.
AB - 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 Combining double low line 9ppbvppmv-1) compared to the West Sea (dCO dCO2 Combining double low line 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.
UR - http://www.scopus.com/inward/record.url?scp=85051189480&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85051189480&partnerID=8YFLogxK
U2 - 10.5194/acp-18-11007-2018
DO - 10.5194/acp-18-11007-2018
M3 - Article
SN - 1680-7316
VL - 18
SP - 11007
EP - 11030
JO - Atmospheric Chemistry and Physics
JF - Atmospheric Chemistry and Physics
IS - 15
ER -