ALBERT

Description: 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=9 ppbv 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.

Description: 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 plus two higher resolution forecasts (16-km 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-km and 9-km CO2 forecasts, and analyses, respectively. The positive CO2 mean bias in the16-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 show a remarkable agreement with observed enhancement ratios of CO with CO2 over Seoul metropolitan and over the West Sea, where East Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul (delta(CO)/delta(CO2) = 9 ppbv/ppmv) compared to the West Sea (delta(CO)/delta(CO2) = 28 ppbv/ppmv). 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, West Sea: ~30 ppbv/ppmv) 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, 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 for CO2 and 3.5 ppbv/hPa for CO) in the morning samples than observed (~0.25 ppmv/hPa for CO2 and 1.7 ppbv/hPa 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 produce better forecasts.

Description: 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 (dCOdCO2 = 9ppbvppmv(exp 1)) compared to the West Sea (dCOdCO2 = 28ppbvppmv(exp 1)). This "combustion signature contrast" is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 812ppbvppmv(exp 1), the West Sea: 30ppbvppmv(exp 1)) regardless of forecast/analysis configurations. The correlation of CAMS CO bias with CO2 bias is relatively high over these two regions (Seoul: 0.640.90, 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(exp 1) for CO2 and 3.5ppbvhPa(exp 1) for CO) in the morning samples than observed ( 0.25ppmvhPa(exp 1) for CO2 and 1.7ppbvhPa(exp 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.