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

Journal Article · · Atmospheric Chemistry and Physics (Online)
ORCiD logo [1];  [1]; ORCiD logo [2]; ORCiD logo [3];  [2];  [4]; ORCiD logo [4];  [4]; ORCiD logo [5];  [5];  [5];  [6]; ORCiD logo [7]; ORCiD logo [7];  [8];  [5]; ORCiD logo [9]; ORCiD logo [10];  [11];  [12]
  1. Univ. of Arizona, Tucson, AZ (United States)
  2. NASA Langley Research Center, Hampton, VA (United States)
  3. NASA Langley Research Center, Hampton, VA (United States); Science Systems and Applications, Inc., Hampton, VA (United States)
  4. European Centre for Medium-Range Weather Forecasts, Reading (United Kingdom)
  5. National Center for Atmospheric Research, Boulder, CO (United States)
  6. Korea Research Institute of Standards and Science, Daejeon (South Korea)
  7. Yonsei Univ., Seoul (South Korea)
  8. Japan Agency for Marine-Earth Science and Technology, Kanagawa (Japan)
  9. Univ. Space Research Assoc., Columbia, MD (United States); NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
  10. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
  11. Univ. of Houston, Houston, TX (United States)
  12. Konkuk Univ., Seoul (South Korea)

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 -20.7 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 Combining double low line 9 ppbvppmv-1) compared to the West Sea (dCO dCO2 Combining double low line 28 ppbvppmv-1). This "combustion signature contrast" is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 8-12 ppbvppmv-1, the West Sea: ~ 30 ppbvppmv-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 ppmvhPa-1 for CO2 and 3.5 ppbvhPa-1 for CO) in the morning samples than observed (~ 0.25 ppmvhPa-1 for CO2 and 1.7 ppbvhPa-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.

Research Organization:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1479436
Journal Information:
Atmospheric Chemistry and Physics (Online), Vol. 18, Issue 15; ISSN 1680-7324
Publisher:
European Geosciences UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 27 works
Citation information provided by
Web of Science

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Cited By (11)

Ceilometer Monitoring of Boundary-Layer Height and Its Application in Evaluating the Dilution Effect on Air Pollution journal May 2019
Modeling Regional Pollution Transport Events During KORUS‐AQ: Progress and Challenges in Improving Representation of Land‐Atmosphere Feedbacks journal September 2018
Balance of Emission and Dynamical Controls on Ozone During the Korea‐United States Air Quality Campaign From Multiconstituent Satellite Data Assimilation journal January 2019
Source Contributions to Carbon Monoxide Concentrations During KORUS‐AQ Based on CAM‐chem Model Applications journal March 2019
Surface Meteorological Conditions and Boundary Layer Height Variations During an Air Pollution Episode in Nanjing, China journal March 2019
Evaluation of Regional CO 2 Mole Fractions in the ECMWF CAMS Real‐Time Atmospheric Analysis and NOAA CarbonTracker Near‐Real‐Time Reanalysis With Airborne Observations From ACT‐America Field Campaigns journal July 2019
Numerical simulation of atmospheric CO2 concentration and flux over the Korean Peninsula using WRF-VPRM model during Korus-AQ 2016 campaign journal January 2020
Secondary organic aerosol production from local emissions dominates the organic aerosol budget over Seoul, South Korea, during KORUS-AQ journal January 2018
Integration of airborne and ground observations of nitryl chloride in the Seoul metropolitan area and the implications on regional oxidation capacity during KORUS-AQ 2016 journal January 2019
Satellite data reveal a common combustion emission pathway for major cities in China journal January 2019
Modelling CO 2 weather – why horizontal resolution matters journal January 2019

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