Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ

Abstract

Abstract. Global coupled chemistry–climate models underestimate carbon monoxide (CO) in the Northern Hemisphere, exhibiting a pervasive negative bias against measurements peaking in late winter and early spring. While this bias has been commonly attributed to underestimation of direct anthropogenic and biomass burning emissions, chemical production and loss via OH reaction from emissions of anthropogenic and biogenic volatile organic compounds (VOCs) play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the Korea–United States Air Quality (KORUS-AQ) experiment in South Korea and the Air Chemistry Research in Asia (ARIAs) in the North China Plain (NCP). For reference, multispectral CO retrievals (V8J) from the Measurements of Pollution in the Troposphere (MOPITT) are jointly assimilated with meteorological observations using an ensemble adjustment Kalman filter (EAKF) within the global Community Atmosphere Model with Chemistry (CAM-Chem) and the Data Assimilation Research Testbed (DART). With regard to KORUS-AQ data, CO is underestimated by 42 % in the control run and by 12 % with the MOPITT assimilation run. The inversion suggests an underestimation of anthropogenic CO sources in many regions, by up to 80 % for northern China, with large increments over the Liaoning Province and the North China Plain (NCP). Yet, an often-overlooked aspect of these inversions is that correcting the underestimation in anthropogenic CO emissions also improves the comparison with observational O3 datasets and observationally constrained box model simulations of OH and HO2. Running a CAM-Chem simulation with the updated emissions of anthropogenic CO reduces the bias by 29 % for CO, 18 % for ozone, 11 % for HO2, and 27 % for OH. Longer-lived anthropogenic VOCs whose model errors are correlated with CO are also improved, while short-lived VOCs, including formaldehyde, are difficult to constrain solely by assimilating satellite retrievals of CO. During an anticyclonic episode, better simulation of O3, with an average underestimation of 5.5 ppbv, and a reduction in the bias of surface formaldehyde and oxygenated VOCs can be achieved by separately increasing by a factor of 2 the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to widespread NOx controls, can improve ozone pollution over East Asia.

Comprehensive evaluation of the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis against independent observations

“…Although further investigations and sensitivity analysis will be needed to prove this, it is likely that unreasonable trends in the emissions are responsible for the drifts (see Section 3.4). In a recent study, Gaubert et al (2020) show that running CTMs with biased CO and volatile organic compound (VOC) emissions can lead to poorly modeled O 3 .…”

Analysis of secondary organic aerosol simulation bias in the Community Earth System Model (CESM2.1)

“…To reveal the uncertainties associated with OA simulation in climate models, we evaluate a recent version of Community Earth System Model version 2.1 (CESM2.1) in this study with multiple observational datasets in the US. The model has been widely applied for OA climate effect assessment purposes (Gettelman et al, 2019;Glotfelty et al, 2017;Tilmes et al, 2019;Jo et al, 2021), and a significant portion of improvements has been implemented in the latest version regarding the chemical mechanisms . In the previous CESM version (Lamarque et al, 2012), SOA chemistry was represented with the two-product method (Lack et al, 2004;Heald et al, 2008).…”

The Environment and Climate Change Canada Carbon Assimilation System (EC-CAS v1.0): demonstration with simulated CO observations

“…The Kalman filter equation (Ghil et al, 1981;Cohn and Parrish, 1991) at a particular DA cycle at time t is given by…”

“…MOPITT is an important component of the global CO observing system because it measures spectra in both the near-infrared and thermal infrared ranges; thus, its retrieved profiles are sensitive to CO in the lower troposphere during daytime over land, where the flux signal from surface emissions is most readily detected. As a result of this sensitivity to lower tropospheric CO and due to the long observational record, MOPITT data are widely used for inverse modeling of CO emissions and for air quality studies (Arellano and Hess, 2006;Fortems-Cheiney et al, 2011;Barré et al, 2015;Jiang et al, 2015a;Yin et al, 2015;Mizzi et al, 2016;Inness et al, 2019;Gaubert et al, 2020;Miyazaki et al, 2020). It has a nadir footprint of 22 km ×22 km and a 612 km cross-track scanning swath, with an orbit that repeats every 3 d. We used V7J MOPITT data with locations thinned to one observation per grid box.…”