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

Benjamin Gaubert (1) , Louisa Emmons , Kevin Raeder , Simone Tilmes , Kazuyuki Miyazaki , Avelino Arellano Jr. , Nellie Elguindi , Claire Granier (2) , Wenfu Tang , Jérôme Barré , Helen Worden , Rebecca Buchholz , David Edwards , Philipp Franke , Jeffrey Anderson , Marielle Saunois , Jason Schroeder , Jung-Hun Woo , Isobel Simpson , Donald Blake , Simone Meinardi , Paul Wennberg , John Crounse , Alex Teng , Michelle Kim , Russell Dickerson , Hao He , Xinrong Ren

1 NCAR - National Center for Atmospheric Research [Boulder]
2 LAERO - Laboratoire d'aérologie

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 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 Plains (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 two the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to wide spread NOx controls, can improve pollution ozone over East Asia.

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 VOCs play an important role. Here we investigate the 40 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 45 (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 2 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 50 Plains (NCP). Yet, an often-overlooked aspect of these inversions is that correcting the underestimation in anthropogenic CO emissions also improves the comparison with observational O 3 datasets, and observationally constrained box model simulations of OH and HO 2. Running a CAM-chem simulation with the updated emissions of anthropogenic CO reduces the bias by 29 % for CO, 18 % for ozone, 11 % for HO 2 and 27 % for OH. Longer lived anthropogenic VOCs whose 55 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 O 3 , 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 two the modeled biogenic emissions for the plant functional types found 60 in Korea. Results also suggest that controlling VOC and CO emissions, in addition to wide spread NOx controls, can improve pollution ozone over East Asia.

Domaines: Planète et Univers [physics]

Benjamin Gaubert, Louisa Emmons, Kevin Raeder, Simone Tilmes, Kazuyuki Miyazaki, et al.. Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ. 2020. ⟨hal-03108152v1⟩