Articles | Volume 17, issue 4
https://doi.org/10.5194/gmd-17-1931-2024
https://doi.org/10.5194/gmd-17-1931-2024
Model evaluation paper
 | 
01 Mar 2024
Model evaluation paper |  | 01 Mar 2024

Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign

Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang

Related authors

Diurnal variations of NO2 tropospheric vertical column density over the Seoul Metropolitan Area from the Geostationary Environment Monitoring Spectrometer (GEMS): seasonal differences and impacts of varying a priori NO2 profile data
Seunghwan Seo, Si-Wan Kim, Kyoung-Min Kim, Andreas Richter, Kezia Lange, John Philip Burrows, Junsung Park, Hyunkee Hong, Hanlim Lee, Ukkyo Jeong, and Jhoon Kim
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-33,https://doi.org/10.5194/amt-2024-33, 2024
Preprint under review for AMT
Short summary
Changes in surface ozone in South Korea on diurnal to decadal timescales for the period of 2001–2021
Si-Wan Kim, Kyoung-Min Kim, Yujoo Jeong, Seunghwan Seo, Yeonsu Park, and Jeongyeon Kim
Atmos. Chem. Phys., 23, 12867–12886, https://doi.org/10.5194/acp-23-12867-2023,https://doi.org/10.5194/acp-23-12867-2023, 2023
Short summary

Related subject area

Atmospheric sciences
Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method
Shuai Wang, Mengyuan Zhang, Yueqi Gao, Peng Wang, Qingyan Fu, and Hongliang Zhang
Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024,https://doi.org/10.5194/gmd-17-3617-2024, 2024
Short summary
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024,https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024,https://doi.org/10.5194/gmd-17-3599-2024, 2024
Short summary
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024,https://doi.org/10.5194/gmd-17-3533-2024, 2024
Short summary
Assessing acetone for the GISS ModelE2.1 Earth system model
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024,https://doi.org/10.5194/gmd-17-3487-2024, 2024
Short summary

Cited articles

Anenberg, S. C., Henze, D. K., Tinney, V., Kinney, P. L., Raich, W., Fann, N., Malley, C. S., Roman, H., Lamsal, L., Duncan, B., Martin, R. V., van Donkelaar, A., Brauer, M., Doherty, R., Jonson, J. E., Davila, Y., Sudo, K., and Kuylenstierna, J. C. I.: Estimates of the global burden of ambient PM2.5, Ozone, and NO2 on asthma incidence and emergency room visits, Environ. Health Persp., 126, 107004, https://doi.org/10.1289/EHP3766, 2018. 
Atmospheric Chemistry Observations & Modeling/National Center for Atmospheric Research/University Corporation for Atmospheric Research: CESM2.1 The Community Atmosphere Model with Chemistry (CAM-chem) Outputs as Boundary Conditions, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory [data set], https://doi.org/10.5065/CKR4-GP38, 2019. 
Buchholz, R. R., Emmons, L. K., Tilmes, S., and The CESM2 Development Team: CESM2.1/CAM-chem Instantaneous Output for Boundary Conditions, UCAR/NCAR – Atmospheric Chemistry Observations and Modeling Laboratory, Lat: −5 to 45, Lon: 75 to 145, 28 Nov 2022, https://doi.org/10.5065/NMP7-EP60, 2019. 
Carter, W. P.: Documentation of the SAPRC-99 chemical mechanism for VOC reactivity assessment, Contract, 92, 95–308, https://intra.engr.ucr.edu/~carter/pubs/s99doc.pdf (last access: 9 June 2023), 2000. 
Choi, J., Henze, D. K., Cao, H., Nowlan, C. R., Abad, G. G., Kwon, H.-A., Lee, H.-M., Oak, Y. J., Park, R. J., Bates, K. H., Massakkers, J. D., Wisthaler, A., and Weinheimer, A. J.: An Inversion Framework for Optimizing Non-Methane VOC Emissions Using Remote Sensing and Airborne Observations in Northeast Asia During the KORUS-AQ Field Campaign, J. Geophys. Res.-Atmos., 127, e2021JD035844, https://doi.org/10.1029/2021JD035844, 2022. 
Download
Short summary
Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.