Articles | Volume 20, issue 10
https://doi.org/10.5194/acp-20-6015-2020
https://doi.org/10.5194/acp-20-6015-2020
Research article
 | 
20 May 2020
Research article |  | 20 May 2020

Improving air quality forecasting with the assimilation of GOCI aerosol optical depth (AOD) retrievals during the KORUS-AQ period

Soyoung Ha, Zhiquan Liu, Wei Sun, Yonghee Lee, and Limseok Chang

Related authors

Incremental analysis update (IAU) in the Model for Prediction Across Scales coupled with the Joint Effort for Data assimilation Integration (MPAS–JEDI 2.0.0)
Soyoung Ha, Jonathan J. Guerrette, Ivette Hernández Baños, William C. Skamarock, and Michael G. Duda
Geosci. Model Dev., 17, 4199–4211, https://doi.org/10.5194/gmd-17-4199-2024,https://doi.org/10.5194/gmd-17-4199-2024, 2024
Short summary
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta): ensemble of 3D ensemble-variational (En-3DEnVar) assimilations
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023,https://doi.org/10.5194/gmd-16-7123-2023, 2023
Short summary
Aerosol data assimilation with aqueous chemistry in WRF-Chem/WRFDA V4.3.1
Soyoung Ha
EGUsphere, https://doi.org/10.5194/egusphere-2022-371,https://doi.org/10.5194/egusphere-2022-371, 2022
Preprint withdrawn
Short summary
Implementation of aerosol data assimilation in WRFDA (v4.0.3) for WRF-Chem (v3.9.1) using the RACM/MADE-VBS scheme
Soyoung Ha
Geosci. Model Dev., 15, 1769–1788, https://doi.org/10.5194/gmd-15-1769-2022,https://doi.org/10.5194/gmd-15-1769-2022, 2022
Short summary

Related subject area

Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
The surface tension and cloud condensation nuclei (CCN) activation of sea spray aerosol particles
Judith Kleinheins, Nadia Shardt, Ulrike Lohmann, and Claudia Marcolli
Atmos. Chem. Phys., 25, 881–903, https://doi.org/10.5194/acp-25-881-2025,https://doi.org/10.5194/acp-25-881-2025, 2025
Short summary
Exploring the processes controlling secondary inorganic aerosol: evaluating the global GEOS-Chem simulation using a suite of aircraft campaigns
Olivia G. Norman, Colette L. Heald, Solomon Bililign, Pedro Campuzano-Jost, Hugh Coe, Marc N. Fiddler, Jaime R. Green, Jose L. Jimenez, Katharina Kaiser, Jin Liao, Ann M. Middlebrook, Benjamin A. Nault, John B. Nowak, Johannes Schneider, and André Welti
Atmos. Chem. Phys., 25, 771–795, https://doi.org/10.5194/acp-25-771-2025,https://doi.org/10.5194/acp-25-771-2025, 2025
Short summary
Influence of land cover change on atmospheric organic gases, aerosols, and radiative effects
Ryan Vella, Matthew Forrest, Andrea Pozzer, Alexandra P. Tsimpidi, Thomas Hickler, Jos Lelieveld, and Holger Tost
Atmos. Chem. Phys., 25, 243–262, https://doi.org/10.5194/acp-25-243-2025,https://doi.org/10.5194/acp-25-243-2025, 2025
Short summary
Quantifying the impacts of marine aerosols over the southeast Atlantic Ocean using a chemical transport model: implications for aerosol–cloud interactions
Mashiat Hossain, Rebecca M. Garland, and Hannah M. Horowitz
Atmos. Chem. Phys., 24, 14123–14143, https://doi.org/10.5194/acp-24-14123-2024,https://doi.org/10.5194/acp-24-14123-2024, 2024
Short summary
Quantifying the impact of global nitrate aerosol on tropospheric composition fields and its production from lightning NOx
Ashok K. Luhar, Anthony C. Jones, and Jonathan M. Wilkinson
Atmos. Chem. Phys., 24, 14005–14028, https://doi.org/10.5194/acp-24-14005-2024,https://doi.org/10.5194/acp-24-14005-2024, 2024
Short summary

Cited articles

Ackermann, I. J., Hass, H., Memmesheimer, M., Ebel, A., Binkowski, F. S., and Shankar, U.: Modal aerosol dynamics model for Europe: development and first applications, Atmos. Environ., 32, 2981–2999, https://doi.org/10.1016/S1352-2310(98)00006-5, 1998. a
Ahmadov, R., McKeen, S. A., Robinson, A. L., Bahreini, R., Middlebrook, A. M., de Gouw, J. A., Meagher, J., Hsie, E.-Y., Edgerton, E., Shaw, S., and Trainer, M.: A volatility basis set model for summertime secondary organic aerosols over the eastern United States in 2006, J. Geophys. Res.-Atmos., 117, D06301, https://doi.org/10.1029/2011JD016831, 2012. a
Baklanov, A., Schlünzen, K., Suppan, P., Baldasano, J., Brunner, D., Aksoyoglu, S., Carmichael, G., Douros, J., Flemming, J., Forkel, R., Galmarini, S., Gauss, M., Grell, G., Hirtl, M., Joffre, S., Jorba, O., Kaas, E., Kaasik, M., Kallos, G., Kong, X., Korsholm, U., Kurganskiy, A., Kushta, J., Lohmann, U., Mahura, A., Manders-Groot, A., Maurizi, A., Moussiopoulos, N., Rao, S. T., Savage, N., Seigneur, C., Sokhi, R. S., Solazzo, E., Solomos, S., Sørensen, B., Tsegas, G., Vignati, E., Vogel, B., and Zhang, Y.: Online coupled regional meteorology chemistry models in Europe: current status and prospects, Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, 2014. a
Baklanov, A., Brunner, D., Carmichael, G., Flemming, J., Freitas, S., Gauss, M., Hov, O., Mathur, R., Schlünzen, K. H., Seigneur, C., and Vogel, B.: Key Issues for Seamless Integrated Chemistry–Meteorology Modeling, B. Am. Meteorol. Soc., 98, 2285–2292, https://doi.org/10.1175/BAMS-D-15-00166.1, 2017. a
Barker, D., Huang, X.-Y., Liu, Z., Auligné, T., Zhang, X., Rugg, S., Ajjaji, R., Bourgeois, A., Bray, J., Chen, Y., Demirtas, M., Guo, Y.-R., Henderson, T., Huang, W., Lin, H.-C., Michalakes, J., Rizvi, S., and Zhang, X.: The Weather Research and Forecasting Model's Community Variational/Ensemble Data Assimilation System: WRFDA, B. Am. Meteorol. Soc., 93, 831–843, https://doi.org/10.1175/BAMS-D-11-00167.1, 2012. a
Download
Short summary
This study examines the effect of aerosol optical depth (AOD) retrieved from the Korean Geostationary Ocean Color Imager (GOCI) sensors on surface PM2.5 forecasts using the online coupled WRF-Chem forecasting model and the GSI 3D-Var analysis system. During the KORUS-AQ campaign period, the assimilation of GOCI AOD retrieved at the 550 nm wavelength greatly improved air quality forecasting up to 24 h when assimilated with surface PM2.5 observations, particularly for heavy pollution events.
Altmetrics
Final-revised paper
Preprint