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Chemical data assimilation with aqueous chemistry in WRF-Chem coupled with WRFDA (V4.4.1)
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  • Soyoung Ha,
  • Rajesh Kumar,
  • Gabriele G. Pfister,
  • Yonghee Lee,
  • Daegyun Lee,
  • Hyun Mee Kim,
  • Young-Hee Ryu
Soyoung Ha
National Center for Atmospheric Research (UCAR)

Corresponding Author:[email protected]

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Rajesh Kumar
National Center for Atmospheric Research (UCAR)
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Gabriele G. Pfister
National Center for Atmospheric Research (UCAR)
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Yonghee Lee
National Institute of Environmental Research
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Daegyun Lee
National Institute of Environmental Research
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Hyun Mee Kim
Yonsei University
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Young-Hee Ryu
Yonsei University
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Abstract

This study introduces a new chemistry option in the Weather Research and Forecasting model data assimilation (WRFDA) system, coupled with the WRF-Chem model (Version 4.4.1), to incorporate aqueous chemistry (AQCHEM) in the assimilation of ground-level chemical measurements. The new data assimilation capability includes the integration of aqueous-phase aerosols from the Regional Atmospheric Chemistry Mechanism (RACM) gas chemistry, the Modal Aerosol Dynamics Model for Europe (MADE) aerosol chemistry, and the Volatility Basis Set (VBS) for secondary organic aerosol (SOA) production. The RACM-MADE-VBS-AQCHEM scheme facilitates aerosol-cloud-precipitation interactions by activating aerosol particles in cloud water during the model simulation. With the goal of enhancing air quality forecasting in cloudy conditions, this new implementation is demonstrated in the weakly coupled three-dimensional variational data assimilation (3D-Var) system through regional air quality cycling over East Asia. Surface particulate matter (PM) concentrations and four gas species (SO$_2$, NO$_2$, O$_3$, and CO) are assimilated every 6 h for the month of March 2019. The results show that including aqueous-phase aerosols in both the analysis and forecast can represent aerosol wet removal processes associated with cloud development and rainfall production. During a pollution event with high cloud cover, simulations without aerosols defined in cloud water exhibit significantly higher values for liquid water path (LWP), and surface PM$_{10}$ (PM$_{2.5}$) concentrations are overestimated by a factor of 10 (3) when wet scavenging processes dominate. On the contrary, aqueous chemistry proves to be helpful in simulating the wet deposition of aerosols, accurately predicting the evolution of surface PM concentrations without such overestimation.
14 Jul 2023Submitted to ESS Open Archive
20 Jul 2023Published in ESS Open Archive