Preprints
https://doi.org/10.5194/egusphere-2022-371
https://doi.org/10.5194/egusphere-2022-371
 
29 Jun 2022
29 Jun 2022
Status: this preprint is open for discussion.

Aerosol data assimilation with aqueous chemistry in WRF-Chem/WRFDA V4.3.1

Soyoung Ha Soyoung Ha
  • National Center for Atmospheric Research, Boulder, Colorado, USA

Abstract. This article introduces a new chemistry option in the Weather Research and Forecasting model data assimilation (WRFDA) system coupled with the WRF-Chem model (Version 4.3.1) to activate aqueous chemistry (AQCHEM) for the assimilation of surface concentrations of particulate matter (PM) along with atmospheric observations. The gas-phase mechanism used is the Regional Atmospheric Chemistry Mechanism (RACM), the inorganic aerosols are treated with the Modal Aerosol Dynamics Model for Europe (MADE), and secondary organic aerosol (SOA) production is parameterized based on the Volatility Basis Set (VBS) approach. The "RACM-MADE-VBS-AQCHEM" scheme used in the weakly coupled data assimilation and forecast system facilitates aerosol-cloud-radiation-precipitation interactions through analysis and forecast cycling, accounting for both direct and indirect aerosol effects in the short-term air quality prediction. The new implementation in the three-dimensional variational data assimilation (3D-Var) system was tested with the assimilation of PM2.5 and PM10 concentrations on the ground over the East Asian region through month-long cycling for Spring 2019. It is demonstrated that the inclusion of aerosol species in the aqueous (or cloud-borne) phase in both analysis and forecast reproduces aerosol wet removal processes in association with the development of clouds, systematically changing the atmospheric composition. The new option with aqueous chemistry in WRFDA is beneficial in air quality forecasting in cloudy conditions, while the simulations without aqueous chemistry overestimate surface PM10 (PM2.5) by a factor of 10 (3).

Soyoung Ha

Status: open (until 24 Aug 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Soyoung Ha

Model code and software

WRF-Chem/WRFDA Soyoung Ha https://doi.org/10.5281/zenodo.6569325

Soyoung Ha

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Short summary
Heavy pollution events often occur in cloudy conditions, which is hard to observe. This study introduces a new 3D-Var analysis that can facilitate aerosol-cloud interactions through weakly coupled data assimilation using WRF-Chem/WRFDA.