WRF-GC (v2.0): online two-way coupling of WRF (v18.104.22.168) and GEOS-Chem (v12.7.2) for modeling regional atmospheric chemistry-meteorology interactions
- 1Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China
- 2John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
- 3State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China
- 4Shenzhen Institute of Sustainable Development, Southern University of Science and Technology, Shenzhen, Guangdong, China
- 5National Meteorological Information Center, China Meteorological Administration, Beijing, China
- 6State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China
Abstract. We present the WRF-GC model v2.0, an online two-way coupling of the Weather Research and Forecasting (WRF) meteorological model (v22.214.171.124) and the GEOS-Chem chemical model (v12.7.2). WRF-GC v2.0 is built on the modular framework of WRF-GC v1.0 and further includes aerosol-radiation interactions (ARI) and aerosol-cloud interactions (ACI) based on bulk aerosol mass and composition, as well as the capability to nest multiple domains for high-resolution simulations. WRF-GC v2.0 is the first implementation of the GEOS-Chem model in an open-source dynamic model with chemical feedbacks to meteorology. We apply prescribed size distributions to the 10 aerosol types simulated by GEOS-Chem to diagnose aerosol optical properties and activated cloud droplet numbers; the results are passed to the WRF model for radiative and cloud microphysics calculations. We use WRF-GC v2.0 to conduct sensitivity simulations with different combinations of ARI and ACI over China during January 2015 and July 2016, with the goal of evaluating the simulated aerosol and cloud properties and the impacts of ARI and ACI on meteorology and air quality. WRF-GC reproduces the day-to-day variability of the aerosol optical depth (AOD) observed by the Aerosol Robotic Network (AERONET) project at four representative Chinese sites in January 2015, with temporal correlation coefficients of 0.56 to 0.85. The magnitudes and spatial distributions of the simulated liquid cloud effective radii, liquid cloud optical depths, surface downward shortwave radiation, and surface temperature over China for July 2016 are in good agreement with aircraft, satellite, and surface observations. WRF-GC simulations including both ARI and ACI reproduce the observed surface concentrations and spatial distributions of PM2.5 in January 2015 (normalized mean bias = −6.6 %, spatial correlation r = 0.74) and afternoon ozone in July 2016 (normalized mean bias = 19 %, spatial correlation r = 0.56) over Eastern China, respectively. Our sensitivity simulations show that including the ARI and ACI improved the model's performance in simulating ozone concentrations over China in July, 2016. WRF-GC v2.0 is open source and freely available from http://wrf.geos-chem.org.
Xu Feng et al.
Xu Feng et al.
Xu Feng et al.
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