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We present the WRF-GC model v2.0, an online two-way coupling of the Weather Research and Forecasting (WRF) meteorological model (v3.9.1.1) 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. [ABSTRACT FROM AUTHOR]

We developed the WRF-GC model, an online coupling of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the GEOS-Chem atmospheric chemistry model, for regional atmospheric chemistry and air quality modeling. Both WRF and GEOS-Chem are open-source and community-supported. WRF-GC provides regional chemistry modellers easy access to the GEOS-Chem chemical module, which is stably-configured, state-of-the-science, well-documented, traceable, benchmarked, actively developed by a large international user base, and centrally managed by a dedicated support team. At the same time, WRF-GC gives GEOS-Chem users the ability to perform high-resolution forecasts and hindcasts for any location and time of interest. WRF-GC is designed to be easy to use, massively parallel, extendable, and easy to update. The WRF-GC coupling structure allows future versions of either one of the two parent models to be immediately integrated into WRF-GC. This enables WRF-GC to stay state-of-the-science with traceability to parent model versions. Physical and chemical state variables in WRF and in GEOS-Chem are managed in distributed memory and translated between the two models by the WRF-GC Coupler at runtime. We used the WRF-GC model to simulate surface PM2.5 concentrations over China during January 22 to 27, 2015 and compared the results to surface observations and the outcomes from a GEOS-Chem nested-grid simulation. Both models were able to reproduce the observed spatiotemporal variations of regional PM2.5, but the WRF-GC model (r = 0.68, bias = 29%) reproduced the observed daily PM2.5 concentrations over Eastern China better than the GEOS-Chem model did (r = 0.72, bias = 55%). This was mainly because our WRF-GC simulation, nudged with surface and upper-level meteorological observations, was able to better represent the spatiotemporal variability of the planetary boundary layer heights over China during the simulation period. Both parent models and the WRF-GC Coupler are parallelized across computational cores and can scale to massively parallel architectures. The WRF-GC simulation was three times more efficient than the GEOS-Chem nested-grid simulation at similar resolutions and for the same number of computational cores, owing to the more efficient transport algorithm and the MPI-based parallelization provided by the WRF software framework. WRF-GC scales nearly perfectly up to a few hundred cores on a variety of computational platforms. Version 1.0 of the WRF-GC model supports one-way coupling only, using WRF-simulated meteorological fields to drive GEOS-Chem with no feedbacks from GEOS-Chem. The development of two-way coupling capabilities, i.e., the ability to simulate radiative and microphysical feedbacks of chemistry to meteorology, is under-way. The WRF-GC model is open-source and freely available from http://wrf.geos-chem.org. [ABSTRACT FROM AUTHOR]