WRF-GC (v1.0): online coupling of WRF (v3.9.1.1) and GEOS-Chem (v12.2.1) for regional atmospheric chemistry modeling – Part 1: Description of the one-way model

• Main Authors: H. Lin, X. Feng, T.-M. Fu, H. Tian, Y. Ma, L. Zhang, D. J. Jacob, R. M. Yantosca, M. P. Sulprizio, E. W. Lundgren, J. Zhuang, Q. Zhang, X. Lu, L. Shen, J. Guo, S. D. Eastham, C. A. Keller
• Format: Article
• Language: English
• Published: Copernicus Publications 2020-07-01
• Series: Geoscientific Model Development
• Online Access: https://gmd.copernicus.org/articles/13/3241/2020/gmd-13-3241-2020.pdf

<p>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. WRF and GEOS-Chem are both open-source community models. WRF-GC offers regional modellers access to the latest GEOS-Chem chemical module, which is 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 enables GEOS-Chem users to perform high-resolution forecasts and hindcasts for any region and time of interest. WRF-GC uses unmodified copies of WRF and GEOS-Chem from their respective sources; the coupling structure allows future versions of either one of the two parent models to be integrated into WRF-GC with relative ease. Within WRF-GC, the physical and chemical state variables are managed in distributed memory and translated between WRF and GEOS-Chem by the WRF-GC coupler at runtime. We used the WRF-GC model to simulate surface PM<span class="inline-formula">_2.5</span> concentrations over China during 22 to 27 January 2015 and compared the results to surface observations and the outcomes from a GEOS-Chem Classic nested-China simulation. Both models were able to reproduce the observed spatiotemporal variations of regional PM<span class="inline-formula">_2.5</span>, but the WRF-GC model (<span class="inline-formula"><i>r</i>=0.68</span>, bias <span class="inline-formula">=29</span>&thinsp;%) reproduced the observed daily PM<span class="inline-formula">_2.5</span> concentrations over eastern China better than the GEOS-Chem Classic model did (<span class="inline-formula"><i>r</i>=0.72</span>, bias <span class="inline-formula">=55</span>&thinsp;%). This was because the WRF-GC simulation, nudged with surface and upper-level meteorological observations, was able to better represent the pollution meteorology during the study period. The WRF-GC model is parallelized across computational cores and scales well on massively parallel architectures. In our tests where the two<span id="page3242"/> models were similarly configured, the WRF-GC simulation was 3 times more efficient than the GEOS-Chem Classic nested-grid simulation due to the efficient transport algorithm and the Message Passing Interface (MPI)-based parallelization provided by the WRF software framework. WRF-GC v1.0 supports one-way coupling only, using WRF-simulated meteorological fields to drive GEOS-Chem with no chemical feedbacks. 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 <span class="uri">http://wrf.geos-chem.org</span> (last access: 10 July 2020).</p>