Difference between revisions of "Papers:Lin et al 2020"
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'''Abstract |''' 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 PM2.5 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 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 Classic model did (r=0.72, bias =55 %). 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 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 http://wrf.geos-chem.org (last access: 10 July 2020). | '''Abstract |''' 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 PM2.5 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 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 Classic model did (r=0.72, bias =55 %). 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 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 http://wrf.geos-chem.org (last access: 10 July 2020). | ||
| − | '''Publication |''' '''Lin, H.''', '''Feng, X.''', '''Fu, T.-M.*''', '''Tian, H.''', '''Ma, Y.''', '''Zhang, L.''', Jacob, D.J., Yantosca, R.M., Sulprizio, M.P., Lundgren, E.W., Zhuang, J., Zhang, Q., Lu, X., Zhang, L., Shen, L., Guo, J., Eastham, S.D., Keller, C.A. (2020), 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, ''Geosci. Model Dev.'', doi:10.5194/gmd-13-3241-2020. [https:// | + | '''Publication |''' '''Lin, H.''', '''Feng, X.''', '''Fu, T.-M.*''', '''Tian, H.''', '''Ma, Y.''', '''Zhang, L.''', Jacob, D.J., Yantosca, R.M., Sulprizio, M.P., Lundgren, E.W., Zhuang, J., Zhang, Q., Lu, X., Zhang, L., Shen, L., Guo, J., Eastham, S.D., Keller, C.A. (2020), 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, ''Geosci. Model Dev.'', doi:10.5194/gmd-13-3241-2020. [https://atmoschem.org.cn/papers/Lin_et_al_2020_Geoscientific_Model_Development.pdf PDF ] [https://gmd.copernicus.org/articles/13/3241/2020/gmd-13-3241-2020.html Full text] |
Latest revision as of 15:00, 8 October 2023
Abstract | 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 PM2.5 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 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 Classic model did (r=0.72, bias =55 %). 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 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 http://wrf.geos-chem.org (last access: 10 July 2020).
Publication | Lin, H., Feng, X., Fu, T.-M.*, Tian, H., Ma, Y., Zhang, L., Jacob, D.J., Yantosca, R.M., Sulprizio, M.P., Lundgren, E.W., Zhuang, J., Zhang, Q., Lu, X., Zhang, L., Shen, L., Guo, J., Eastham, S.D., Keller, C.A. (2020), 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, Geosci. Model Dev., doi:10.5194/gmd-13-3241-2020. PDF Full text
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