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13. WRF-CMAQ Model#
13.1 Introduction#
Air Quality Models (AQMs) such as CMAQ are typically run in retrospective mode using archived meteorological data to drive the chemistry-transport calculations. Here the model producing the meteorological data is run first producing inputs that are synthesized into AQM model-ready inputs via pre-processors, such as MCIP.
But this one-way coupling process interpolates simulated dynamics and does not consider the effects of atmospheric pollutants on the energy budget of the atmosphere, both of which can change the driving meteorology. For example, aerosols can affect the amount of sunlight that reaches the surface, thus impacting temperature (aerosol direct effect).
To address these shortcomings, a coupled WRF-CMAQ model was developed (Wong et al., 2012). A single source code principle was used to construct this two-way coupling system so that CMAQ can be executed either as a stand-alone model or part of the coupled system without any code changes, by treating CMAQ as a subroutine in the WRF structure; this approach eliminates maintenance of separate code versions for the coupled and uncoupled systems.
The design also provides the flexibility to permit users: (1) to adjust the call frequency of WRF and CMAQ to balance the accuracy of the simulation versus computational intensity of the system, and (2) to execute the two-way coupling system with feedbacks to study the effect of gases and aerosols on short wave radiation and subsequent simulated dynamics.
13.2 Aerosol Direct Radiative Feedback Effects#
The presence of aerosols impacts the amount of radiation reaching the surface, in turn altering the energy budget of the atmosphere (manifesting itself as changes to temperature and the planetary boundary layer height). This is called the shortwave aerosol direct radiative effect. This has been implemented in the shortwave Rapid Radiative Transfer Model for General Circulation Models (RRTMG) radiation scheme in WRF, where aerosol optical properties such as extinction, single scattering albedo, and asymmetry factor are calculated for 14 wavelength bands (Clough et al. 2005) using aerosol composition and size information simulated by CMAQ. Specifically, data representing seven aerosol quantities (water soluble mass, water insoluble mass, elemental carbon, sea salt, water, geometric mean diameters, and standard deviations) for all three aerosol modes (Aitken, accumulation, and coarse) is transferred from CMAQ to WRF. The implementation utilizes the core-shell model where black carbon is treated as the center and the other substances comprise the shell. The aerosol optics calculations are based on Bohren and Huffman (1983). RRTMG is the only radiation scheme in WRF that is supported by the coupled WRF-CMAQ model.
13.3 Application and Evaluation#
The aerosol optics calculations in the WRF-CMAQ model were assessed through comparison to measured optical properties of ambient aerosols made during the Carbonaceous Aerosol and Radiation Effects Study (CARES) as detailed by Gan et al. (2015a).
The ability of the WRF-CMAQ system to reproduce historical trends in the tropospheric aerosol burden, aerosol optical depth, and clear-sky short wave radiation across the northern hemisphere and the U.S., was assessed through extensive comparisons of long-term simulations of these quantities with observation-derived records from 1990 to 2010 (Xing et al. 2015a,b; Gan et al., 2015b). The model captured declining Aerosol Optical Depth (AOD) trends along with the corresponding decreased top-of-atmosphere (TOA) short-wave radiation (SWR), or upwelling, and increased surface SWR, or downwelling, in the eastern US, Europe and the northern Atlantic for the 2000–2010 period. Estimates of the aerosol direct radiative effects (ADE) at TOA were comparable with those derived from measurements and, compared to general circulation models, the model exhibited better estimates of surface-aerosol direct radiative efficiency (Eτ) (Xing et al., 2015b).
Additionally, top-of-atmosphere clear-sky shortwave radiation during 2000-2010, inferred from the NASA Cloud and Earth’s Radiant Energy System (CERES) satellite retrievals, showed decreasing trends in the eastern U.S. and increasing trends in eastern China. The inclusion of ADE in WRF-CMAQ yielded better agreement with these contrasting trends suggesting that the trends in clear-sky radiation are influenced by trends in the tropospheric aerosol burden (Xing et al., 2015ab; Mathur et al., 2017).
Impacts of aerosol cooling are not limited to changes in surface temperature, since variation in atmospheric dynamics caused by the increased stability can worsen local air quality and impact human health (Xing et al., 2016).
Hemispheric WRF-CMAQ model simulation over two decades (1990−2010) shows enhanced surface PM2.5 concentrations in the most polluted regions of the world due to the aerosol direct effect (Xing et al., 2016).
13.4 Latest WRF-CMAQ Release#
Coupled WRF-CMAQv5.5 is compatible with WRF versions 4.4 to 4.5.1. EPA’s testing of WRF-CMAQ has included chemical mechanisms CB6r5 and CRACMMv1 with the M3DRY dry deposition scheme. Other model options can be used with the WRF-CMAQ model but will have limited user support for issues that are encountered.
A complete step by step build process and run instructions are provided in the WRF-CMAQ Tutorial.
WRF-CMAQ bug in v5.3 series#
A bug was identified within the CMAQ to WRF coupling routine (twoway_feedback.F90) where aerosol feedback information is transferred from CMAQ to WRF. In doing so, it was found that WRF was not receiving the correct aerosol feedback information in some cases due to a looping error relating to the number of layers. The bug impacts the WRF-CMAQ coupled system in the CMAQv5.3 release series (v5.3, v5.3.1, v5.3.2, v5.3.3) when running with short wave radiative feedback. The bug was not present in prior WRF-CMAQ versions. The bugfix in CMAQv5.4 (and all subsequent versions) correctly captures the variations in the aerosol optical properties and consequently the direct feedback effects through all layers. Users of WRF-CMAQv5.3 are strongly encouraged to update to CMAQv5.4 or later. See the WRF-CMAQ Bugfix Release Note for more information.
13.5 WRF-CMAQ Benchmark Test Case#
See the WRF-CMAQ Benchmark Tutorial for step-by-step instructions for running the 2 day benchmark case. The input files for the WRF-CMAQ benchmark case are provided in the base model benchmark inputs .tar file. Output WRF-CMAQ files associated with the sample run script for the coupled WRF-CMAQ model in this release package are provided in the base model benchmark outputs .tar file.
13.6 WRF Namelist Options#
As with the previous version of the coupled model (WRFv4.4-CMAQv5.4), all related runtime options are controlled via the WRF namelist under the &wrf_cmaq section. For convenience these options are set as runscript variables (look for the section labeled &wrf_cmaq in the sample runscript ) and automatically duplicated when creating the WRF namelist. There are five parameters with varying options (see below):
Name |
Value |
Description |
|---|---|---|
wrf_cmaq_option |
2 |
Dictates how the coupled model should be executed |
wrf_cmaq_freq |
5 |
Indicates how often WRF and CMAQ interact; |
met_file_tstep |
10000 |
Time step size of MCIP like intermediate output files (HHMMSS) |
direct_sw_feedback |
.true. |
Logical; whether to turn on/off aerosol shortwave direct effects |
feedback_restart |
.false. |
Logical; whether aerosol shortwave direct effect information is available in the WRF restart file |
If you have any questions, please contact David Wong at wong.david-c@epa.gov
13.7 References#
Bohren, C. F. and Huffman, D. R. (1983). Absorption and Scattering of Light by Small Particles, Wiley-Interscience, New York, USA, 530 pp.
Clough, S.A., Shephard, M. W., Mlawer, E. J., Delamere, J. S., Iacono, M. J., Cady-Pereira, K., Boukabara, S., & Brown, P. D. (2005). Atmospheric radiative transfer modeling: a summary of the AER codes. J. Quant. Spectrosc. Ra., 91, 233–244.
Gan, C., Binkowski, F., Pleim, J., Xing, J., Wong, D-C., Mathur, R., Gilliam, R. (2015a). Assessment of the Aerosol Optics Component of the Coupled WRF-CMAQ Model using CARES Field Campaign data and a Single Column Model. Atmospheric Environment, 115, 670-682. https://doi.org/10.1016/j.atmosenv.2014.11.028
Gan, C., Pleim, J., Mathur, R., Hogrefe, C., Long, C., Xing, J., Wong, D-C., Gilliam, R., Wei, C. (2015b). Assessment of long-term WRF–CMAQ simulations for understanding direct aerosol effects on radiation “brightening” in the United States. Atmospheric Chemistry and Physics, 15, 12193-12209. https://doi.org/10.5194/acp-15-12193-2015
Mathur, R., Pleim, J., Wong, D., Otte, T., Gilliam, R., Roselle, S., Young, J. (2011). Overview of the Two-way Coupled WRF-CMAQ Modeling System. 2011 CMAS Conference, Chapel Hill, NC. Presentation available from the CMAS conference website.
Mathur, R., Xing, J., Gilliam, R., Sarwar, G., Hogrefe, C., Pleim, J., Pouliot, G., Roselle, S., Spero, T. L., Wong, D. C., Young, J. (2017). Extending the Community Multiscale Air Quality (CMAQ) modeling system to hemispheric scales: overview of process considerations and initial applications, Atmos. Chem. Phys., 17, 12449–12474, https://doi.org/10.5194/acp-17-12449-2017
Wong, D.C., Pleim, J., Mathur, R., Binkowski, F., Otte, T., Gilliam, R., Pouliot, G., Xiu, A., Kang, D. (2012). WRF-CMAQ two-way coupled system with aerosol feedback: software development and preliminary results. Geosci. Model Dev., 5, 299-312. https://doi.org/10.5194/gmd-5-299-2012
Xing, J., Mathur, R., Pleim, J., Hogrefe, C., Gan, C.-M., Wong, D. C., Wei, C. (2015a). Can a coupled meteorology–chemistry model reproduce the historical trend in aerosol direct radiative effects over the Northern Hemisphere?, Atmos. Chem. Phys., 15, 9997–10018, https://doi.org/10.5194/acp-15-9997-2015
Xing, J., Mathur, R., Pleim, J., Hogrefe, C., Gan, C.-M., Wong, D., Wei, C., Wang, J. (2015b). Air pollution and climate response to aerosol direct radiative effects: a modeling study of decadal trends across the Northern Hemisphere, J. Geophys. Res.-Atmos., 120, 12221–12236, https://doi.org/10.1002/2015JD023933
Xing, J., Wang, J., Mathur, R., Pleim, J., Wang, S., Hogrefe, C., Gan, C.-M., Wong, D., Hao, J. (2016). Unexpected benefits of reducing aerosol cooling effects, Environ. Sci. Technol., 50, 7527– 7534, https://doi.org/10.1021/acs.est.6b00767
For an overview of the 2-way Coupled WRF-CMAQ see: http://www.cmascenter.org/conference/2011/slides/mathur_overview_two-way_2011.pptx
and for more details on the 2-way Coupled WRF-CMAQ system see: http://www.cmascenter.org/conference/2011/slides/wong_wrf-cmaq_two-way_2011.pptx
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CMAQv5.5 User’s Guide