Geoscientific Model Development Discussions www.geosci-model-dev-discuss.net 1991-9611 1991-962X 2 2 2009 10.5194/gmdd-2-1081-2009 http://www.geosci-model-dev-discuss.net/2/1081/2009/ http://www.geosci-model-dev-discuss.net/2/1081/2009/gmdd-2-1081-2009.html http://www.geosci-model-dev-discuss.net/2/1081/2009/gmdd-2-1081-2009.pdf 1081 1114 2009-07-30 Sensitivity of the Community Multiscale Air Quality (CMAQ) Model v4.7 results for the eastern United States to MM5 and WRF meteorological drivers K. W. Appel appel.wyat@epa.gov S. J. Roselle R. C. Gilliam J. E. Pleim Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory, Office of Research and Development, US Environmental Protection Agency, RTP, NC 27711, USA This paper presents a comparison of the operational performances of two Community Multiscale Air Quality (CMAQ) model v4.7 simulations that utilize input data from the 5th-generation Mesoscale Model (MM5) and the Weather Research and Forecasting (WRF) meteorological models. Two sets of CMAQ model simulations were performed for January and August 2006. One set utilized MM5 meteorology (MM5-CMAQ) and the other utilized WRF meteorology (WRF-CMAQ), while all other model inputs and options were kept the same. For January, predicted ozone (O₃) concentrations were higher in the Southeast and lower Mid-west regions in the WRF-CMAQ simulation, resulting in slightly higher bias and error as compared to the MM5-CMAQ simulations. The higher predicted O₃ concentrations are attributed to less dry deposition of O₃ in the WRF-CMAQ simulation due to differences in the calculation of the vegetation fraction between the MM5 and WRF models. The WRF-CMAQ results showed better performance for particulate sulfate (SO₄^2&minus;), similar performance for nitrate (NO₃^&minus;) and total nitrate (TNO₃), and slightly worse performance for total carbon (TC) and total fine particulate (PM_2.5) mass than the corresponding MM5-CMAQ results. For August, predictions of O₃ were notably higher in the WRF-CMAQ simulation, particularly in the southern United States, resulting in increased model bias. Concentrations of predicted particulate SO₄^2&minus; were lower in the region surrounding the Ohio Valley and higher along the Gulf of Mexico in the WRF-CMAQ simulation, contributing to poorer model performance. The primary cause of the differences in predicted concentrations between the MM5-CMAQ and WRF-CMAQ simulations is due to differences in the calculation of the friction velocity (<i>u</i>_*) in MM5 and WRF models, which has a large effect on the dry deposition of NO, NO₂ and HNO₃. Differences in the calculation of the vegetation fraction and the predicted cloud cover, along with several other minor differences in the simulations also affect the predicted concentrations from CMAQ. The performance for SO₄^2&minus;, NO₃^&minus; and NH₄⁺ wet deposition was similar for both simulations for January and August. Appel, K. W., Bhave, P. V., Gilliland, A. B., Sarwar, G., and Roselle, S. J.: Evaluation of the Community Multiscale Air Quality (CMAQ) model version 4.5: Sensitivities impacting model performance; Part II – particulate matter, Atmos. Environ., 42, 6057–6066, 2008. Appel, K. W., Gilliland, A. B., Sarwar, G., and Gilliam, R. C.: Evaluation of the Community Multiscale Air Quality (CMAQ) model version 4.5: Sensitivities impacting model performance: Part I – Ozone, Atmos. Environ., 41, 9603–9615, 2007. Appel, K. W. and Gilliam, R. C.: Overview of the Atmospheric Model Evaluation Tool (AMET). 7th Annual CMAS Conference, Chapel Hill, NC, 6–8~October~2008, http://www.cmascenter.org/conference/2008/agenda.cfm, 2008. Byun, D. W. and Schere, K. L.: Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system, Appl. Mech. Rev., 55, 51–77, 2006. Carlton, A. M. G., Bhave, P. V., Napelenok, S. L., Pinder, R. W., Sarwar, G., Pouliot, G. A., Edney, E. O., and Houyoux, M.: Improved Treatment of Secondary Organic Aerosols in CMAQ, Environ. Sci. Technol., submitted, 2009. de Meij, A., Gzella, A., Thunis, P., Cuvelier, C., Bessagnet, B., Vinuesa, J. F., and Menut, L.: The impact of MM5 and WRF meteorology over complex terrain on CHIMERE model calculations, Atmos. Chem. Phys. Discuss., 9, 2319–2380, 2009. Deng, A., Stauffer, D.R., Dudhia, J., Hunter, G.K., and Bruyere, C.: WRF-ARW analysis nudging update and future development plan. 9th Annual WRF Users' Workshop, Boulder, CO, 23–27~June~2008, http://www.mmm.ucar.edu/wrf/users/workshops/WS2008/abstracts/1-06.pdf. Dudhia, J.: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model, J. Atmos. Sci., 46, 3077–3107, 1989. ENVIRON: User's Guide to the Comprehensive Air Quality Model with Extensions (CAMx) Version 4.50. ENVIRON International Corporation, 773 San Marin Drive, Suite 2115 Novato, California 94998. Available at http://www.camx.com/files/CAMxUsersGuide_v4.50.pdf, 2008. Fulton, R. A., Breidenbach, J. P., Seo, D. J., Miller, D. A., and O'Bannon, T.: The WSR-88D rainfall algorithm, Weather Forecasting, 13, 377–395, 1998. Gilliam, R. C. and Pleim, J. E.: Performance assessment of new land-surface and planetary boundary layer physics in the WRF-ARW, J. Appl. Meteor. Clim., in review, 2009. Grell, G. A., Dudhia, A. J., and Stauffer, D. R.: A description of the Fifth-Generation PennState/NCAR Mesoscale Model (MM5). NCAR Technical Note NCAR/TN-398+STR. Available at http://www.mmm.ucar.edu/mm5/doc1.html, 1994. Jiang, W., Smyth, S., Giroux, E., Roth, H., and Yin, D.: Differences between CMAQ fine mode particle and PM$_2.5$ concentrations and their impact on model performance evaluation in the lower Fraser valley, Atmos. Environ., 40, 4973–4985, 2006. Kain, J. S.: The Kain-Fritsch convective parameterization: An update, J. Appl. Meteor., 43, 170–181, 2004. Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the long-wave, J. Geophys. Res., 102(D14), 16663–16682, 1997. Otte, T. L., Pouliot, G., Pleim, J. E., Young, J. O., Schere, K. L., Wong, D. C., Lee, P. C. S., Tsidulko, M., McQueen, J. T., Davidson, P., Mathur, R., Chuang, H. Y., DiMego, G., and Seaman, N. L.: Linking the Eta model with the Community Multiscale Air Quality (CMAQ) modeling system to build a national air quality forecasting system, Weather Forecasting, 20, 367–384, 2005. Pleim, J. E. and Xiu, A.: Development and testing of a surface flux and planetary boundary layer model for application in mesoscale models, J. Appl. Meteor., 34, 16–32, 1995. Pleim, J. E. and Xiu, A.: Development of a Land-surface Model. Part II: Data Assimilation, J. Appl. Meteor., 42, 1811–1822, 2003. Pleim, J. E.: A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: model description and testing, J. Appl. Meteor. Clim., 46, 1383–1395, 2007a. Pleim, J. E.: A combined local and nonlocal closure model for the atmospheric boundary layer, Part II: application and evaluation in a mesoscale meteorological model, J. Appl. Meteor. Clim., 46, 1396–1409, 2007b. Reisner, J., Rasmussen, R. M., and Bruintjes, R. T.: Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model, Q. J. Roy. Meteor. Soc., 124, 1071–1107, 1998. Seo, D. J.: Real-time estimation of rainfall fields using rain gauge data under fractional coverage conditions, J. Hydrol., 208, 25–36, 1998a. Seo, D. J.: Real-time estimation of rainfall fields using radar rainfall and rain gauge data, J. Hydrol., 208, 37–52, 1998b. Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda, M. G., Huang, X.-Y., Wang, W., and Powers, J. G.: A description of the advanced research WRF version 3. NCAR Tech Note NCAR/TN 475 STR, 125 pp., [available from UCAR Communications, P.O Box~3000, Boulder, CO 80307, USA], 2008. Smyth, S. C., Yin, D., Roth, H., Jiang, W., Moran, M. D., and Crevier, L. P.: The impact of GEM and MM5 modeled meteorological conditions on CMAQ air quality modeling results in Eastern Canada and the Northeastern United States, J. Appl. Meteor. Clim., 45, 1525–1541, 2006. Thompson, G., Rasmussen, R. M., and Manning, K.: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis, Mon. Weather Rev., 132, 519–542, 2004. Xiu, A. and Pleim, J. E.: Development of a land-surface model. Part I: application in a mesoscale meteorological model, J. Appl. Meteor., 40, 192–209, 2001. Yarwood, G., Roa, S., Yocke, M., and Whitten, G.: Updates to the carbon bond chemical mechanism: CBo5. Final report to the US EPA, RT-0400675, available at http://www.camx.com, 2005.