Impact of gas-phase mechanisms on Weather Research Forecasting Model with Chemistry (WRF/Chem) predictions: Mechanism implementation and comparative evaluation

Journal of Geophysical Research Atmospheres

Volumn 117, Issue 1, 2012, Pages

  Zhang, Yang ^a   Chen, Yaosheng ^a   Sarwar, Golam ^b   Schere, Kenneth ^b  

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

^b U S ENVIRONMENTAL PROTECTION AGENCY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ATMOSPHERIC AEROSOLS; ATMOSPHERIC CHEMISTRY; ATMOSPHERIC HUMIDITY; CLIMATE MODELS; DROPS; FEEDBACK; GASES; NITROGEN OXIDES; OZONE; PRECIPITATION (METEOROLOGY); RADIATION EFFECTS; REAL VARIABLES; SPATIAL DISTRIBUTION;

AEROSOL GROWTH; AEROSOL MASS; AEROSOL OPTICAL DEPTHS; ATMOSPHERIC PROCESS; CHEMICAL SPECIES; CHEMICAL TRANSPORT; CLOUD CONDENSATION NUCLEI; CLOUD DROPLET NUMBER; CLOUD DROPLETS; CLOUD MICROPHYSICS; CLOUD OPTICAL THICKNESS; CLOUD WATER; CLOUDY CONDITIONS; COMPARATIVE EVALUATIONS; FEEDBACK MECHANISMS; FORECASTING MODELS; GAS PHASE CHEMISTRY; GAS-PHASE MECHANISM; GASEOUS PRECURSORS; HOMOGENEOUS NUCLEATION; INDIRECT EFFECTS; MASS CONCENTRATION; METEOROLOGICAL PREDICTION; METEOROLOGICAL VARIABLES; MODEL REPRESENTATION; NEW PARTICLE FORMATION; NUMBER CONCENTRATION; PARAMETERIZATIONS; RADIATIVE PROCESS; REANALYSIS; REGULATORY APPLICATIONS; SATELLITE DATA; SECONDARY AEROSOLS; SHORT-WAVE RADIATION; SURFACE CONCENTRATION; SURFACE LAYERS; SURFACE OBSERVATION; TEMPERATURE AND RELATIVE HUMIDITY; TROPOSPHERIC OZONE; WEATHER RESEARCH; WIND SPEED;

WEATHER FORECASTING;

AEROSOL FORMATION; AIR TEMPERATURE; ATMOSPHERIC CHEMISTRY; ATMOSPHERIC MODELING; CARBON MONOXIDE; CLIMATE FEEDBACK; CLIMATE PREDICTION; CLOUD CONDENSATION NUCLEUS; CLOUD WATER; COMPARATIVE STUDY; DROPLET; ERROR ANALYSIS; GAS PHASE REACTION; NITROGEN DIOXIDE; NUCLEATION; OPTICAL DEPTH; ORGANIC MATTER; OXIDANT; OZONE; PARAMETERIZATION; PARTICULATE MATTER; RELATIVE HUMIDITY; SATELLITE DATA; SHORTWAVE RADIATION; SPATIAL DISTRIBUTION; TROPOSPHERE; UNCERTAINTY ANALYSIS; WEATHER FORECASTING; WIND VELOCITY;

UNITED STATES;

EID: 84862932190     PISSN: 01480227     EISSN: None     Source Type: Journal    
DOI: 10.1029/2011JD015775     Document Type: Article

References (122)

1. Abdul-Razzak, H., and S. J. Ghan (2002), A parameterization of aerosol activation. 3. Sectional representation, J. Geophys. Res., 107(D3), 4026, doi:10.1029/2001JD000483.
2. Arteta, J., S. Cautenet, M. Taghavi, and N. Audiffren (2006), Impact of two chemistry mechanisms fully coupled with mesoscale model on the atmospheric pollutants distribution, Atmos. Environ., 40, 7983-8001, doi:10.1016/j.atmosenv. 2006.06.050. (Pubitemid 44781206)
3. Audiffren, N., E. Buisson, S. Cautenet, and N. Chaumerliac (2004), Photolytic impact of a stratocumulus cloud layer upon the chemistry of an offshore advected plume of pollutants during the NARE 1993 intensive experiment: A numerical study, Atmos. Res., 70, 89-108, doi:10.1016/j. atmosres.2004.01. 004. (Pubitemid 38549673)
4. Bennartz, R. (2007), Global assessment of marine boundary layer cloud droplet number concentration from satellite, J. Geophys. Res., 112, D02201, doi:10.1029/2006JD007547. (Pubitemid 47260876)
5. Binkowski, F. S., and S. J. Roselle (2003), Models-3 Community Multiscale Air Quality (CMAQ) model aerosol component: 1. Model description, J. Geophys. Res., 108(D6), 4183, doi:10.1029/2001JD001409.
6. Boersma, K. F., H. J. Eskes, and E. J. Brinksma (2004), Error analysis for tropospheric NO2 retrieval from space, J. Geophys. Res., 109, D04311, doi:10.1029/2003JD003962.
7. Brulfert, G., C. Chemel, E. Chaxel, and J. P. Chollet (2005), Modelling photochemistry in alpine valleys, Atmos. Chem. Phys., 5, 2341-2355, doi:10.5194/acp-5-2341-2005. (Pubitemid 41479774)
8. Byun, D., and K. L. Schere (2006), Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system, Appl. Mech. Rev., 59, 51-77, doi:10.1115/1.2128636. (Pubitemid 46132191)
9. Carter, W. P. L. (2010), Development of the SAPRC-07 chemical mechanism, Atmos. Environ., 44, 5324-5335, doi:10.1016/j.atmosenv.2010. 01.026.
10. CASTNET (2005), Clean Air Status and Trends Network (CASTNET) 2004 Annual Report, 72 pp., MACTEC Eng. and Consult. for U.S. Environ. Prot. Agency, Washington, D. C. [Available at http://epa.gov/castnet/javaweb/docs/annual- report-2004.pdf.]
11. Chapman, E. G., W. I. Gustafson Jr., R. C. Easter, J. C. Barnard, S. J. Ghan, M. S. Pekour, and J. D. Fast (2009), Coupling aerosol-cloud-radiative processes in the WRF-Chem model: Investigating the radiative impact of elevated point sources, Atmos. Chem. Phys., 9, 945-964, doi:10.5194/acp-9-945-2009.
12. Chen, F., and J. Dudhia (2001), Coupling an advanced land surface- hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity, Mon. Weather Rev., 129, 569-585, doi:10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2. (Pubitemid 32511917)
13. Chen, S.-H., and W.-Y. Sun (2002), A one-dimensional time dependent cloud model, J. Meteorol. Soc. Jpn., 80, 99-118, doi:10.2151/jmsj.80.99.
14. Chen, S., X. Ren, J. Mao, Z. Chen, W.H. Brune, B. Lefer, B. Rappenglück, J. Flynn, J. Olson, and J.H. Crawford (2009), A comparison of chemical mechanisms based on TRAMP-2006 field data, Atmos. Environ., 44, 4116-4125, doi:10.1016/j.atmosenv.2009.05.027.
15. Chou, M.-D., and M. J. Suarez (1999), A Solar Radiation Parameterization for Atmospheric Studies, Tech. Rep. Ser. on Global Model. and Data Assimilation, vol. 15, NASA/TM-1999-104606, 51 pp., NASA Goddard Space Flight Cent., Greenbelt, Md.
16. Chou, M. D., M. J. Suarez, C.H. Ho, M. M.H. Yan, and K. T. Lee (1998), Parameterizations for cloud overlapping and shortwave single-scattering properties for use in general circulation and cloud ensemble models, J. Clim., 11, 202-214, doi:10.1175/1520-0442(1998)011<0202:PFCOAS>2.0.CO;2
17. Chuang, M.-T., Y. Zhang, and D.-W. Kang (2011), Application of WRF/Chem-MADRID for real-time air quality forecasting over the Southeastern United States, Atmos. Environ., 45, 6241-6250, doi:10.1016/j.atmosenv.2011.06. 071.
18. Davis, J. M., P. V. Bhave, and K. M. Foley (2008), Parameterization of N2O5 reaction probabilities on the surface of particles containing ammonium, sulfate, and nitrate, Atmos. Chem. Phys., 8, 5295-5311, doi:10.5194/acp-8-5295-2008.
19. Deeter, M. N., D. P. Edwards, J. C. Gille, and J. R. Drummond (2009), CO retrievals based on MOPITT near-infrared observations, J. Geophys. Res., 114, D04303, doi:10.1029/2008JD010872.
20. Derwent, R. G. (1990), Evaluation of a number of chemical mechanisms for their application in models describing the formation of photochemical ozone in Europe, Atmos. Environ., Part A, 24, 2615-2624. (Pubitemid 20320538)
21. Derwent, R. G. (1993), Evaluation of the chemical mechanism employed in the EMEP photochemical oxidant model, Atmos. Environ., Part A, 27, 277-279.
22. Desert Research Institute (DRI) (2002a), Performance audit of meteorological instruments, DRI SOP #4-104.2, Desert Res. Inst. Div. of Atmos. Sci., Reno, Nev. [Available at http://www.atmospheric-research.com/PDFs/ AuditSOPs/DRI%20Met%20Audit%20SOP.pdf.]
23. Desert Research Institute (DRI) (2002b), Performance audit of continuous ozone analyzers, DRI SOP #4-101.2, Desert Res. Inst. Div. of Atmos. Sci., Reno, Nev. [Available at http://www.atmospheric-research.com/PDFs/AuditSOPs/ DRI%20Ozone%20Audit%20SOP.pdf.]
24. Desert Research Institute (DRI) (2002c), Performance audit of continuous gas analyzers, DRI SOP #4-101.3, Desert Res. Inst. Div. of Atmos. Sci., Reno, Nev. [Available at http://www.atmospheric-research.com/PDFs/AuditSOPs/ DRI%20Trace%20Gas%20Audit%20SOP.pdf.]
25. Desert Research Institute (DRI) (2002d), Performance audit of Rupprecht and Patashnick Tapered Element Oscillating Microbalance (TEOM), DRI SOP # 4-111.1, Desert Res. Inst. Div. of Atmos. Sci., Reno, Nev. [Available at http://www.atmospheric-research.com/PDFs/AuditSOPs/DRI%20TEOM%20Audit%20SOP.pdf. ]
26. Desert Research Institute (DRI) (2002e), Performance audit of continuous particulate sulfate, nitrate, and ammonium samplers, DRI SOP # 4-116.1, Desert Res. Inst. Div. of Atmos. Sci., Reno, Nev. [Available at http://www.atmospheric- research.com/PDFs/AuditSOPs/DRI%20SO4-NO3- NH4%20Audit%20SOP.pdf.
27. Desert Research Institute (DRI) (2002f), Performance audit of Rupprecht and Patashnick carbon analyzer, Model 5400, DRI SOP #4-110.1, Desert Res. Inst. Div. of Atmos. Sci., Reno, Nev. [Available at http://www.atmospheric- research.com/PDFs/AuditSOPs/DRI%20Carbon%20Audit% 20SOP.pdf.]
28. Edwards, D. P., et al. (2004), Observations of carbon monoxide and aerosols from the Terra satellite: Northern Hemisphere variability, J. Geophys. Res., 109, D24202, doi:10.1029/2004JD004727. Ek, M. B., K. B. Mitchell, Y. Lin, B. Rogers, P. Grunmann, V. Koren,
29. G. Gayno, and J. D. Tarpley (2003), Implementation of NOAH land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res., 108(D22), 8851, doi:10.1029/2002JD003296.
30. Emmerson, K. M., and M. J. Evans (2009), Comparison of tropospheric gas-phase chemistry schemes for use within global models, Atmos. Chem. Phys., 9, 1831-1845, doi:10.5194/acp-9-1831-2009.
31. Emmons, L. K., G. G. Pfister, D. P. Edwards, J. C. Gille, G. Sachse, D. Blake, S. Wofsy, C. Gerbig, D. Matross, and P. Nédélec (2007), Measurements of Pollution in the Troposphere (MOPITT) validation exercises during summer 2004 field campaigns over North America, J. Geophys. Res., 112, D12S02, doi:10.1029/2006JD007833. (Pubitemid 47241659)
32. Fahey, K. M., and S. N. Pandis (2001), Optimizing model performance: Variable size resolution in cloud chemistry modeling, Atmos. Environ., 35, 4471-4478, doi:10.1016/S1352-2310(01)00224-2.
33. Faraji, M., Y. Kimura, E. McDonald-Buller, and D. Allen (2008), Comparison of the carbon bond and SAPRC photochemical mechanisms under conditions relevant to southeast Texas, Atmos. Environ., 42, 5821-5836, doi:10.1016/j.atmosenv.2007.07.048. (Pubitemid 351952351)
34. Fast, J. D., W. I. Gustafson Jr., R. C. Easter, R. A. Zaveri, J. C. Barnard, E. G. Chapman, G. A. Grell, and S. E. Peckham (2006), Evolution of ozone, particulates, and aerosol direct radiative forcing on the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model, J. Geophys. Res., 111, D21305, doi:10.1029/2005JD006721. (Pubitemid 46978606)
35. Gao, B.-C., and Y. J. Kaufman (2003), Water vapor retrievals using Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared channels, J. Geophys. Res., 108(D13), 4389, doi:10.1029/2002JD003023.
36. Gery, M. W., G. Z. Whitten, J. P. Killus, and M. C. Dodge (1989), A photochemical kinetics mechanism for urban and regional scale computer modeling, J. Geophys. Res., 94(D10), 12,925-12,956, doi:10.1029/JD094iD10p12925.
37. Ghan, S. J., L. R. Leung, R. C. Easter, and H. Abdul-Razzak (1997), Prediction of cloud droplet number in a general circulation model, J. Geophys. Res., 102(D18), 21,777-21,794, doi:10.1029/97JD01810.
38. Gong, S. L., L. A. Barrie, and M. Lazare (2002), Canadian Aerosol Module (CAM): A size-segregated simulation of atmospheric aerosol processes for climate and air quality models: 2. Global sea-salt aerosol and its budgets, J. Geophys. Res., 107(D24), 4779, doi:10.1029/2001JD002004. (Pubitemid 44793946)
39. Grell, G. A., and D. Devenyi (2002), A generalized approach to parameterizing convection combining ensemble and data assimilation techniques, Geophys. Res. Lett., 29(14), 1693, doi:10.1029/2002GL015311.
40. Grell, G. A., S. Emeis, W. R. Stockwell, T. Schoenemeyer, R. Forkel, J. Michalakes, R. Knoche, and W. Seidl (2000), Application of a multiscale, coupled MM5/chemistry model to the complex terrain of the VOTALP valley campaign, Atmos. Environ., 34, 1435-1453, doi:10.1016/S1352- 2310(99)00402-1. (Pubitemid 30089690)
41. Grell, G. A., S. E. Peckham, R. Schmitz, S. A. McKeen, G. Frost, W. C. Skamarock, and B. Eder (2005), Fully coupled "online" chemistry within the WRF model, Atmos. Environ., 39, 6957-6975, doi:10.1016/j. atmosenv.2005.04.027. (Pubitemid 41539465)
42. Gross, A., and W. R. Stockwell (2003), Comparison of the EMEP, RADM2 and RACM mechanisms, J. Atmos. Chem., 44, 151-170, doi:10.1023/A:1022483412112. (Pubitemid 36394905)
43. Gustafson, W. I., Jr., E. G. Chapman, S. J. Ghan, R. C. Easter, and J. D. Fast (2007), Impact on modeled cloud characteristics due to simplified treatment of uniform cloud condensation nuclei during NEAQS 2004, Geophys. Res. Lett., 34, L19809, doi:10.1029/2007GL030021. (Pubitemid 350263042)
44. Hansen, D. A., E. S. Edgerton, B. E. Hartsell, J. J. Jansen, N. Kandasamy, G. M. Hidy, and C. L. Blanchard (2003), The southeastern aerosol research and characterization study: Part 1. Overview, J. Air Waste Manage. Assoc., 53, 1460-1471. (Pubitemid 37517930)
45. Hong, S., Y. Noh, and J. Dudhia (2006), A new vertical diffusion package with an explicit treatment of entrainment processes, Mon. Weather Rev., 134, 2318-2341, doi:10.1175/MWR3199.1. (Pubitemid 44445432)
46. Hough, A. M. (1988), An intercomparison of mechanisms for the production of photochemical oxidants, J. Geophys. Res., 93(D4), 3789-3812, doi:10.1029/JD093iD04p03789.
47. Hyer, E. J., J. S. Reid, and J. Zhang (2010), An over-land aerosol optical depth data set for data assimilation by filtering, correction, and aggregation of MODIS Collection 5 optical depth retrievals, Atmos. Meas. Tech. Discuss., 3, 4091-4167, doi:10.5194/amtd-3-4091-2010.
48. Jacobson, M. Z. (2005), A solution to the problem of nonequilibrium acid/base gas-particle transfer at long time step, Aerosol Sci. Technol., 39, 92-103, doi:10.1080/027868290904546. (Pubitemid 40279437)
49. Jacobson, M. Z., R. P. Turco, E. J. Jensen, and O. B. Toon (1994), Modeling coagulation among particles of different composition and size, Atmos. Environ., 28, 1327-1338, doi:10.1016/1352-2310(94)90280-1.
50. Janjic, Z. I. (2001), Nonsingular Implementation of the Mellor-Yamada Level 2.5 Scheme in the NCEP Meso Model, NCEP Off. Note 437, 61 pp., Natl. Cent. for Environ. Predict., Camp Springs, Md.
51. Janssen, R.H. H., L. N. Ganzeveld, P. Kabat, M. Kulmala, T. Nieminen, and R. A. Roebeling (2011), Estimating seasonal variations in cloud droplet number concentration over the boreal forest from satellite observations, Atmos. Chem. Phys., 11, 7701-7713, doi:10.5194/acp-11-7701- 2011.
52. Jimenez, P., J. M. Baldasano, and D. Dabdub (2003), Comparison of photochemical mechanisms for air quality modeling, Atmos. Environ., 37, 4179-4194, doi:10.1016/S1352-2310(03)00567-3. (Pubitemid 37020955)
53. Kanakidou, M., et al. (2005), Organic aerosol and global climate modeling: A review, Atmos. Chem. Phys., 5, 1053-1123, doi:10.5194/acp-5-1053- 2005. (Pubitemid 40560480)
54. Karamchandani, P., Y. Zhang, S.-Y. Chen, and R. Balmori-Bronson (2011), Development of an extended chemical mechanism for global-throughurban applications, Atmos. Pollut. Res., doi:10.5094/APR.2011.047, in press.
55. Kim, Y., K. Sartelet, and C. Seigneur (2009), Comparison of two gas-phase chemical kinetic mechanisms of ozone formation over Europe, J. Atmos. Chem., 62, 89-119, doi:10.1007/s10874-009-9142-5.
56. Kim, Y., K. Sartelet, and C. Seigneur (2011a), Formation of secondary aerosols: impact of the gas-phase chemical mechanism, Atmos. Chem. Phys., 11, 583-598, doi:10.5194/acp-11-583-2011.
57. Kim, Y., F. Couvidat, K. Sartelet, and C. Seigneur (2011b), Comparison of different gas-phase mechanisms and aerosol modules for simulating particulate matter formation, J. Air Waste Manage. Assoc., 61, 1218-1226, doi:10.1080/10473289.2011.603999.
58. Kuhn, M., et al. (1998), Intercomparison of the gas-phase chemistry in several chemistry and transport models, Atmos. Environ., 32, 693-709, doi:10.1016/S1352-2310(97)00329-4. (Pubitemid 28142516)
59. Li, Z., and A. P. Trishchenko (2001), Quantifying uncertainties in determining SW cloud radiative forcing and cloud absorption due to variability in atmospheric conditions, J. Atmos. Sci., 58, 376-389, doi:10.1175/1520- 0469(2001)058<0376:QUIDSC>2.0.CO;2. (Pubitemid 32511771)
60. Liang, J., B. Jackson, and A. Kaduwela (2006), Evaluation of the ability of indicator species ratios to determine the sensitivity of ozone to reductions in emissions of volatile organic compounds and oxides of nitrogen in northern California, Atmos. Environ., 40, 5156-5166, doi:10.1016/j. atmosenv.2006.03.060. (Pubitemid 44067513)
61. Liebmann, B., and C. A. Smith (1996), Description of a complete (interpolated) outgoing longwave radiation dataset, Bull. Am. Meteorol. Soc., 77, 1275-1277.
62. Lin, Y.-L., R. D. Farley, and H. D. Orville (1983), Bulk parameterization of the snow field in a cloud model, J. Clim. Appl. Meteorol., 22, 1065-1092, doi:10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2.
63. Liu, P., and Y. Zhang (2011), Use of a process analysis tool for diagnostic study on fine particulate matter predictions in the U.S. Part I: Model evaluation using surface, aircraft, and satellite data, Atmos. Pollut. Res., 2(1), 49-60, doi:10.5094/APR.2011.007.
64. Liu, Y., P.H. Daum, and R. L. McGraw (2005), Size truncation effect, threshold behavior, and a new type of autoconversion parameterization, Geophys. Res. Lett., 32, L11811, doi:10.1029/2005GL022636. (Pubitemid 41174850)
65. Lu, C.-H., and J. S. Chang (1998), On the indicator-based approach to assess ozone sensitivities and emissions features, J. Geophys. Res., 103, 3453-3462, doi:10.1029/97JD03128. (Pubitemid 28400473)
66. Luecken, D. J., S. Phillips, G. Sarwar, and C. Jang (2008), Effects of using the CB05 vs. SAPRC99 vs. CB4 chemical mechanism on model predictions: Ozone and gas-phase photochemical precursor concentrations, Atmos. Environ., 42, 5805-5820, doi:10.1016/j.atmosenv.2007.08.056. (Pubitemid 351952353)
67. McMurry, P.H., and S. K. Friedlander (1979), New particle formation in the presence of an aerosol, Atmos. Environ., 13, 1635-1651, doi:10.1016/0004- 6981(79)90322-6. (Pubitemid 10159480)
68. McPeters, R. D., et al. (1998), Earth Probe Total Ozone Mapping Spectrometer (TOMS) Data Products User's Guide, NASA Tech. Publ. 1998-206895, 64 pp., NASA Goddard Space Flight Cent., Greenbelt, Md. [Available at http://cedadocs.badc.rl.ac.uk/107/1/earthprobe-userguide. pdf.].
69. Miao, J.-F., D. Chen, K. Wyser, K. Borne, J. Lindgren, M. K. S. Strandevall, S. Thorsson, C. Achberger, and E. Almkvist (2008), Evaluation of MM5 mesoscale model at local scale for air quality applications over the Swedish west coast: Influence of PBL and LSM parameterizations, Meteorol. Atmos. Phys., 99, 77-103, doi:10.1007/s00703-007-0267-2.
70. Milford, J. B., D. Gao, S. Sillman, P. Blossey, and A. G. Russell (1994), Total reactive nitrogen (NOy) as an indicator of the sensitivity of ozone to reductions in hydrocarbon and NOx emissions, J. Geophys. Res., 99(D2), 3533-3542, doi:10.1029/93JD03224. (Pubitemid 24403959)
71. Minvielle, F., et al. (2004), Modelling the transport of aerosols during INDOEX 1999 and comparison with experimental data. Part 2: Continental aerosols and their optical depth, Atmos. Environ., 38, 1823-1837, doi:10.1016/j.atmosenv. 2003.12.033. (Pubitemid 38292964)
72. Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough (1997), Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res., 102 (D14), 16,663-16,682, doi:10.1029/97JD00237.
73. Monin, A. S., and A. M. Obukhov (1954), Basic laws of turbulent mixing in the surface layer of the atmosphere [in Russian], Tr. Geophiz. Inst. Akad. Nauk. SSSR, 24(151), 163-187.
74. Office of Air Quality Planning and Standards (OAQPS) (1999), Quality Assurance Project Plan: PM2.5 Speciation Trends Network Field Sampling (Final Draft), U.S. Environ. Prot. Agency, Research Triangle Park, N. C.
75. Office of Air Quality Planning and Standards (OAQPS) (2000), Quality Assurance Guidance Document, Rep. EPA-454/R-01-001, U.S. Environ. Prot. Agency, Research Triangle Park, N. C.
76. Office of Air Quality Planning and Standards (OAQPS) (2002), IMPROVE: Interagency Monitoring of Protected Visual Environments Quality Assurance Project Plan, U.S. Environ. Prot. Agency, Research Triangle Park, N. C. [Available at http://vista.cira.colostate.edu/IMPROVE/Publications/QA-QC/ IMPROVE-QAPP-R0.pdf.]
77. Office of Air Quality Planning and Standards (OAQPS) (2007), Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze, Rep. EPA- 454/B-07-002, U.S. Environ. Prot. Agency, Research Triangle Park, N. C. [Available at http://www.epa.gov/scram001/guidance/guide/final- 03-pm-rh-guidance.pdf.]
78. Office of Air Quality Planning and Standards (OAQPS) (2008), Quality Assurance Handbook for Air Pollution Measurement Systems, Vol. II: Ambient Air Quality Monitoring Program, Rep. EPA-454/B-08-003, U.S. Environ. Prot. Agency, Research Triangle Park, N. C. [Available at http://www.epa.gov/ttn/amtic/files/ ambient/pm25/qa/QA-Handbook-Vol-II. pdf.]
79. Olson, J., et al. (1997), Results from the Intergovernmental Panel on Climate Change Photochemical Model Intercomparison (PhotoComp), J. Geophys. Res., 102(D5), 5979-5991, doi:10.1029/96JD03380.
80. Otkin, J. A., and T. J. Greenwald (2008), Comparison of WRF modelsimulated and MODIS-derived cloud data, Mon. Weather Rev., 136, 1957-1970, doi:10.1175/2007MWR2293.1.
81. Otte, T. L. (2008a), The impact of nudging in the meteorological model for retrospective air quality simulations. Part II: Evaluating collocated meteorological and air quality observations, J. Appl. Meteorol. Climatol., 47, 1868-1887, doi:10.1175/2007JAMC1791.1.
82. Otte, T. L. (2008b), The impact of nudging in the meteorological model for retrospective air quality simulations. Part I: Evaluation against national observational networks, J. Appl. Meteorol. Climatol., 47, 1853-1867, doi:10.1175/2007JAMC1790.1.
83. Pincus, R., S. Platnick, S. A. Ackerman, R. S. Hemler, and R. J. P. Hofmann (2011), Reconciling simulated and observed views of clouds: MODIS, ISCCP, and the limits of instrument simulators, J. Clim., in press.
84. Pun, B. K., C. Seigneur, J. Pankow, E. Chang, R. Griffin, and E. Knipping (2005), An upgraded absorptive secondary organic aerosol partitioning module for three-dimensional air quality applications, paper presented at the Twenty-Fourth Annual AAAR Conference, Austin, Tex., 17-21 October.
85. Remer, L. A., et al. (2005), The MODIS aerosol algorithm, products, and validation, J. Atmos. Sci., 62, 947-973, doi:10.1175/JAS3385.1. (Pubitemid 40659709)
86. Roy, B., R. Mathur, A. B. Gilliland, and S. C. Howard (2007), A comparison of CMAQ-based aerosol properties with IMPROVE, MODIS, and AERONET data, J. Geophys. Res., 112, D14301, doi:10.1029/2006JD008085. (Pubitemid 47433819)
87. Salzmann, M. (2007), Using KPP generated chemistry solvers in WRFChem, presented at the Eighth WRF Users' Workshop, Boulder, Colo., 11-15 June.
88. Salzmann, M. (2008), WRF-Chem/KPP Coupler (WKC) for WRF V3, Users' and Developers Guide v2.0, Princeton Univ. Press, Princeton, N. J.
89. Sanjay, J. (2008), Assessment of atmospheric boundary-layer processes represented in the numerical model MM5 for a clear sky day using LASPEX observations, Boundary Layer Meteorol., 129, 159-177, doi:10.1007/s10546-008- 9298-6.
90. Sarwar, G., D. Luecken, G. Yarwood, G. Z. Whitten, and W. P. L. Carter (2008), Impact of an updated carbon bond mechanism and predictions from the CMAQ modeling system: Preliminary assessment, J. Appl. Meteorol. Climatol., 47, 3-14, doi:10.1175/2007JAMC1393.1. (Pubitemid 351351462)
91. Sarwar, G., K. W. Appel, A. G. Carlton, R. Mathur, K. Schere, R. Zhang, and M. Majeed (2011), Impact of a new condensed toluene mechanism on air quality model predictions in the US, Geosci. Model Dev., 4, 183-193, doi:10.5194/gmd-4-183-2011.
92. Seethala, C. (2011), Cloud liquid water path from spaceborne measurements, paper presented at Climate Observation Science Meeting, KNMI, De Bilt, Netherlands, 17 January.
93. Seinfeld, J.H., and J. F. Pankow (2003), Organic atmospheric particulate material, Annu. Rev. Phys. Chem., 54, 121-140, doi:10.1146/annurev. physchem.54.011002.103756.
94. Sillman, S. (1995), The use of NOy, H2O2, and HNO3 as indicators for ozone-NOx-hydrocarbon sensitivity in urban locations, J. Geophys. Res., 100(D7), 14,175-14,188, doi:10.1029/94JD02953.
95. Sillman, S., D. He, C. Cardelino, and R. E. Imhoff (1997), The use of photochemical indicators to evaluate ozone-NOx-hydrocarbon sensitivity: Case studies from Atlanta, New York, and Los Angeles, J. Air Waste Manage. Assoc., 47, 642-652.
96. Skamarock, W. C., and M. L. Weisman (2009), The impact of positivedefinite moisture transport on NWP precipitation forecasts, Mon. Weather Rev., 137, 488-494, doi:10.1175/2008MWR2583.1.
97. Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers (2005), A Description of the Advanced Research WRF Version 2, Tech. Note NCAR/TN-468+STR, 88 pp., Natl. Cent. for Atmos. Res., Boulder, Colo. [Available at http://wrf-model.org/wrfadmin/publications.php.].
98. Southeastern Aerosol Research and Characterization Study (SEARCH) (2003), Search methodology for construction of pie and bar charts using PM2.5 speciation data, SEARCH data and metric protocols, Atmos. Res. and Anal., Inc., Plano, Tex. [Available at http://www.atmosphericresearch. com/method/index.html. ]
99. Tarasova, T. A., J. P. R. Fernandez, I. A. Pisnichenko, J. A. Marengo, J. C. Ceballos, and M. J. Bottino (2006), Impact of new solar radiation parameterization in the Eta model on the simulation of summer climate over South America, J. Appl. Meteorol. Climatol., 45, 318-333, doi:10.1175/JAM2342.1.
100. Tonnesen, G. S., and R. L. Dennis (2000a), Analysis of radical propagation efficiency to assess ozone sensitivity to hydrocarbons and NO x 1. Local indicators of instantaneous odd oxygen production sensitivity, J. Geophys. Res., 105(D7), 9213-9225, doi:10.1029/1999JD900371.
101. Tonnesen, G. S., and R. L. Dennis (2000b), Analysis of radical propagation efficiency to assess ozone sensitivity to hydrocarbons and NO x 2. Longlived species as indicators of ozone concentration sensitivity, J. Geophys. Res., 105(D7), 9227-9241, doi:10.1029/1999JD900372.
102. Turpin, B. J., and H. J. Lim (2001), Species contributions to PM2.5 mass concentrations: revisiting common assumptions for estimating organic mass, Aerosol Sci. Technol., 35, 602-610. (Pubitemid 32606003)
103. U.S. Environmental Protection Agency (EPA) (1983), Quality Assurance Handbook for Air Pollution Measurement Systems: Volume 5. Manual for Precipitation Measurement Systems, Rep. EPA-600/4-82-042a&b, U.S. Environ. Prot. Agency, Research Triangle Park, N. C. [Available at http://nepis.epa.gov/ EPA/html/Pubs/pubalpha-Q.html.]
104. White, W.H., and P. T. Roberts (1977), On the nature and origins of visibility- reducing aerosols in the Los Angeles air basin, Atmos. Environ., 11, 803-812, doi:10.1016/0004-6981(77)90042-7. (Pubitemid 8376208)
105. Whitten, G. Z., G. Heo, Y. Kimura, E. McDonald-Buller, D. T. Allen, W. P. L. Carter, and G. Yarwood (2010), A new condensed toluene mechanism for Carbon Bond: CB05-TU, Atmos. Environ., 44, 5346-5355, doi:10.1016/j.atmosenv.2009.12. 029.
106. Wild, O., X. Zhu, and M. J. Prather (2000), Fast-J: Accurate simulation of in- and below-cloud photolysis in tropospheric chemical models, J. Atmos. Chem., 37, 245-282, doi:10.1023/A:1006415919030.
107. Xie, P., and P. A. Arkin (1997), Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs, Bull. Am. Meteorol. Soc., 78, 2539-2558, doi:10.1175/1520-0477(1997) 078<2539:GPAYMA>2.0.CO;2.
108. Yarwood, G., T. E. Stoeckenius, J. G. Heiken, and A. M. Dunker (2003), Modeling weekday/weekend ozone differences in the Los Angeles region for 1997, J. Air Waste Manag. Assoc., 53, 864-875. (Pubitemid 36807960)
109. Yarwood, G., S. Rao, M. Yocke, and G. Z. Whitten (2005), Final Report- Updates to the Carbon Bond Chemical Mechanism: CB05, Rep. RT-04-00675, 246 pp., Yocke and Co., Novato, Calif. [Available at http://www.camx.com/publ/pdfs/CB05- Final-Report-120805.pdf.].
110. Yu, S., R. Mathur, K. Schere, D. Kang, J. Pleim, J. Young, D. Tong, G. Pouliot, S. A. McKeen, and S. T. Rao (2008), Evaluation of realtime PM2.5 forecasts and process analysis for PM2.5 formation over the eastern United States using the Eta-CMAQ forecast model during the 2004 ICARTT Study, J. Geophys. Res., 113, D06204, doi:10.1029/2007JD009226.
111. Zaveri, R. A., and L. K. Peters (1999), A new lumped structure photochemical mechanism for large-scale applications, J. Geophys. Res., 104(D23), 30,387-30,415, doi:10.1029/1999JD900876.
112. Zhang, N., Y.-S. Chen, and Y. Zhang (2011), Forecasting O3 and PM2.5 during summer and winter with WRF/Chem-MADRID over the southeastern United States, poster presented at the Tenth Annual CMAS Conference, Chapel Hill, N. C., 24-26 October.
113. Zhang, Y. (2008), Online coupled meteorology and chemistry models: History, current status, and outlook, Atmos. Chem. Phys., 8, 2895-2932, doi:10.5194/acp-8-2895-2008.
114. Zhang, Y., B. Pun, K. Vihayaraghavan, S.-Y. Wu, C. Seigneur, S. N. Pandis, M. Z. Jacobson, A. Nenes, and J.H. Seinfeld (2004), Development and application of the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID), J. Geophys. Res., 109, D01202, doi:10.1029/2003JD003501.
115. Zhang, Y., P. Liu, B. Pun, and C. Seigneur (2006a), A comprehensive performance evaluation of MM5-CMAQ for summer 1999 Southern Oxidants Study Episode, Part I. Evaluation protocols, databases, and meteorological predictions, Atmos. Environ., 40, 4825-4838, doi:10.1016/j. atmosenv.2005.12. 043. (Pubitemid 44066867)
116. Zhang, Y., P. Liu, B. Pun, and C. Seigneur (2006b), A comprehensive performance evaluation of MM5-CMAQ for the summer 1999 Southern Oxidants Study Episode, Part III. Diagnostic and mechanistic evaluations, Atmos. Environ., 40, 4856-4873, doi:10.1016/j.atmosenv.2005. 12.046. (Pubitemid 44066872)
117. Zhang, Y., X.-Y. Wen, K. Wang, K. Vijayaraghavan, and M. Z. Jacobson (2009), Probing into regional O3 and PM pollution in the U.S., Part II. An examination of formation mechanisms through a process analysis technique and sensitivity study, J. Geophys. Res., 114, D22305, doi:10.1029/2009JD011900.
118. Zhang, Y., Y. Pan, K. Wang, J. D. Fast, and G. A. Grell (2010a), WRF/Chem-MADRID: Incorporation of an aerosol module into WRF/Chem and its initial application to the TexAQS2000 episode, J. Geophys. Res., 115, D18202, doi:10.1029/2009JD013443.
119. Zhang, Y., X.-Y. Wen, and C. J. Jang (2010b), Simulating chemistry- aerosol-cloud-radiation-climate feedbacks over the continental U.S. using the online-coupled Weather Research Forecasting Model with chemistry (WRF/Chem), Atmos. Environ., 44, 3568-3582, doi:10.1016/j.atmosenv.2010.05.056.
120. Zhang, Y., P. Liu, X.-H. Liu, B. Pun, C. Seigneur, M. Z. Jacobson, and W.-X. Wang (2010c), Fine scale modeling of wintertime aerosol mass, number, and size distributions in central California, J. Geophys. Res., 115, D15207, doi:10.1029/2009JD012950.
121. Zhang, Y., Y.-S. Chen, S.-Y. Wu, S. Zhu, K. Sartelet, P. Tran, and C. Seigneur (2011), Application of WRF/Chem-MADRID in Europe: Model evaluation and aerosol-meteorology interactions, paper presented at the European Geosciences Union General Assembly 2011, Vienna, Austria, 3-8 April.
122. Zhu, S., and Y. Zhang (2011), Sensitivity of simulated chemical concentrations and aerosol-meteorology interactions to aerosol treatments in WRF/Chem, paper presented at the COST Action ES1004: "EuMetChem" scientific meeting, Vienna, Austria, 3-8 April.