Impact on modeled cloud characteristics due to simplified treatment of uniform cloud condensation nuclei during NEAQS 2004

Geophysical Research Letters

Volumn 34, Issue 19, 2007, Pages

  Gustafson Jr , William I ^a   Chapman, Elaine G ^a   Ghan, Steven J ^a   Easter, Richard C ^a   Fast, Jerome D ^a  

^a PACIFIC NORTHWEST NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ATMOSPHERIC AEROSOLS; ATMOSPHERIC RADIATION; COMPUTER SIMULATION; MATHEMATICAL MODELS; SYSTEMATIC ERRORS;

CLOUD CONDENSATION NUCLEI; CLOUD OPTICAL DEPTH; GLOBAL CLIMATE MODELS;

CLOUDS;

CLIMATE MODELING; CLOUD CONDENSATION NUCLEUS; CLOUD RADIATIVE FORCING; OPTICAL DEPTH; SHORTWAVE RADIATION;

EID: 37249042269     PISSN: 00948276     EISSN: None     Source Type: Journal    
DOI: 10.1029/2007GL030021     Document Type: Article

References (24)

1. Albrecht, B. A. (1989), Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227-1230.
2. Barker, H. W., and P. Räisänen (2004), Neglect by GCMs of subgrid-scale horizontal variations in cloud-droplet effective radius: A diagnostic radiative analysis, Q. J. R. Meteorol. Soc., 130, 1905-1920.
3. Barnard, J. C., and C. N. Long (2004), A simple empirical equation to calculate cloud optical thickness using shortwave broadband measurements, J. Appl. Meteorol., 43, 1057-1066.
4. Berg, L. K., and R. B. Stull (2005), A simple parameterization coupling the convective daytime boundary layer and fair-weather cumuli, J. Atmos. Sci., 62, 1976-1988.
5. Easter, R. C., et al. (2004), MIRAGE: Model description and evaluation of aerosols and trace gases, J. Geophys. Res., 109, D20210, doi:10.1029/2004JD004571.
6. Fahey, K, M., and S. N. Pandis (2001), Optimizing model performance: Variable size resolution in cloud chemistry modeling, Atmos. Environ., 35, 4471-4478.
7. 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 in the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model, J. Geophys. Res., 111, D21305, doi:10.1029/2005JD006721.
8. x emissions on ozone in the eastern United States: Proof of concept, J. Geophys. Res., 111, D12306, doi:10.1029/2005JD006354.
9. Ghan, S., R. Easter, J. Hudson, and F. Bréon (2001), Evaluation of aerosol indirect radiative forcing in MIRAGE, J. Geophys. Res., 106, 5317-5334.
10. Grell, G. A., et al. (2005), Fully coupled "online" chemistry within the WRF model, Atmos. Environ., 39, 6957-6975.
11. Jacobson, M. Z., et al. (1994), Modeling coagulation among particles of different composition and size, Atmos. Environ., 28, 1327-1338.
12. Larson, V. E., et al. (2005), Supplying local microphysics parameterizations with information about subgrid variability: Latin hypercube sampling, J. Atmos. Sci., 62, 4010-4026.
13. 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.
14. Mesinger, F., et al. (2006), North American regional reanalysis, Bull. Am. Meteorol. Soc., 87, 343-360.
15. Michalsky, J. J., J. A. Schlemmer, W. E. Berkheiser, J. L. Berndt, L. C. Harrison, N. S. Laulainen, N. R. Larson, and J. C. Barnard (2001), Multi-year measurements of aerosol optical depth in the Atmospheric Radiation Measurement and Quantitative Links programs, J. Geophys. Res., 106, 12099-12107.
16. Ming, Y., et al. (2007), Modeling the interactions between aerosols and liquid water clouds with a self-consistent cloud scheme in a general circulation model, J. Atmos. Sci., 64, 1189-1209.
17. Miura, H., H. Tomita, T. Nasuno, S. Iga, M. Satoh, and T. Matsuno (2005), A climate sensitivity test using a global cloud resolving model under an aqua planet condition, Geophys. Res. Lett., 32, L19717, doi:10.1029/2005GL023672.
18. 2O vapors, J. Geophys. Res., 107(D19), 4381, doi:10.1029/2002JD002132.
19. Randall, D., et al. (2003), Breaking the cloud parameterization deadlock, Bull. Am. Meteorol. Soc., 84, 1547-1564.
20. Skamarock, W. C., et al. (2005), A description of the Advanced Research WRF Version 2, 88 pp., Tech. Note NCAR/TN-468+STR, Natl. Cent. for Atmos. Res., Boulder, Colo.
21. Storelvmo, T., J. E. Kristjánsson, S. J. Ghan, A. Kirkevåg, Ø. Seland, and T. Iversen (2006), Predicting cloud droplet number concentration in Community Atmosphere Model (CAM)-Oslo, J. Geophys. Res., 111, D24208, doi:10.1029/2005JD006300.
22. Tomita, H., H. Miura, S. Iga, T. Nasuno, and M. Satoh (2005), A global cloud-resolving simulation: Preliminary results from an aqua planet experiment, Geophys. Res. Lett., 32, L08805, doi:10.1029/ 2005GL022459.
23. Twomey, S. (1991), Aerosols, clouds and radiation, Atmos. Environ. Part A, 25, 2435-2442.
24. U.S. Environmental Protection Agency (EPA) (2001), Current methods used to estimate emissions, in 1985-1999 Procedures Document for National Emission Inventory, Criteria Air Pollutants 1985-1999, EPA-454/ R-01-006, Washington, D. C.