PDF parameterization of boundary layer clouds in models with horizontal grid spacings from 2 to 16 km

Monthly Weather Review

Volumn 140, Issue 1, 2012, Pages 285-306

  Larson, Vincent E ^a   Schanen, David P ^a   Wang, Minghuai ^b   Ovchinnikov, Mikhail ^b   Ghan, Steven ^b  

^a UNIVERSITY OF WISCONSIN MILWAUKEE   (United States)

^b PACIFIC NORTHWEST NATIONAL LABORATORY   (United States)

Author keywords

Cloud microphysics; Cloud resolving models; Clouds; Parameterization

Indexed keywords

ATMOSPHERIC MODELING; BOUNDARY LAYER CLOUDS; BOUNDARY LAYER TURBULENCE; CLOUD FRACTION; CLOUD LAYERS; CLOUD MICROPHYSICS; CLOUD RESOLVING MODEL; CLOUD RESOLVING MODELS; CLOUD TYPES; DEEP CONVECTION; GENERAL CIRCULATION MODEL; GRID-SPACINGS; HORIZONTAL GRID SPACING; HORIZONTAL WINDS; JOINT PROBABILITY DENSITY FUNCTION; MULTI-SCALE MODELING; NUMERICAL WEATHER PREDICTION MODELS; PARAMETERIZATIONS; REDUCED SENSITIVITY; VERTICAL VELOCITY;

ATMOSPHERIC THERMODYNAMICS; BOUNDARY LAYERS; CLIMATE MODELS; CLOUDS; PARAMETERIZATION; PROBABILITY DENSITY FUNCTION; TURBULENCE;

COMPUTER SIMULATION;

ATMOSPHERIC CONVECTION; ATMOSPHERIC MODELING; BOUNDARY LAYER; CLOUD MICROPHYSICS; GENERAL CIRCULATION MODEL; NUMERICAL MODEL; PARAMETERIZATION; STRATOCUMULUS;

EID: 84862947106     PISSN: 00270644     EISSN: None     Source Type: Journal    
DOI: 10.1175/MWR-D-10-05059.1     Document Type: Article

References (47)

1. Ackerman, A. S., and Coauthors, 2009: Large-eddy simulations of a drizzling, stratocumulus-topped marine boundary layer. Mon. Wea. Rev., 137, 1083-1110.
2. Anand, M. S., A. T. Hsu, and S. B. Pope, 1997: Calculations of swirl combustors using joint velocity-scalar probability density function method. AIAA J., 35, 1143-1150.
3. Andrejczuk, M., J. M. Reisner, B. Henson, M. K. Dubey, and C. A. Jeffery, 2008: The potential impacts of pollution on a nondrizzling stratus deck: Does aerosol number matter more than type? J. Geophys. Res., 113, D19204, doi:10.1029/2007JD009445.
4. Arakawa, A., 2004: The cumulus parameterization problem: Past, present, and future. J. Climate, 17, 2493-2525.
5. Arakawa, A., J.-H. Jung, and C.-M. Wu, 2011: Toward unification of the multiscale modeling of the atmosphere. Atmos. Chem. Phys. Discuss., 11, 3181-3217.
6. Blossey, P. N., C. S. Bretherton, and M. C. Wyant, 2009: Subtropical low cloud response to a warmer climate in a superparameterized climate model. Part II. Column modeling with a cloud resolving model. J.Adv.Model. Earth Syst., 1, doi:10.3894/JAMES.2009.1.8.
7. Bougeault, P., 1981: Modeling the trade-wind cumulus boundary layer. Part II: A higher-order one-dimensional model. J. Atmos. Sci., 38, 2429-2439.
8. Bretherton, C. S., 2007: Challenges in numerical modeling of Tropical circulations. The Global Circulation of the Atmosphere, T. Schneider andA. H. Sobel, Eds., Princeton University Press, 302-330.
9. Brown, A. R., and Coauthors, 2002: Large-eddy simulation of the diurnal cycle of shallow cumulus convection over land. Quart. J. Roy. Meteor. Soc., 128, 1075-1093.
10. Cheng, A., and K.-M. Xu, 2008: Simulation of boundary-layer cumulus and stratocumulus clouds using a cloud-resolving model with low- and third-order turbulence closures. J. Meteor. Soc. Japan, 86, 67-86.
11. Cheng, A., and K.-M. Xu, 2009:APDF-based microphysics parameterization for simulation of drizzling boundary layer clouds. J. Atmos. Sci., 66, 2317-2334.
12. De Roode, S. R., P. G. Duynkerke, and H. J. J. Jonker, 2004: Largeeddy simulation: How large is large enough? J. Atmos. Sci., 61, 403-421.
13. Gerard, L., 2007: An integrated package for subgrid convection, clouds and precipitation compatible with meso-gamma scales. Quart. J. Roy. Meteor. Soc., 133, 711-730.
14. Golaz, J.-C., V. E. Larson, and W. R. Cotton, 2002: A PDF-based model for boundary layer clouds. Part I: Method and model description. J. Atmos. Sci., 59, 3540-3551.
15. Guo, H., J.-C. Golaz, L. J. Donner, V. E. Larson, D. P. Schanen, and B. M. Griffin, 2010: A dynamic probability density function treatment of cloud mass and number concentrations for low level clouds in GFDL SCM/GCM. Geosci. Model Dev., 3, 475-486.
16. Jeffery, C. A., and J. M. Reisner, 2006:Astudy of cloud mixing and evolution using PDF methods. Part I: Cloud front propagation and evaporation. J. Atmos. Sci., 63, 2848-2864.
17. Kain, J. S., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170-181.
18. Kain, J. S., and Coauthors, 2008: Some practical considerations regarding horizontal resolution in the first generation of operational convection-allowing NWP. Wea. Forecasting, 23, 931-952.
19. Khairoutdinov, M., and Y. Kogan, 2000: A new cloud physics parameterization in a large-eddy simulation model of marine stratocumulus. Mon. Wea. Rev., 128, 229-243.
20. Khairoutdinov, M., and D. A. Randall, 2001: A cloud resolving model as a cloud parameterization in the NCAR Community Climate System Model: Preliminary results. Geophys. Res. Lett., 28, 3617-3620.
21. Khairoutdinov, M., and D. A. Randall, 2003: Cloud resolving modeling of the ARM Summer 1997 IOP: Model formulation, results, uncertainties, and sensitivities. J. Atmos. Sci., 60, 607-624.
22. Khairoutdinov, M., and D. A. Randall, and C. DeMott, 2005: Simulations of the atmospheric general circulation using a cloud-resolving model as a superparameterization of physical processes. J. Atmos. Sci., 62, 2136-2154.
23. Khairoutdinov, M., C. DeMott, and D. A. Randall, 2008: Evaluation of the simulated interannual and subseasonal variability in an AMIP-style simulation using the CSU multiscale modeling framework. J. Climate, 21, 413-431.
24. Lappen, C.-L., and D. A. Randall, 2001: Towards a unified parameterization of the boundary layer and moist convection. Part I: A new type of mass-flux model. J. Atmos. Sci., 58, 2021-2036.
25. Larson, V. E., and J.-C. Golaz, 2005: Using probability density functions to derive consistent closure relationships among higher-order moments. Mon. Wea. Rev., 133, 1023-1042.
26. Larson, V. E., R. Wood, P. R. Field, J.-C. Golaz, T. H. Vonder Haar, and W. R. Cotton, 2001: Small-scale and mesoscale variability of scalars in cloudy boundary layers: One-dimensional probability density functions. J. Atmos. Sci., 58, 1978-1994.
27. Morrison, H., and J. O. Pinto, 2005:Mesoscale modeling of springtime Arctic mixed-phase stratiform clouds using a new two-moment bulk microphysics scheme. J. Atmos. Sci., 62, 3683-3704.
28. Morrison, H., G. Thompson, and V. Tatarskii, 2009: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Mon. Wea. Rev., 137, 993-1009.
29. Neggers, R. A. J., 2009: A dual mass flux framework for boundary layer convection. Part II: Clouds. J. Atmos. Sci., 66, 1489-1506.
30. Neggers, R. A. J., M. Köhler, and A. C. M. Beljaars, 2009: A dual mass flux framework for boundary layer convection. Part I: Transport. J. Atmos. Sci., 66, 1465-1488.
31. Noh, Y., W. G. Cheon, S. Y. Hong, and S. Raasch, 2003: Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data. Bound.-Layer Meteor., 107, 401-427.
32. Park, S., and C. S. Bretherton, 2009: The University of Washington shallow convection and moist turbulence schemes and their impact on climate simulations with the Community Atmosphere Model. J. Climate, 22, 3449-3469.
33. Pergaud, J., V. Masson, S. Malardel, and F. Couvreux, 2009: A parameterization of dry thermals and shallow cumuli for mesoscale numerical weather prediction. Bound.-Layer Meteor., 132, 83-106.
34. Randall, D. A., Q. Shao, and C.-H. Moeng, 1992: A second-order bulk boundary-layer model. J. Atmos. Sci., 49, 1903-1923.
35. Ringler, T. D., D. Jacobsen, M. Gunzburger, L. Ju, M. Duda, and W. Skamarock, 2011: Exploring a multiresolution modeling approach within the shallow-water equations. Mon. Wea. Rev., 139, 3348-3368.
36. Siebesma, A. P., and Coauthors, 2003: A large eddy simulation intercomparison study of shallow cumulus convection. J. Atmos. Sci., 60, 1201-1219.
37. Siebesma, A. P., P. M. M. Soares, and J. Teixeira, 2007: A combined eddydiffusivity mass-flux approach for the convective boundary layer. J. Atmos. Sci., 64, 1230-1248.
38. Soares, P. M. M., P.M.A.Miranda, A. P. Siebesma, and J. Teixeira, 2004: An eddy-diffusivity/mass-flux parametrization for dry and shallow cumulus convection. Quart. J. Roy. Meteor. Soc., 130, 3365-3383.
39. Sommeria, G., and J. W. Deardorff, 1977: Subgrid-scale condensation in models of nonprecipitating clouds. J. Atmos. Sci., 34, 344-355.
40. Stevens, B., and Coauthors, 2003: On entrainment rates in nocturnal marine stratocumulus. Quart. J. Roy. Meteor. Soc., 129, 3469-3492.
41. Stevens, B., and Coauthors, 2005: Evaluation of large-eddy simulations via observations of nocturnal marine stratocumulus. Mon. Wea. Rev., 133, 1443-1462.
42. Tao, W.-K., and Coauthors, 2009: A multiscale modeling system: Developments, applications, and critical issues. Bull. Amer. Meteor. Soc., 90, 515-534.
43. Tompkins, A. M., 2002: A prognostic parameterization for the subgrid-scale variability of water vapor and clouds in largescale models and its use to diagnose cloud cover. J. Atmos. Sci., 59, 1917-1942.
44. Wang, M., and Coauthors, 2011: The multi-scale aerosol-climate model PNNL-MMF: model description and evaluation. Geosci. Model Dev., 4, 137-168.
45. Weisman, M.L., C.Davis, W.Wang, K.W.Manning, and J. B.Klemp, 2008: Experiences with 0- to 36-h explicit convective forecasts with the WRF-ARW model. Wea. Forecasting, 23, 407-437.
46. Wyant, M. C., M. Khairoutdinov, and C. S. Bretherton, 2006: Climate sensitivity and cloud response of a GCM with a superparameterization. Geophys. Res. Lett., 33, L06714, doi:10.1029/2005GL025464.
47. Wyngaard, J. C., 2004: Toward numerical modeling in the "Terra Incognita." J. Atmos. Sci., 61, 1816-1826.