SEARCH

SEARCH BY CITATION

References

  • Ackerman, T. P., and G. M. Stokes (2003), The Atmospheric Radiation Measurement Program, Phys. Today, 56, 3844.
  • Arakawa, A., and W. H. Schubert (1974), Interaction of a cumulus cloud ensemble with the large-scale environment, Part I, J. Atmos. Sci., 31, 674701.
  • Barnes, S. L. (1964), A technique for maximizing details in numerical map analysis, J. Appl. Meteorol., 3, 396409.
  • Collins, W. D.et al. (2003), Description of the NCAR Community Atmosphere Model (CAM2), 171 pp., Natl. Cent. for Atmos. Res., Boulder, Colo.
  • Coquard, J., et al. (2004), Simulations of western U.S. surface climate in 15 global climate models, Clim. Dyn., in press.
  • Dai, A. (2001), Global precipitation and thunderstorm frequencies: Part II. Diurnal variations, J. Clim., 14, 11121128.
  • Dai, A., and K. T. Trenberth (2004), The diurnal cycle and its depiction in the Community Climate System Model, J. Clim., 17, 930951.
  • Dai, A., F. Giorgi, and K. E. Trenberth (1999), Observed and model simulated precipitation diurnal cycle over the contiguous United States, J. Geophys. Res., 104, 63776402.
  • Duffy, P. B., B. Govindasamy, J. P. Iorio, J. Milovich, K. R. Sperber, K. E. Taylor, M. F. Wehner, and S. L. Thompson (2003), High-resolution simulations of global climate: Part 1. Present climate, Clim. Dyn., 21, 371390.
  • Fritsch, J. M., and C. F. Chappell (1980), Numerical prediction of convectively driven mesoscale pressure systems: Part I. Convective parameterization, J. Atmos. Sci., 37, 17221733.
  • Ghan, S. J., et al. (2000), An intercomparison of single column model simulations of summertime midlatitude continental convection, J. Geophys. Res., 105, 20912124.
  • Hack, J. J. (1994), Parameterization of moist convection in the National Center for Atmopsheric Research Community Climate (CCM2), J. Geophys. Res., 99, 55515568.
  • Huffman, G. J., R. F. Adler, M. M. Morrissey, D. T. Bolvin, S. Curtis, R. Joyce, B. McGavock, and J. Susskind (2001), Global precipitation at one-degree daily resolution from multisatellite observations, J. Hydrometeorol, 2, 3650.
  • Kain, J. S., and J. M. Fritsch (1993), Convective parameterization for mesoscale models: The Kain-Fritsch scheme, the representation of cumulus convection in numerical models, Meteorol. Monogr., 46, 165170.
  • Kiehl, J. T., J. J. Hack, G. B. Bonan, B. A. Boville, D. L. Williamson, and P. J. Rasch (1998), The National Center for Atmospheric Research Community Climate Model: CCM3, J. Clim., 11, 11311149.
  • Klein, S. A., and C. Jakob (1999), Validation and sensitivities of front clouds simulated by the ECMWF model, Mon. Weather Rev., 127, 25142531.
  • Kuo, H. L. (1965), On formation and intensification of tropical cyclones through latent heat release by cumulus convection, J. Atmos. Sci., 22, 4063.
  • Kuo, H. L. (1974), Further studies of the parameterization of the influence of cumulus convection on large-scale flow, J. Atmos. Sci., 31, 12321240.
  • Lin, W. Y., and M. H. Zhang (2004), Evaluation of clouds and their radiation effects simulated by the NCAR Community Atmospheric Model CAM2 against satellite observations, J. Clim., in press.
  • Minnis, P., W. L. Smith, D. P. Garber, J. K. Ayers, and D. R. Doeling (1995), Cloud properties derived from GOES-7 for spring 1994 ARM Intensive Observing Period using version 1.0.0 of ARM satellite data analysis program, NASA Ref. Publ., 1366, 59 pp.
  • Phillips, T. J., et al. (2004), Evaluating parameterizations in general circulation models: Climate simulation meets weather prediction, Bull. Am. Meteorol. Soc., in press.
  • Rogers, R., and J. M. Fritsch (1996), A general framework for convective trigger functions, Mon. Weather Rev., 124, 24382452.
  • Rossow, W. B., A. W. Walker, D. Beuschel, and M. Roiter (1996), International Satellite Cloud Climatology Project (ISCCP) description of new cloud datasets, WMO/TD 737, 115 pp., World Clim. Res. Programme, Int. Counc. of Sci. Unions, Geneva.
  • Stokes, G. M., and S. E. Schwartz (1994), The Atmospheric Radiation Measurement (ARM) Program: Programmatic background and design of the cloud and radiation test bed, Bull. Am. Meteorol. Soc., 75, 12021221.
  • Wang, J., and D. A. Randall (1994), The moist available energy of a conditionally unstable atmosphere: II. Further analysis of the GATE data, J. Atmos. Sci., 51, 703710.
  • Webb, M., C. Senior, S. Bony, and J. J. Morcrette (2001), Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models, Clim. Dyn., 17, 905922.
  • White, P. W. (Ed.) (2001), FULL-POS postprocessing and interpolation, in IFS Documentation Part VI: Technical and Computational Procedures (CY23R4), chap. 2, Eur. Cent. for Medium-Range Weather Forecasts, Reading, UK.
  • Xie, S. C. (1998), Single-column modeling: Methodology and application to the evaluation of cumulus convection schemes in GCMs, Ph.D. thesis, 126 pp., State Univ. of New York at Stony Brook.
  • Xie, S. C., and M. H. Zhang (2000), Impact of the convective triggering function on single-column model simulations, J. Geophys. Res., 105, 14,98314,996.
  • Xie, S. C., et al. (2002), Intercomparison and evaluation of cumulus parameterizations under summertime midlatitude continental conditions, Q. J. R. Meteorol. Soc., 128, 10951135.
  • Xie, S. C., R. T. Cederwall, M. Zhang, and J. Yio (2003), Comparison of SCM and CSRM forcing data derived from the ECMWF model and from objective analysis at the ARM SGP, J. Geophys. Res., 108(D16), 4499, doi:10.1029/2003JD003541.
  • Zhang, G. J. (2002), Convective quasi-equalibrium in midlatitude continental environment and its effect on convective parameterization, J. Geophys. Res., 107(D14), 4220, doi:10.1029/2001JD001005.
  • Zhang, G. J., and N. A. McFarlane (1991), Convective stabilization in midlatitudes, Mon. Weather Rev., 119, 19151928.
  • Zhang, G. J., and N. A. McFarlane (1995), Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Center general circulation model, Atmos. Ocean, 33, 407446.
  • Zhang, M. H., and J. L. Lin (1997), Constrained variational analysis of sounding data bases on column-integrated budgets of mass, heat, moisture, and momentum: Approach and application to ARM measurements, J. Atmos. Sci., 54, 15031524.
  • Zhang, M. H., J. L. Lin, R. T. Cederwall, J. J. Yio, and S. C. Xie (2001), Objective analysis of ARM IOP Data: Method and sensitivity, Mon. Weather Rev., 129, 295311.