Editorial Type:
Article
Article Type:
Research Article

Nested-Model Simulation of Moist Convection: The Impact of Coarse-Grid Parameterized Convection on Fine-Grid Resolved Convection

Thomas T. Warner National Center for Atmospheric Research*, and Program in Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado

Search for other papers by Thomas T. Warner in
Current site
Google Scholar
PubMed Close
and
Hsiao-Ming Hsu National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Hsiao-Ming Hsu in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Jul 2000
DOI:
https://doi.org/10.1175/1520-0493(2000)128<2211:NMSOMC>2.0.CO;2
Page(s):
2211–2231
Restricted access

Abstract

Future-generation, operational, weather prediction systems will likely include storm-scale, limited-area models that will explicitly resolve convective precipitation. However, the high-resolution convection-resolving grids will need to be embedded, or nested, within coarser-resolution grids that will provide lateral-boundary conditions. It is the purpose of this study to illustrate how the convective environment on a convection-resolving storm-scale model grid, and therefore the convection itself, can be significantly influenced by the treatment of convection on the coarser grids within which the fine grid is embedded.

It was confirmed that, as in the actual atmosphere, mass-field adjustments resulting from convection in one area (the outer grids, in this case) affect the convection in other areas (the inner, convection-resolving grid). That is, the errors in precipitation timing, precipitation intensity, and the vertical distribution of latent heating, associated with the treatment of convection on the outer grids, greatly affect the explicit convection on the inner grid. In this case, the different precipitation parameterizations on the outer two grids produce up to a factor of 3 difference in the 24-h amount of explicit rainfall simulated on the inner grid. Even when the parameterization is limited to only the outer grid, with explicit precipitation on both the middle and inner grids, over a factor of 2 difference in 24-h total explicit rainfall is produced on the inner grid. The different precipitation parameterizations on the outer grids appear to differently modulate the intensity and the timing of the explicit convection on the inner grid through induced subsidence.

Corresponding author address: Thomas T. Warner, NCAR/RAP, P.O. Box 3000, Boulder, CO 80307-3000.

Abstract

Future-generation, operational, weather prediction systems will likely include storm-scale, limited-area models that will explicitly resolve convective precipitation. However, the high-resolution convection-resolving grids will need to be embedded, or nested, within coarser-resolution grids that will provide lateral-boundary conditions. It is the purpose of this study to illustrate how the convective environment on a convection-resolving storm-scale model grid, and therefore the convection itself, can be significantly influenced by the treatment of convection on the coarser grids within which the fine grid is embedded.

It was confirmed that, as in the actual atmosphere, mass-field adjustments resulting from convection in one area (the outer grids, in this case) affect the convection in other areas (the inner, convection-resolving grid). That is, the errors in precipitation timing, precipitation intensity, and the vertical distribution of latent heating, associated with the treatment of convection on the outer grids, greatly affect the explicit convection on the inner grid. In this case, the different precipitation parameterizations on the outer two grids produce up to a factor of 3 difference in the 24-h amount of explicit rainfall simulated on the inner grid. Even when the parameterization is limited to only the outer grid, with explicit precipitation on both the middle and inner grids, over a factor of 2 difference in 24-h total explicit rainfall is produced on the inner grid. The different precipitation parameterizations on the outer grids appear to differently modulate the intensity and the timing of the explicit convection on the inner grid through induced subsidence.

Corresponding author address: Thomas T. Warner, NCAR/RAP, P.O. Box 3000, Boulder, CO 80307-3000.

Save
Cover Monthly Weather Review
Monthly Weather Review

  • Betts, A. K., and M. J. Miller, 1993: The Betts–Miller scheme. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr., No. 46, Amer. Meteor. Soc., 107–121.

  • Black, T., M. Baldwin, G. DiMego, and E. Rogers, 1998: Results from daily forecasts of the NCEP Eta-10 model over the western United States. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., 246–247.

  • Bretherton, C. S., 1987: A theory for nonprecipitating moist convection between two parallel plates. Part I: Thermodynamic and“linear” solutions. J. Atmos. Sci.,44, 1809–1827.

  • ——, and P. K. Smolarkiewicz, 1989: Gravity waves, compensating subsidence and detrainment around cumulus clouds. J. Atmos. Sci.,46, 740–759.

  • Carpenter, R. L., Jr., and Coauthors, 1998: Storm-scale NWP for commercial aviation: Results from real-time operational tests in 1996–1997. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., 213–216.

  • Cram, J. M., R. A. Pielke, and W. R. Cotton, 1992: Numerical simulation and analysis of a prefrontal squall line. Part II: Propagation of the squall line as an internal gravity wave. J. Atmos. Sci.,49, 209–225.

  • Davis, C., H.-M. Hsu, T. Keller, A. Shantz, and T. Warner, 1998: A meso-γ-scale real time forecasting system suitable for regions of complex terrain. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., 223–225.

  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci.,46, 3077–3107.

  • ——, 1993: A nonhydrostatic version of the Penn State/NCAR mesoscale model: Validation tests and the simulation of an Atlantic cyclone and cold front. Mon. Wea. Rev.,121, 1493–1513.

  • Grell, G. A., 1993: Prognostic evaluation of assumptions used by cumulus parameterizations. Mon. Wea. Rev.,121, 764–787.

  • ——, J. Dudhia, and D. R. Stauffer, 1994: A description of the fifth generation Penn State/NCAR Mesoscale Model (MM5). NCAR Tech. Note NCAR/TN 398+STR, 138 pp.

  • Hong, S.-Y., and H.-L. Pan, 1996: Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev.,124, 2322–2339.

  • Janjic, Z. I., 1994: The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev.,122, 927–945.

  • Johnson, R. H., B. D. Miner, and P. E. Ciesielski, 1995: Circulations between mesoscale convective systems along a cold front. Mon. Wea. Rev.,123, 585–599.

  • Kain, J. S., and J. M. Fritsch, 1990: A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci.,47, 2784–2802.

  • ——, and ——, 1993: Convective parameterization for mesoscale models: The Kain–Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr., No. 46, Amer. Meteor. Soc., 165–170.

  • Mapes, B. E., 1993: Gregarious tropical convection. J. Atmos. Sci.,50, 2026–2037.

  • Molinari, J., and M. Dudek, 1992: Parameterization of convective precipitation in mesoscale numerical models: A critical review. Mon. Wea. Rev.,120, 326–344.

  • Nicholls, M. E., R. A. Pielke, and W. R. Cotton, 1991: Thermally forced gravity waves in an atmosphere at rest. J. Atmos. Sci.,48, 1869–1884.

  • Ninomiya, K., 1971a: Dynamical analysis of outflow from tornado-producing thunderstorms as revealed by ATS III pictures. J. Appl. Meteor.,10, 275–294.

  • ——, 1971b: Mesoscale modifications of synoptic situations from thunderstorm development as revealed by ATS III and aerological data. J. Appl. Meteor.,10, 1103–1121.

  • Pandya, R. E., and D. R. Durran, 1996: The influence of convectively generated thermal forcing on the mesoscale circulation around squall lines. J. Atmos. Sci.,53, 2924–2951.

  • Schultz, P., 1998: Status and prospects for local data analysis and mesoscale modeling in AWIPS. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., 324.

  • Seaman, N. L., S. A. Michelson, P. C. Shafran, and D. R. Stauffer, 1998: Forecast of a severe squall line development in MM5 using explicit moist physics at 4-km resolution. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., J1–J4.

  • Snook, J. S., P. A. Stamus, J. Edwards, Z. Christidis, and J. A. McGinley, 1998: Local-domain mesoscale analysis and forecast model support for the 1996 Centennial Olympic Games. Wea. Forecasting,13, 138–150.

  • Stensrud, D. J., and R. A. Maddox, 1988: Opposing mesoscale circulations: A case study. Wea. Forecasting,3, 189–204.

  • Szoke, E. J., J. A. McGinley, P. Schultz, and J. S. Snook, 1998: Near-operational short-term forecasts from two mesoscale models. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., 320–323.

  • Troen, I., and L. Mahrt, 1986: A simple model of the atmospheric boundary layer: Sensitivity to surface evaporation. Bound.-Layer Meteor.,37, 129–148.

  • Wang, W., and N. L. Seaman, 1997: A comparison study of convective parameterization schemes in a mesoscale model. Mon. Wea. Rev.,125, 252–278.

  • Warner, T. T., Y.-H. Kuo, J. D. Doyle, J. Dudhia, D. R. Stauffer, and N. L. Seaman, 1992: Nonhydrostatic, mesobeta-scale real-data simulations with the Penn State University/National Center for Atmospheric Research mesoscale model. Meteor. Atmos. Phys.,49, 209–227.

  • ——, R. A. Petersen, and R. E. Treadon, 1997: A tutorial on lateral boundary conditions as a basic and potentially serious limitation to regional numerical weather prediction. Bull. Amer. Meteor. Soc.,78, 2599–2617.

  • Weisman, M. L., W. C. Skamarock, and J. B. Klemp, 1997: The resolution dependence of explicitly modeled convective systems. Mon. Wea. Rev.,125, 527–548.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1046 763 45
PDF Downloads 142 55 3