Editorial Type:
Article
Article Type:
Research Article

The Role of Negative Buoyancy in Surface-Based Convection and Its Representation in Cumulus Parameterization Schemes

Manisha Ganeshan Department of Atmospheric and Oceanic Science, University of Maryland, College Park, College Park, Maryland

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Raghu Murtugudde Department of Atmospheric and Oceanic Science, and Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland

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John Strack Wind Erosion and Water Conservation Research Unit, USDA Agricultural Research Service, Big Spring, Texas

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Print Publication:
01 Dec 2013
DOI:
https://doi.org/10.1175/JAMC-D-12-0181.1
Page(s):
2887–2905
Restricted access

Abstract

Several warm season, late-afternoon precipitation events are simulated over the Chesapeake Bay watershed using the Weather Research and Forecasting (WRF) model at three different resolutions. The onset and peak of surface-based convection are predicted to occur prematurely when two popular cumulus parameterization schemes (Betts–Miller–Janjić and Kain–Fritsch) are used. Rainfall predictions are significantly improved with explicit convection. The early bias appears to be associated with the inadequacy in representing convective inhibition (CIN) or negative buoyancy in the trigger for moist convection. In particular, both schemes have weak constraints for the negative buoyancy above cloud base and below the level of free convection, leading to premature rainfall. Satellite-derived soundings suggest that, even with extremely favorable conditions, negative buoyancy in this layer may delay the onset of surface-based convection. Other factors, such as enhanced mixing due to overactive shallow convection, also appear to contribute to the early rainfall bias through the premature removal of CIN during the day.

Corresponding author address: Manisha Ganeshan, Dept. of Atmospheric and Oceanic Science, University of Maryland, College Park, College Park, MD 20742-2425. E-mail: mganeshan@atmos.umd.edu

Abstract

Several warm season, late-afternoon precipitation events are simulated over the Chesapeake Bay watershed using the Weather Research and Forecasting (WRF) model at three different resolutions. The onset and peak of surface-based convection are predicted to occur prematurely when two popular cumulus parameterization schemes (Betts–Miller–Janjić and Kain–Fritsch) are used. Rainfall predictions are significantly improved with explicit convection. The early bias appears to be associated with the inadequacy in representing convective inhibition (CIN) or negative buoyancy in the trigger for moist convection. In particular, both schemes have weak constraints for the negative buoyancy above cloud base and below the level of free convection, leading to premature rainfall. Satellite-derived soundings suggest that, even with extremely favorable conditions, negative buoyancy in this layer may delay the onset of surface-based convection. Other factors, such as enhanced mixing due to overactive shallow convection, also appear to contribute to the early rainfall bias through the premature removal of CIN during the day.

Corresponding author address: Manisha Ganeshan, Dept. of Atmospheric and Oceanic Science, University of Maryland, College Park, College Park, MD 20742-2425. E-mail: mganeshan@atmos.umd.edu
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Journal of Applied Meteorology and Climatology

  • Accadia, C., S. Mariani, M. Casaioli, A. Lavagnini, and A. Speranza, 2003: Sensitivity of precipitation forecast skill scores to bilinear interpolation and a simple nearest-neighbor average method on high-resolution verification grids. Wea. Forecasting, 18, 918–932.

    • Search Google Scholar
    • Export Citation

  • Arakawa, A., and W. H. Schubert, 1974: Interaction of a cumulus cloud ensemble with the large-scale environment, Part I. J. Atmos. Sci., 31, 674–701.

    • Search Google Scholar
    • Export Citation

  • Baldwin, M. E., and K. E. Mitchell, 1996: The NCEP hourly multi-sensor U.S. precipitation analysis. Preprints, 15th Conf. on Weather Analysis and Forecasting, Norfolk, VA, Amer. Meteor. Soc., J95–J96.

  • Baldwin, M. E., J. S. Kain, and M. P. Kay, 2002: Properties of the convection scheme in NCEP's Eta Model that affect forecast sounding interpretation. Wea. Forecasting, 17, 1063–1079.

    • Search Google Scholar
    • Export Citation

  • Banacos, P. C., and D. M. Schultz, 2005: The use of moisture flux convergence in forecasting convective initiation: Historical and operational perspectives. Wea. Forecasting, 20, 351–366.

    • Search Google Scholar
    • Export Citation

  • Betts, A. K., 1986: A new convective adjustment scheme. Part I: Observational and theoretical basis. Quart. J. Roy. Meteor. Soc., 112, 677–691.

    • Search Google Scholar
    • Export Citation

  • Betts, A. K., and M. J. Miller, 1986: A new convective adjustment scheme. Part II: Single column tests using GATE wave, BOMEX, and arctic air-mass data sets. Quart. J. Roy. Meteor. Soc., 112, 693–709.

    • Search Google Scholar
    • Export Citation

  • Betts, A. K., and C. Jakob, 2002: Evaluation of the diurnal cycle of precipitation, surface thermodynamics, and surface fluxes in the ECMWF model using LBA data. J. Geophys. Res., 107, 8045, doi:10.1029/2001JD000427.

    • Search Google Scholar
    • Export Citation

  • Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model description and implementation. Mon. Wea. Rev., 129, 569–585.

    • Search Google Scholar
    • Export Citation

  • Colby, F. P., Jr., 1984: Convective inhibition as a predictor of convection during AVE-SESAME II. Mon. Wea. Rev., 112, 2239–2252.

  • Colman, B. R., 1990: Thunderstorms above frontal surfaces in environments without positive CAPE. Part I: A climatology. Mon. Wea. Rev., 118, 1103–1122.

    • Search Google Scholar
    • Export Citation

  • Dai, A. F., and K. E. Trenberth, 2004: The diurnal cycle and its depiction in the Community Climate System Model. J. Climate, 17, 930–995.

    • Search Google Scholar
    • Export Citation

  • Developmental Testbed Center, 2009: Model Evaluation Tools version 2.0 (METv2.0) user's guide. DTC Tech. Rep., 191 pp. [Available online at http://www.dtcenter.org/met/users/docs/users_guide/MET_Users_Guide_v2.0_rev2.pdf.]

  • Diaconis, P., and B. Efron, 1983: Computer-intensive methods in statistics. Sci. Amer., 248, 116–130.

  • Dirmeyer, P. A., and Coauthors, 2010: Simulating the hydrologic diurnal cycle in global climate models: Resolution versus parameterization. Center for Ocean–Land–Atmosphere Studies Tech. Rep. 304, 45 pp.

  • Fritsch, J. M., and C. F. Chappell, 1980: Numerical prediction of convectively driven mesoscale pressure systems. Part I: Convective parameterization. J. Atmos. Sci., 37, 1722–1733.

    • Search Google Scholar
    • Export Citation

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

  • Grell, G. A., 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, 122 pp.

  • Hong, S., and J. J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). J. Korean Meteor. Soc., 42, 129–151.

  • Hong, S., J. Dudhia, and S. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132, 103–120.

    • Search Google Scholar
    • Export Citation

  • Hong, S., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318–2341.

    • Search Google Scholar
    • Export Citation

  • Janjić, 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.

    • Search Google Scholar
    • Export Citation

  • Kain, J. S., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170–181.

  • Kain, J. S., and J. M. Fritsch, 1992: The role of the convective “trigger function” in numerical forecasts of mesoscale convective systems. Meteor. Atmos. Phys., 49, 93–106.

    • Search Google Scholar
    • Export Citation

  • Kuo, H.-L., 1974: Further studies of the parameterization of the influence of cumulus convection on large-scale flow. J. Atmos. Sci., 31, 1232–1240.

    • Search Google Scholar
    • Export Citation

  • Lee, M.-I., and Coauthors, 2007: An analysis of the warm season diurnal cycle over the continental United States and northern Mexico in general circulation models. J. Hydrometeor., 8, 344–366.

    • Search Google Scholar
    • Export Citation

  • Lee, M.-I., S. D. Schubert, M. J. Suarez, J.-K. E. Schemm, H.-L. Pan, J. Han, and S.-H. Yoo, 2008: Role of convection triggers in the simulation of the diurnal cycle of precipitation over the United States Great Plains in a general circulation model. J. Geophys. Res., 113, D02111, doi:10.1029/2007JD008984.

    • Search Google Scholar
    • Export Citation

  • Liang, X., L. Li, A. Dai, and K. E. Kunkel, 2004: Regional climate model simulation of summer precipitation diurnal cycle over the United States. Geophys. Res. Lett., 31, L24208, doi:10.1029/2004GL021054.

    • Search Google Scholar
    • Export Citation

  • Lin, Y., and K. E. Mitchell, 2005: The NCEP stage II/IV hourly precipitation analyses: Development and applications. Preprints, 19th Conf. on Hydrology, San Diego, CA, Amer. Meteor. Soc., 1.2. [Available online at https://ams.confex.com/ams/pdfpapers/83847.pdf.]

  • Masunaga, H., 2012: A satellite study of the atmospheric forcing and response to moist convection over tropical and subtropical oceans. J. Atmos. Sci., 69, 150–167.

    • Search Google Scholar
    • Export Citation

  • Mellor, G. L., and T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys. Space Phys., 20, 851–875.

    • Search Google Scholar
    • Export Citation

  • NCAR, cited2012: The NCAR Command Language version 6.0. NCAR online reference manual. [Available online at http://www.ncl.ucar.edu/Document/Manuals/Ref_Manual/.]

  • Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech Note NCAR/TN-475+STR, 113 pp.

  • Smith, W. L., E. Weisz, S. Kirev, D. K. Zhou, Z. Li, and E. E. Borbas, 2012: Dual-regression retrieval algorithm for real-time processing of satellite ultraspectral radiances. J. Appl. Meteor. Climatol., 51, 1455–1476.

    • Search Google Scholar
    • Export Citation

  • Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117, 1779–1800.

    • Search Google Scholar
    • Export Citation

  • Wallace, J. M., 1975: Diurnal variations in precipitation and thunderstorm frequency over the conterminous United States. Mon. Wea. Rev., 103, 406–419.

    • Search Google Scholar
    • Export Citation

  • Weisz, E., H.-L. Huang, J. Li, E. Borbas, K. Baggett, P. Thapliyal, and L. Guan, 2007a: International MODIS and AIRS processing package: AIRS products and applications. J. Appl. Remote Sens., 1, 013519, doi:10.1117/1.2766867.

    • Search Google Scholar
    • Export Citation

  • Weisz, E., J. Li, D. K. Zhou, H.-L. Huang, M. D. Goldberg, and P. Yang, 2007b: Cloudy sounding and cloud-top height retrieval from AIRS alone single field-of-view radiance measurements. Geophys. Res. Lett., 34, L12802, doi:10.1029/2007GL030219.

    • Search Google Scholar
    • Export Citation

  • Zhang, G. J., 2002: Convective quasi-equilibrium in midlatitude continental environment and its effect on convective parameterization. J. Geophys. Res., 107 (D14), doi:10.1029/2001JD001005.

    • Search Google Scholar
    • Export Citation

  • Zhang, G. J., 2003: Roles of tropospheric and boundary layer forcing in the diurnal cycle of convection in the U.S. southern Great Plains. Geophys. Res. Lett., 30, 2281, doi:10.1029/2003GL018554.

    • Search Google Scholar
    • Export Citation
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