Resolution Dependence of Initiation and Upscale Growth of Deep Convection in Convection-Allowing Forecasts of the 31 May–1 June 2013 Supercell and MCS

Russ S. Schumacher Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Abstract

On 31 May 2013, a supercell thunderstorm initiated in west-central Oklahoma and produced a deadly tornado. This convection then grew upscale, with a nearly stationary line developing early on 1 June that produced very heavy rainfall and caused deadly flash flooding in the Oklahoma City area. Real-time convection-allowing (Δx = 4 km) model forecasts used during the Mesoscale Predictability Experiment (MPEX) provided accurate guidance regarding the timing, location, and evolution of convection in this case. However, attempts to simulate this event at higher resolution degraded the forecast, with the primary supercell failing to initiate and the evolution of the overnight MCS not resembling the observed system. Experiments to test the dependence of forecasts of this event on model resolution show that with grid spacing smaller than 4 km, mixing along the dryline in northwest Texas was more vigorous, causing low-level dry air to move more quickly eastward into Oklahoma. This drying prevented the supercell from initiating near the triple point in the higher-resolution simulations. Then, the lack of supercellular convection and its associated cold pool altered the evolution of subsequent convection. Whereas in observations and the 4-km forecast, a nearly stationary MCS developed parallel to, but displaced from, the supercell’s cold pool, the higher-resolution simulations instead had a faster-moving squall line that produced less rainfall. Although the degradation of convective forecasts at higher resolution is probably unusual and appears sensitive to the choice of boundary layer parameterization, these findings demonstrate that how numerical models treat boundary layer processes at different grid spacings can, in some cases, have profound influences on predictions of high-impact weather.

Corresponding author address: Dr. Russ Schumacher, Department of Atmospheric Science, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523. E-mail: russ.schumacher@colostate.edu

Abstract

On 31 May 2013, a supercell thunderstorm initiated in west-central Oklahoma and produced a deadly tornado. This convection then grew upscale, with a nearly stationary line developing early on 1 June that produced very heavy rainfall and caused deadly flash flooding in the Oklahoma City area. Real-time convection-allowing (Δx = 4 km) model forecasts used during the Mesoscale Predictability Experiment (MPEX) provided accurate guidance regarding the timing, location, and evolution of convection in this case. However, attempts to simulate this event at higher resolution degraded the forecast, with the primary supercell failing to initiate and the evolution of the overnight MCS not resembling the observed system. Experiments to test the dependence of forecasts of this event on model resolution show that with grid spacing smaller than 4 km, mixing along the dryline in northwest Texas was more vigorous, causing low-level dry air to move more quickly eastward into Oklahoma. This drying prevented the supercell from initiating near the triple point in the higher-resolution simulations. Then, the lack of supercellular convection and its associated cold pool altered the evolution of subsequent convection. Whereas in observations and the 4-km forecast, a nearly stationary MCS developed parallel to, but displaced from, the supercell’s cold pool, the higher-resolution simulations instead had a faster-moving squall line that produced less rainfall. Although the degradation of convective forecasts at higher resolution is probably unusual and appears sensitive to the choice of boundary layer parameterization, these findings demonstrate that how numerical models treat boundary layer processes at different grid spacings can, in some cases, have profound influences on predictions of high-impact weather.

Corresponding author address: Dr. Russ Schumacher, Department of Atmospheric Science, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523. E-mail: russ.schumacher@colostate.edu
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  • Bryan, G. H., J. C. Wyngaard, and J. M. Fritsch, 2003: Resolution requirements for the simulation of deep moist convection. Mon. Wea. Rev., 131, 23942416, doi:10.1175/1520-0493(2003)131<2394:RRFTSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Burghardt, B. J., C. Evans, and P. J. Roebber, 2014: Assessing the predictability of convection initiation in the high plains using an object-based approach. Wea. Forecasting, 29, 403418, doi:10.1175/WAF-D-13-00089.1.

    • 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 implementation and sensitivity. Mon. Wea. Rev., 129, 569585, doi:10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Ching, J., R. Rotunno, M. LeMone, A. Martilli, B. Kosovic, P. A. Jimenez, and J. Dudhia, 2014: Convectively induced secondary circulations in fine-grid mesoscale numerical weather prediction models. Mon. Wea. Rev., 142, 32843302, doi:10.1175/MWR-D-13-00318.1.

    • Search Google Scholar
    • Export Citation
  • Cifelli, R., N. Doesken, P. Kennedy, L. D. Carey, S. A. Rutledge, C. Gimmestad, and T. Depue, 2005: The community collaborative rain, hail, and snow network: Informal education for scientists and citizens. Bull. Amer. Meteor. Soc., 86, 10691077, doi:10.1175/BAMS-86-8-1069.

    • Search Google Scholar
    • Export Citation
  • Clark, A. J., W. A. Gallus Jr., and T.-C. Chen, 2007: Comparison of the diurnal precipitation cycle in convection-resolving and nonconvection-resolving mesoscale models. Mon. Wea. Rev., 135, 34563473, doi:10.1175/MWR3467.1.

    • Search Google Scholar
    • Export Citation
  • Clark, A. J., and Coauthors, 2012: An overview of the 2010 Hazardous Weather Testbed Experimental Forecast Program spring experiment. Bull. Amer. Meteor. Soc., 93, 5574, doi:10.1175/BAMS-D-11-00040.1.

    • Search Google Scholar
    • Export Citation
  • Clark, A. J., J. Gao, P. T. Marsh, T. Smith, J. S. Kain, J. Correia Jr., M. Xue, and F. Kong, 2013: Tornado pathlength forecasts from 2010 to 2011 using ensemble updraft helicity. Wea. Forecasting, 28, 387407, doi:10.1175/WAF-D-12-00038.1.

    • Search Google Scholar
    • Export Citation
  • Clark, A. J., M. C. Coniglio, B. E. Coffer, G. Thompson, M. Xue, and F. Kong, 2015: Sensitivity of 24-h forecast dryline position and structure to boundary layer parameterizations in convection-allowing WRF Model simulations. Wea. Forecasting, 30, 613–638, doi:10.1175/WAF-D-14-00078.1.

    • Search Google Scholar
    • Export Citation
  • Coffer, B. E., L. C. Maudlin, P. G. Veals, and A. J. Clark, 2013: Dryline position errors in experimental convection-allowing NSSL-WRF model forecasts and the operational NAM. Wea. Forecasting, 28, 746761, doi:10.1175/WAF-D-12-00092.1.

    • Search Google Scholar
    • Export Citation
  • Coniglio, M. C., J. Correia Jr., P. T. Marsh, and F. Kong, 2013: Verification of convection-allowing WRF Model forecasts of the planetary boundary layer using sounding observations. Wea. Forecasting, 28, 842862, doi:10.1175/WAF-D-12-00103.1.

    • Search Google Scholar
    • Export Citation
  • Done, J., C. A. Davis, and M. Weisman, 2004: The next generation of NWP: Explicit forecasts of convection using the Weather Research and Forecasting (WRF) model. Atmos. Sci. Lett., 5, 110117, doi:10.1002/asl.72.

    • Search Google Scholar
    • Export Citation
  • Doswell, C. A., III, H. E. Brooks, and R. A. Maddox, 1996: Flash flood forecasting: An ingredients-based methodology. Wea. Forecasting, 11, 560581, doi:10.1175/1520-0434(1996)011<0560:FFFAIB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Duda, J. D., and W. A. Gallus Jr., 2013: The impact of large-scale forcing on skill of simulated convective initiation and upscale evolution with convection-allowing grid spacings in the WRF. Wea. Forecasting, 28, 9941018, doi:10.1175/WAF-D-13-00005.1.

    • Search Google Scholar
    • Export Citation
  • Durran, D. R., 1990: Mountain waves and downslope windstorms. Atmospheric Processes over Complex Terrain, Meteor. Monogr., No. 23, Amer. Meteor. Soc., 59–81.

  • Hacker, J. P., 2010: Spatial and temporal scales of boundary layer wind predictability in response to small-amplitude land surface uncertainty. J. Atmos. Sci., 67, 217233, doi:10.1175/2009JAS3162.1.

    • Search Google Scholar
    • Export Citation
  • Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, doi:10.1029/2008JD009944.

  • Janjić, Z. I., 2002: Nonsingular implementation of the Mellor–Yamada level 2.5 scheme in the NCEP Meso model. NCEP Office Note 437, 61 pp.

  • Johns, R. H., and C. A. Doswell III, 1992: Severe local storms forecasting. Wea. Forecasting, 7, 588612, doi:10.1175/1520-0434(1992)007<0588:SLSF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kain, J. S., and Coauthors, 2008: Some practical considerations regarding horizontal resolution in the first generation of operational convection-allowing NWP. Wea. Forecasting, 23, 931952, doi:10.1175/WAF2007106.1.

    • Search Google Scholar
    • Export Citation
  • Kain, J. S., and Coauthors, 2013: A feasibility study for probabilistic convection initiation forecasts based on explicit numerical guidance. Bull. Amer. Meteor. Soc., 94, 12131225, doi:10.1175/BAMS-D-11-00264.1.

    • Search Google Scholar
    • Export Citation
  • Lemone, M. A., F. Chen, M. Tewari, J. Dudhia, B. Geerts, Q. Miao, R. L. Coulter, and R. L. Grossman, 2010: Simulating the IHOP_2002 fair-weather CBL with the WRF-ARW–Noah modeling system. Part II: Structures from a few kilometers to 100 km across. Mon. Wea. Rev., 138, 745764, doi:10.1175/2009MWR3004.1.

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

  • Lock, N. A., and A. L. Houston, 2014: Empirical examination of the factors regulating thunderstorm initiation. Mon. Wea. Rev., 142, 240258, doi:10.1175/MWR-D-13-00082.1.

    • Search Google Scholar
    • Export Citation
  • Mellor, G. L., and T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys., 20, 851875, doi:10.1029/RG020i004p00851.

    • Search Google Scholar
    • Export Citation
  • Mirocha, J., B. Kosović, and G. Kirkil, 2014: Resolved turbulence characteristics in large-eddy simulations nested within mesoscale simulations using the weather research and forecasting model. Mon. Wea. Rev., 142, 806831, doi:10.1175/MWR-D-13-00064.1.

    • Search Google Scholar
    • Export Citation
  • Moeng, C.-H., J. Dudhia, J. Klemp, and P. Sullivan, 2007: Examining two-way grid nesting for large eddy simulation of the PBL using the WRF model. Mon. Wea. Rev., 135, 22952311, doi:10.1175/MWR3406.1.

    • Search Google Scholar
    • Export Citation
  • Morrison, H. G., 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, 9911007, doi:10.1175/2008MWR2556.1.

    • Search Google Scholar
    • Export Citation
  • Muñoz-Esparza, D., B. Kosović, J. Mirocha, and J. van Beeck, 2014: Bridging the transition from mesoscale to microscale turbulence in numerical weather prediction models. Bound.-Layer Meteor., 153, 409440, doi:10.1007/s10546-014-9956-9.

    • Search Google Scholar
    • Export Citation
  • 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, 401427, doi:10.1023/A:1022146015946.

    • Search Google Scholar
    • Export Citation
  • Nowotarski, C. J., P. M. Markowski, Y. P. Richardson, and G. H. Bryan, 2014: Properties of a simulated convective boundary layer in an idealized supercell thunderstorm environment. Mon. Wea. Rev., 142, 39553976, doi:10.1175/MWR-D-13-00349.1.

    • Search Google Scholar
    • Export Citation
  • NWS, 2014: Service assessment: May 2013 Oklahoma tornadoes and flash flooding. National Weather Service, 63 pp. [Available online at http://www.nws.noaa.gov/om/assessments/pdfs/13oklahoma_tornadoes.pdf.]

  • Peters, J. M., and R. S. Schumacher, 2015a: Mechanisms for organization and echo training in a flash-flood-producing mesoscale convective system. Mon. Wea. Rev., 143, 10581085, doi:10.1175/MWR-D-14-00070.1.

    • Search Google Scholar
    • Export Citation
  • Peters, J. M., and R. S. Schumacher, 2015b: The simulated structure and evolution of a quasi-idealized warm-season convective system with a training convective line. J. Atmos. Sci., 72, 1987–2010, doi:10.1175/JAS-D-14-0215.1.

    • Search Google Scholar
    • Export Citation
  • Potvin, C., and M. Flora, 2015: Sensitivity of idealized supercell simulations to horizontal grid spacing: Implications for warn-on-forecast. Mon. Wea. Rev., 143, 2998–3024, doi:10.1175/MWR-D-14-00416.1.

    • Search Google Scholar
    • Export Citation
  • Schumacher, R. S., and R. H. Johnson, 2005: Organization and environmental properties of extreme-rain-producing mesoscale convective systems. Mon. Wea. Rev., 133, 961976, doi:10.1175/MWR2899.1.

    • Search Google Scholar
    • Export Citation
  • Schwartz, C. S., and Coauthors, 2009: Next-day convection-allowing WRF model guidance: A second look at 2-km versus 4-km grid spacing. Mon. Wea. Rev., 137, 33513372, doi:10.1175/2009MWR2924.1.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp. [Available online at http://www.mmm.ucar.edu/wrf/users/docs/arw_v3_bw.pdf.]

  • Stensrud, D. J., and Coauthors, 2009: Convective-scale warn-on-forecast system: A vision for 2020. Bull. Amer. Meteor. Soc., 90, 14871499, doi:10.1175/2009BAMS2795.1.

    • Search Google Scholar
    • Export Citation
  • Thompson, R. L., B. T. Smith, J. S. Grams, A. R. Dean, and C. Broyles, 2012: Convective modes for significant severe thunderstorms in the contiguous United States. Part II: Supercell and QLCS tornado environments. Wea. Forecasting, 27, 11361154, doi:10.1175/WAF-D-11-00116.1.

    • Search Google Scholar
    • Export Citation
  • Torn, R. D., and G. S. Romine, 2015: Sensitivity of central Oklahoma convection forecasts to upstream potential vorticity anomalies during two strongly forced cases during MPEX. Mon. Wea. Rev., 143, 40644087, doi:10.1175/MWR-D-15-0085.1.

    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., D. J. Stensrud, M. C. Coniglio, R. S. Schumacher, M. E. Baldwin, S. Waugh, and D. T. Conlee, 2015: Mobile radiosonde deployments during the Mesoscale Predictability Experiment (MPEX): Rapid and adaptive sampling of upscale convective feedbacks. Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-14-00258.1, in press.

    • Search Google Scholar
    • Export Citation
  • Trier, S. B., G. S. Romine, D. A. Ahijevych, R. J. Trapp, R. S. Schumacher, M. C. Coniglio, and D. J. Stensrud, 2015: Mesoscale thermodynamic influences on convection initiation near a surface dryline in a convection-permitting ensemble. Mon. Wea. Rev., 143, 3726–3753, doi:10.1175/MWR-D-15-0133.1.

    • Search Google Scholar
    • Export Citation
  • Wakimoto, R. M., H. V. Murphey, E. V. Browell, and S. Ismail, 2006: The “triple point” on 24 May 2002 during IHOP. Part I: Airborne Doppler and LASE analyses of the frontal boundaries and convection initiation. Mon. Wea. Rev., 134, 231250, doi:10.1175/MWR3066.1.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., W. C. Skamarock, and J. B. Klemp, 1997: The resolution dependence of explicitly modeled convective systems. Mon. Wea. Rev., 125, 527548, doi:10.1175/1520-0493(1997)125<0527:TRDOEM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., C. Davis, W. Wang, K. W. Manning, and J. B. Klemp, 2008: Experiences with 0–36-h explicit convective forecasts with the WRF-ARW model. Wea. Forecasting, 23, 407437, doi:10.1175/2007WAF2007005.1.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., and Coauthors, 2015: The Mesoscale Predictability Experiment (MPEX). Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-13-00281.1, in press.

    • Search Google Scholar
    • Export Citation
  • Weiss, C. C., and H. B. Bluestein, 2002: Airborne pseudo-dual Doppler analysis of a dryline–outflow boundary intersection. Mon. Wea. Rev., 130, 12071226, doi:10.1175/1520-0493(2002)130<1207:APDDAO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wurman, J., K. Kosiba, P. Robinson, and T. Marshall, 2014: The role of multiple-vortex tornado structure in causing storm researcher fatalities. Bull. Amer. Meteor. Soc., 95, 3145, doi:10.1175/BAMS-D-13-00221.1.

    • Search Google Scholar
    • Export Citation
  • Wyngaard, J. C., 2004: Toward numerical modeling in the “terra incognita.” J. Atmos. Sci., 61, 18161826, doi:10.1175/1520-0469(2004)061<1816:TNMITT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Xue, M., and W. J. Martin, 2006: A high-resolution modeling study of the 24 May 2002 dryline case during IHOP. Part II: Horizontal convective rolls and convective initiation. Mon. Wea. Rev., 134, 172191, doi:10.1175/MWR3072.1.

    • Search Google Scholar
    • Export Citation
  • Ziegler, C. L., E. N. Rasmussen, M. S. Buban, Y. P. Richardson, L. J. Miller, and R. M. Rabin, 2007: The “triple point” on 24 May 2002 during IHOP. Part II: Ground-radar and in situ boundary layer analysis of cumulus development and convection initiation. Mon. Wea. Rev., 135, 24432472, doi:10.1175/MWR3411.1.

    • Search Google Scholar
    • Export Citation
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