Processes Associated with Convection Initiation in the North American Mesoscale Forecast System, Version 3 (NAMv3)

Michael Colbert Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, and National Weather Service–Weather Forecast Office, State College, Pennsylvania

Search for other papers by Michael Colbert in
Current site
Google Scholar
PubMed
Close
,
David J. Stensrud Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by David J. Stensrud in
Current site
Google Scholar
PubMed
Close
,
Paul M. Markowski Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by Paul M. Markowski in
Current site
Google Scholar
PubMed
Close
, and
Yvette P. Richardson Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by Yvette P. Richardson in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

In support of the Next Generation Global Prediction System (NGGPS) project, processes leading to convection initiation in the North American Mesoscale Forecast System, version 3 (NAMv3) are explored. Two severe weather outbreaks—occurring over the southeastern United States on 28 April 2014 and the central Great Plains on 6 May 2015—are forecast retrospectively using the NAMv3 CONUS (4 km) and Fire Weather (1.33 km) nests, each with 5-min output. Points of convection initiation are identified, and patterns leading to convection initiation in the model forecasts are determined. Results indicate that in the 30 min preceding convection initiation at a grid point, upward motion at low levels of the atmosphere enables a parcel to rise to its level of free convection, above which it is accelerated by the buoyancy force. A moist absolutely unstable layer (MAUL) typically is produced at the top of the updraft. However, when strong updrafts are collocated with large vertical gradients of potential temperature and moisture, noisy vertical profiles of temperature, moisture, and hydrometeor concentration develop beneath the rising MAUL. The noisy profiles found in this study are qualitatively similar to those that resulted in NAMv3 failures during simulations of Hurricane Joaquin in 2015. The CM1 cloud model is used to reproduce these noisy profiles, and results indicate that the noise can be mitigated by including explicit vertical diffusion in the model. Left unchecked, the noisy profiles are shown to impact convective storm features such as cold pools, precipitation, updraft helicity intensity and tracks, and the initiation of spurious convection.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. David J. Stensrud, david.stensrud@psu.edu

Abstract

In support of the Next Generation Global Prediction System (NGGPS) project, processes leading to convection initiation in the North American Mesoscale Forecast System, version 3 (NAMv3) are explored. Two severe weather outbreaks—occurring over the southeastern United States on 28 April 2014 and the central Great Plains on 6 May 2015—are forecast retrospectively using the NAMv3 CONUS (4 km) and Fire Weather (1.33 km) nests, each with 5-min output. Points of convection initiation are identified, and patterns leading to convection initiation in the model forecasts are determined. Results indicate that in the 30 min preceding convection initiation at a grid point, upward motion at low levels of the atmosphere enables a parcel to rise to its level of free convection, above which it is accelerated by the buoyancy force. A moist absolutely unstable layer (MAUL) typically is produced at the top of the updraft. However, when strong updrafts are collocated with large vertical gradients of potential temperature and moisture, noisy vertical profiles of temperature, moisture, and hydrometeor concentration develop beneath the rising MAUL. The noisy profiles found in this study are qualitatively similar to those that resulted in NAMv3 failures during simulations of Hurricane Joaquin in 2015. The CM1 cloud model is used to reproduce these noisy profiles, and results indicate that the noise can be mitigated by including explicit vertical diffusion in the model. Left unchecked, the noisy profiles are shown to impact convective storm features such as cold pools, precipitation, updraft helicity intensity and tracks, and the initiation of spurious convection.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. David J. Stensrud, david.stensrud@psu.edu
Save
  • Aligo, E. A., B. Ferrier, and J. R. Carley, 2018: Modified NAM microphysics for forecasts of deep convective storms. Mon. Wea. Rev., 146, 41154153, https://doi.org/10.1175/MWR-D-17-0277.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Benjamin, S. G., S. Weygandt, C. Alexander, J. M. Brown, T. G. Smirnova, P. Hofmann, E. James, and G. Dimego, 2011: NOAA’s hourly-updated 3km HRRR and RUC/Rapid Refresh—Recent (2010) and upcoming changes toward improving weather guidance for air-traffic management. Second Aviation, Range, and Aerospace Meteorology Special Symp. on Weather–Air Traffic Management Integration, Seattle, WA, Amer. Meteor. Soc., 3.2, https://ams.confex.com/ams/91Annual/webprogram/Paper185659.html.

  • Bryan, G. H., and J. M. Fritsch, 2000: Moist absolute instability: The sixth static stability state. Bull. Amer. Meteor. Soc., 81, 12071230, https://doi.org/10.1175/1520-0477(2000)081<1287:MAITSS>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., and J. M. Fritsch, 2002: A benchmark simulation for moist nonhydrostatic numerical models. Mon. Wea. Rev., 130, 29172928, https://doi.org/10.1175/1520-0493(2002)130<2917:ABSFMN>2.0.CO;2.

    • Crossref
    • 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, https://doi.org/10.1175/WAF-D-13-00089.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Burlingame, B. M., C. Evans, and P. J. Roebber, 2017: The influence of PBL parameterization on the practical predictability of convection initiation during the Mesoscale Predictability Experiment (MPEX). Wea. Forecasting, 32, 11611183, https://doi.org/10.1175/WAF-D-16-0174.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clark, A. J., W. A. Gallus Jr., M. Xue, and F. Kong, 2009: A comparison of precipitation forecast skill between small convection-allowing and large convection-parameterizing ensembles. Wea. Forecasting, 24, 11211140, https://doi.org/10.1175/2009WAF2222222.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Done, J., C. 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, https://doi.org/10.1002/asl.72.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duda, J. D., and W. A. Gallus, 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, https://doi.org/10.1175/WAF-D-13-00005.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eckermann, S., 2009: Hybrid σ–p coordinate choices for a global model. Mon. Wea. Rev., 137, 224245, https://doi.org/10.1175/2008MWR2537.1.

  • Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J. Geophys. Res., 108, 8851, https://doi.org/10.1029/2002JD003296.

    • Search Google Scholar
    • Export Citation
  • Ferrier, B. S., Z. Janjić, E. Aligo, D. Jovic, E. Roger, J. R. Carley, M. Pyle, and G. J. DiMego, 2017: NMMB model changes as part of the NAMv4 upgrade. 28th Conf. on Weather Analysis and Forecasting/24th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., 1205, https://ams.confex.com/ams/97Annual/webprogram/Paper312628.html.

  • Fowle, M. A., and P. J. Roebber, 2003: Short-range (0–48 h) numerical prediction of convective occurrence, mode, and location. Wea. Forecasting, 18, 782794, https://doi.org/10.1175/1520-0434(2003)018<0782:SHNPOC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gremillion, M. S., and R. E. Orville, 1999: Thunderstorm characteristics of cloud-to-ground lightning at the Kennedy Space Center, Florida: A study of lightning initiation signatures as indicated by the WSR-88D. Wea. Forecasting, 14, 640649, https://doi.org/10.1175/1520-0434(1999)014<0640:TCOCTG>2.0.CO;2.

    • Crossref
    • 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, https://doi.org/10.1029/2008JD009944.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Janjić, Z., 1990: The step-mountain coordinate: Physical package. Mon. Wea. Rev., 118, 14291443, https://doi.org/10.1175/1520-0493(1990)118<1429:TSMCPP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Janjić, Z., 1994: The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122, 927945, https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Janjić, Z., and R. Gall, 2012: Scientific documentation of the NCEP nonhydrostatic multiscale model on the B grid (NMMB). Part 1 Dynamics. NCAR Tech. Note NCAR/TN-489+STR, https://doi.org/10.5065/D6WH2MZX.

    • Crossref
    • Export Citation
  • Janjić, Z., T. L. Black, M. E. Pyle, H.-Y. Chuang, E. Rogers, and G. J. DiMego, 2005: The NCEP WRF-NMM core. Preprints, Joint WRF/MM5 User’s Workshop, Boulder, CO, NCAR, 2.9, http://www2.mmm.ucar.edu/wrf/users/workshops/WS2005/presentations/session2/9-Janjic.pdf.

  • Kain, J. S., S. J. Weiss, J. J. Levit, M. E. Baldwin, and D. R. Bright, 2006: Examination of convection-allowing configurations of the WRF model for the prediction of severe convective weather: The SPC/NSSL Spring Program 2004. Wea. Forecasting, 21, 167181, https://doi.org/10.1175/WAF906.1.

    • Crossref
    • 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, https://doi.org/10.1175/WAF2007106.1.

    • Crossref
    • 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, https://doi.org/10.1175/BAMS-D-11-00264.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lane, T. P., R. D. Sharman, T. L. Clark, and H. Hsu, 2003: An investigation of turbulence generation mechanisms above deep convection. J. Atmos. Sci., 60, 12971321, https://doi.org/10.1175/1520-0469(2003)60<1297:AIOTGM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lean, H. W., P. A. Clark, M. Dixon, N. M. Roberts, A. Fitch, R. Forbes, and C. Halliwell, 2008: Characteristics of high-resolution versions of the Met Office Unified Model for forecasting convection over the United Kingdom. Mon. Wea. Rev., 136, 34083424, https://doi.org/10.1175/2008MWR2332.1.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Loftus, A. M., D. B. Weber, and C. A. Doswell, 2008: Parameterized mesoscale forcing mechanisms for initiating numerically simulated isolated multicellular convection. Mon. Wea. Rev., 136, 24082421, https://doi.org/10.1175/2007MWR2133.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mecikalski, J. R., and K. M. Bedka, 2006: Forecasting convective initiation by monitoring the evolution of moving cumulus in daytime GOES imagery. Mon. Wea. Rev., 134, 4978, https://doi.org/10.1175/MWR3062.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16 66316 682, https://doi.org/10.1029/97JD00237.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morrison, H., J. A. Curry, M. D. Shupe, and P. Zuidema, 2005: A new double-moment microphysics parameterization for application in cloud and climate models. Part II: Single-column modeling of arctic clouds. J. Atmos. Sci., 62, 16781693, https://doi.org/10.1175/JAS3447.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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, 9911007, https://doi.org/10.1175/2008MWR2556.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • NEMS-NMMB, 2016: Community NEMS-NMMB users’ guide V1.0. Developmental Testbed Center, 91 pp., http://www.dtcenter.org/nems-nmmb/users/tutorial/nmmb_users_guide.pdf.

  • Roberts, N. M., and H. W. Lean, 2008: Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Mon. Wea. Rev., 136, 7897, https://doi.org/10.1175/2007MWR2123.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roberts, R. D., and S. Rutledge, 2003: Nowcasting storm initiation and growth using GOES-8 and WSR-88D data. Wea. Forecasting, 18, 562584, https://doi.org/10.1175/1520-0434(2003)018<0562:NSIAGU>2.0.CO;2.

    • Crossref
    • 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., https://doi.org/10.5065/D68S4MVH.

    • Crossref
    • Export Citation
  • Smagorinsky, J., 1963: General circulation experiments with the primitive equations. Mon. Wea. Rev., 91, 99164, https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Snively, D. V., and W. A. Gallus, 2014: Prediction of convective morphology in near-cloud-permitting WRF model simulations. Wea. Forecasting, 29, 130149, https://doi.org/10.1175/WAF-D-13-00047.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sobash, R. A., J. S. Kain, D. R. Bright, A. R. Dean, M. C. Coniglio, and S. J. Weiss, 2011: Probabilistic forecast guidance for severe thunderstorms based on the identification of extreme phenomena in convection-allowing model forecasts. Wea. Forecasting, 26, 714728, https://doi.org/10.1175/WAF-D-10-05046.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., and J. B. Klemp, 1982: The dependence of numerically simulated convective storms on vertical wind shear and buoyancy. Mon. Wea. Rev., 110, 504520, https://doi.org/10.1175/1520-0493(1982)110<0504:TDONSC>2.0.CO;2.

    • Crossref
    • 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, https://doi.org/10.1175/2007WAF2007005.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ziegler, C. L., and E. N. Rasmussen, 1998: The initiation of moist convection at the dryline: Forecasting issues from a case study perspective. Wea. Forecasting, 13, 11061131, https://doi.org/10.1175/1520-0434(1998)013<1106:TIOMCA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 2901 1638 83
PDF Downloads 774 243 12