Editorial Type:
Article
Article Type:
Research Article

Some Practical Considerations Regarding Horizontal Resolution in the First Generation of Operational Convection-Allowing NWP

John S. Kain NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma

Search for other papers by John S. Kain in
Current site
Google Scholar
PubMed Close
,
Steven J. Weiss NOAA/NWS/Storm Prediction Center, Norman, Oklahoma

Search for other papers by Steven J. Weiss in
Current site
Google Scholar
PubMed Close
,
David R. Bright NOAA/NWS/Storm Prediction Center, Norman, Oklahoma

Search for other papers by David R. Bright in
Current site
Google Scholar
PubMed Close
,
Michael E. Baldwin Department of Earth and Atmospheric Sciences, Purdue University, West Lafayette, Indiana

Search for other papers by Michael E. Baldwin in
Current site
Google Scholar
PubMed Close
,
Jason J. Levit NOAA/NWS/Storm Prediction Center, Norman, Oklahoma

Search for other papers by Jason J. Levit in
Current site
Google Scholar
PubMed Close
,
Gregory W. Carbin NOAA/NWS/Storm Prediction Center, Norman, Oklahoma

Search for other papers by Gregory W. Carbin in
Current site
Google Scholar
PubMed Close
,
Craig S. Schwartz School of Meteorology, University of Oklahoma, Norman, Oklahoma

Search for other papers by Craig S. Schwartz in
Current site
Google Scholar
PubMed Close
,
Morris L. Weisman National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Morris L. Weisman in
Current site
Google Scholar
PubMed Close
,
Kelvin K. Droegemeier School of Meteorology, University of Oklahoma, Norman, Oklahoma
* Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

Search for other papers by Kelvin K. Droegemeier in
Current site
Google Scholar
PubMed Close
,
Daniel B. Weber * Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

Search for other papers by Daniel B. Weber in
Current site
Google Scholar
PubMed Close
, and
Kevin W. Thomas * Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

Search for other papers by Kevin W. Thomas in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Oct 2008
DOI:
https://doi.org/10.1175/WAF2007106.1
Page(s):
931–952
Restricted access

Abstract

During the 2005 NOAA Hazardous Weather Testbed Spring Experiment two different high-resolution configurations of the Weather Research and Forecasting-Advanced Research WRF (WRF-ARW) model were used to produce 30-h forecasts 5 days a week for a total of 7 weeks. These configurations used the same physical parameterizations and the same input dataset for the initial and boundary conditions, differing primarily in their spatial resolution. The first set of runs used 4-km horizontal grid spacing with 35 vertical levels while the second used 2-km grid spacing and 51 vertical levels.

Output from these daily forecasts is analyzed to assess the numerical forecast sensitivity to spatial resolution in the upper end of the convection-allowing range of grid spacing. The focus is on the central United States and the time period 18–30 h after model initialization. The analysis is based on a combination of visual comparison, systematic subjective verification conducted during the Spring Experiment, and objective metrics based largely on the mean diurnal cycle of the simulated reflectivity and precipitation fields. Additional insight is gained by examining the size distributions of the individual reflectivity and precipitation entities, and by comparing forecasts of mesocyclone occurrence in the two sets of forecasts.

In general, the 2-km forecasts provide more detailed presentations of convective activity, but there appears to be little, if any, forecast skill on the scales where the added details emerge. On the scales where both model configurations show higher levels of skill—the scale of mesoscale convective features—the numerical forecasts appear to provide comparable utility as guidance for severe weather forecasters. These results suggest that, for the geographical, phenomenological, and temporal parameters of this study, any added value provided by decreasing the grid increment from 4 to 2 km (with commensurate adjustments to the vertical resolution) may not be worth the considerable increases in computational expense.

Corresponding author address: John S. Kain, NSSL, 120 David L. Boren Blvd., Norman, OK 73072. Email: jack.kain@noaa.gov

Abstract

During the 2005 NOAA Hazardous Weather Testbed Spring Experiment two different high-resolution configurations of the Weather Research and Forecasting-Advanced Research WRF (WRF-ARW) model were used to produce 30-h forecasts 5 days a week for a total of 7 weeks. These configurations used the same physical parameterizations and the same input dataset for the initial and boundary conditions, differing primarily in their spatial resolution. The first set of runs used 4-km horizontal grid spacing with 35 vertical levels while the second used 2-km grid spacing and 51 vertical levels.

Output from these daily forecasts is analyzed to assess the numerical forecast sensitivity to spatial resolution in the upper end of the convection-allowing range of grid spacing. The focus is on the central United States and the time period 18–30 h after model initialization. The analysis is based on a combination of visual comparison, systematic subjective verification conducted during the Spring Experiment, and objective metrics based largely on the mean diurnal cycle of the simulated reflectivity and precipitation fields. Additional insight is gained by examining the size distributions of the individual reflectivity and precipitation entities, and by comparing forecasts of mesocyclone occurrence in the two sets of forecasts.

In general, the 2-km forecasts provide more detailed presentations of convective activity, but there appears to be little, if any, forecast skill on the scales where the added details emerge. On the scales where both model configurations show higher levels of skill—the scale of mesoscale convective features—the numerical forecasts appear to provide comparable utility as guidance for severe weather forecasters. These results suggest that, for the geographical, phenomenological, and temporal parameters of this study, any added value provided by decreasing the grid increment from 4 to 2 km (with commensurate adjustments to the vertical resolution) may not be worth the considerable increases in computational expense.

Corresponding author address: John S. Kain, NSSL, 120 David L. Boren Blvd., Norman, OK 73072. Email: jack.kain@noaa.gov

Save
Cover Weather and Forecasting
Weather and Forecasting

  • Adlerman, E. J., and Droegemeier K. K. , 2002: The sensitivity of numerically simulated cyclic mesocyclogenesis to variations in model physical and computational parameters. Mon. Wea. Rev., 130 , 2671–2691.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Arakawa, A., 2004: The cumulus parameterization problem: Past, present, and future. J. Climate, 17 , 2493–2525.

  • Baldwin, M. E., and Mitchell K. E. , 1998: Progress on the NCEP hourly multi-sensor U.S. precipitation analysis for operations and GCIP research. Preprints, Second Symp. on Integrated Observing Systems, Phoenix, AZ, Amer. Meteor. Soc., 10–11.

  • Baldwin, M. E., and Wandishin M. S. , 2002: Determining the resolved spatial scales of Eta model precipitation forecasts. Preprints, 15th Conf. on Numerical Weather Prediction, San Antonio, TX, Amer. Meteor. Soc., 85–88.

  • Baldwin, M. E., and Kain J. S. , 2006: Sensitivity of several performance measures to displacement error, bias, and event frequency. Wea. Forecasting, 21 , 636–648.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bélair, S., and Mailhot J. , 2001: Impact of horizontal resolution on the numerical simulation of a midlatitude squall line: Implicit versus explicit condensation. Mon. Wea. Rev., 129 , 2362–2376.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Black, T. L., 1994: The new NMC mesoscale Eta Model: Description and forecast examples. Wea. Forecasting, 9 , 265–278.

  • Bryan, G. H., Wyngaard J. C. , and Fritsch J. M. , 2003: Resolution requirements for the simulation of deep moist convection. Mon. Wea. Rev., 131 , 2394–2416.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Chen, F., Manning K. W. , Yates D. N. , LeMone M. A. , Trier S. B. , Cuenca R. , and Niyogi D. , 2004: Development of high resolution land data assimilation system and its application to WRF. Preprints, 16th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., 22.3. [Available online at http://ams.confex.com/ams/pdfpapers/67333.pdf.].

  • Davis, C., and Coauthors, 2004: The Bow Echo and MCV Experiment (BAMEX): Observations and opportunities. Bull. Amer. Meteor. Soc., 85 , 1075–1093.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Deng, A., and Stauffer D. R. , 2006: On improving 4-km mesoscale model simulations. J. Appl. Meteor. Climatol., 45 , 361–381.

  • Done, J., Davis C. , and Weisman M. , 2004: The next generation of NWP: Explicit forecasts of convection using the Weather Research and Forecasting (WRF) model. Atmos. Sci. Lett., 5 , 6. 110–117.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Droegemeier, K. K., Lazarus S. M. , and Davies-Jones R. P. , 1993: The influence of helicity on numerically simulated convective storms. Mon. Wea. Rev., 121 , 2005–2029.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Droegemeier, K. K., Bassett G. , and Xue M. , 1994: Very high-resolution, uniform-grid simulations of deep convection on a massively parallel processor: Implications for small-scale predictability. Preprints, 10th Conf. on Numerical Weather Prediction, Portland, OR, Amer. Meteor. Soc., 376–379.

  • Droegemeier, K. K., Bassett G. , Lilly D. K. , and Xue M. , 1996: Does helicity really play a role in supercell longevity? Preprints, 18th Conf. on Severe Local Storms, San Francisco, CA, Amer. Meteor. Soc., 205–209.

  • 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.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gallus W. A. Jr., , and Segal M. , 2001: Impact of improved initialization of mesoscale features on convective system rainfall in 10-km Eta simulations. Wea. Forecasting, 16 , 680–696.

    • Crossref
    • Search Google Scholar
    • Export Citation

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

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Iacono, M. J., Mlawer E. J. , Clough S. A. , and Morcrette J-J. , 2000: Impact of an improved longwave radiation model, RRTM, on the energy budget and thermodynamic properties of the NCAR Community Climate Model, CCM3. J. Geophys. Res., 105 , 14873–14890.

    • Crossref
    • 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.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Janjić, Z. I., Black T. L. , Pyle M. , Chuang H-Y. , Rogers E. , and DiMego G. , cited. 2007: An evolutionary approach to nonhydrostatic modeling. [Available online at http://www.wrf-model.org/wrfadmin/publications/Chuang_Janjic_NWP50yearsfinalshort.pdf.].

  • Johns, R. H., and Doswell C. A. III, 1992: Severe local storms forecasting. Wea. Forecasting, 7 , 588–612.

  • Jung, J-H., and Arakawa A. , 2004: The resolution dependence of model physics: Illustrations from nonhydrostatic model experiments. J. Atmos. Sci., 61 , 88–102.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kain, J. S., Baldwin M. E. , Weiss S. J. , Janish P. R. , Kay M. P. , and Carbin G. , 2003a: Subjective verification of numerical models as a component of a broader interaction between research and operations. Wea. Forecasting, 18 , 847–860.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kain, J. S., Janish P. R. , Weiss S. J. , Baldwin M. E. , Schneider R. S. , and Brooks H. E. , 2003b: Collaboration between forecasters and research scientists at the NSSL and SPC: The Spring Program. Bull. Amer. Meteor. Soc., 84 , 1797–1806.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kain, J. S., Weiss S. J. , Baldwin M. E. , Carbin G. W. , Bright D. A. , Levit J. J. , and Hart J. A. , 2005: Evaluating high-resolution configurations of the WRF model that are used to forecast severe convective weather: The 2005 SPC/NSSL Spring Program. Preprints, 21th Conf. on Weather Analysis and Forecasting/17th Conf. on Numerical Weather Prediction, Washington, DC, Amer. Meteor. Soc., 2A.5. [Available online at http://ams.confex.com/ams/pdfpapers/94843.pdf.].

    • Crossref
    • Export Citation

  • Kain, J. S., Weiss S. J. , Levit J. J. , Baldwin M. E. , and Bright D. R. , 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 , 167–181.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kalb, M. W., 1987: The role of convective parameterization in the simulation of a Gulf coast precipitation system. Mon. Wea. Rev., 115 , 214–234.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Koch, S. E., Ferrier B. , Stolinga M. , Szoke E. , Weiss S. J. , and Kain J. S. , 2005: The use of simulated radar reflectivity fields in the diagnosis of mesoscale phenomena from high-resolution WRF model forecasts. Preprints, 12th Conf. on Mesoscale Processes, Albuquerque, NM, Amer. Meteor. Soc., J4J.7. [Available online at http://ams.confex.com/ams/pdfpapers/97032.pdf.].

  • Lean, H. W., Clark P. A. , Dixon M. , Roberts N. M. , Fitch A. , Forbes R. , and Halliwell C. , 2008: Characteristics of high-resolution versions of the Met Office Unified Model for forecasting convection over the United Kingdom. Mon. Wea. Rev., 136 , 3408–3424.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lilly, D. K., Bassett G. M. , Droegemeier K. K. , and Bartello P. , 1998: Stratified turbulence in the atmospheric mesoscales. Theor. Comput. Fluid Dyn., 11 , 139–153.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Liu, C., Moncrieff M. W. , and Grabowski W. W. , 2001: Explicit and parameterized realizations of convective cloud systems in TOGA COARE. Mon. Wea. Rev., 129 , 1689–1703.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mesinger, F., 1996: Improvements in quantitative precipitation forecasts with the Eta regional model at the National Centers for Environmental Prediction: The 48-km upgrade. Bull. Amer. Meteor. Soc., 77 , 2637–2650.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mlawer, E. J., Taubman S. J. , Brown P. D. , Iacono M. J. , and Clough S. A. , 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102 , 16663–16682.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Molinari, J. M., and Dudek M. , 1986: Implicit versus explicit convective heating in numerical weather prediction models. Mon. Wea. Rev., 114 , 326–344.

    • Search Google Scholar
    • Export Citation

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

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Narita, M., and Ohmore S. , 2007: Improving precipitation forecasts by the operational nonhydrostatic mesoscale model with the Kain–Fritsch convective parameterization and cloud microphysics. Preprints, 12th Conf. on Mesoscale Processes, Watervillle Valley, NH, Amer. Meteor. Soc., 3.7. [Available online at http://ams.confex.com/ams/pdfpapers/126017.pdf.].

  • Noh, Y., Cheon W. G. , Hong S-Y. , and Raasch S. , 2003: Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data. Bound.-Layer Meteor., 107 , 401–427.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Petch, J. C., 2006: Sensitivity studies of developing convection in a cloud-resolving model. Quart. J. Roy. Meteor. Soc., 132 , 345–358.

  • Petch, J. C., Brown A. R. , and Gray M. E. B. , 2002: The impact of horizontal resolution on the simulations of convective development over land. Quart. J. Roy. Meteor. Soc., 128 , 2031–2044.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Roberts, N. M., 2003: Results from high resolution modeling of convective events. U.K. Met Office Tech. Rep. 402, 47 pp. [Available online at http://www.metoffice.gov.uk/research/nwp/publications/papers/technical_reports/2003/FRTR402/FRTR402.pdf.].

  • Roberts, N. M., 2005: An investigation of the ability of a storm scale configuration of the Met Office NWP model to predict flood-producing rainfall. U.K. Met Office Tech. Rep. 455, 80 pp. [Available online at http://www.metoffice.gov.uk/research/nwp/publications/papers/technical_reports/2005/FRTR455/FRTR455.pdf.].

  • Rosenthal, S. L., 1978: Numerical simulation of tropical cyclone development with latent heat release by the resolvable scales. I: Model description and preliminary results. J. Atmos. Sci., 35 , 258–271.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Seo, D. J., 1998: Real-time estimation of rainfall fields using radar rainfall and rain gauge data. J. Hydrol., 208 , 37–52.

  • Skamarock, W. C., 2004: Evaluating mesoscale NWP models using kinetic energy spectra. Mon. Wea. Rev., 132 , 3019–3032.

  • Skamarock, W. C., Klemp J. B. , Dudhia J. , Gill D. O. , Barker D. M. , Wang W. , and Powers J. G. , 2005: A description of the Advanced Research WRF version 2. NCAR Tech Note NCAR/TN-468+STR, 88 pp. [Available from UCAR Communications, P. O. Box 3000, Boulder, CO 80307.].

  • Speer, M. S., and Leslie L. M. , 2002: The prediction of two cases of severe convection: Implications for forecast guidance. Meteor. Atmos. Phys., 80 , 165–174.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Steppeler, J., Doms G. , Schattler U. , Bitzer H. W. , Gassmann A. , and Damrath U. , 2003: Meso-gamma scale forecasts using the nonhydrostatic model LM. Meteor. Atmos. Phys., 82 , 75–96.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Stumpf, G. J., Witt A. , Mitchell E. D. , Spencer P. L. , Johnson J. T. , Eilts M. D. , Thomas K. W. , and Burgess D. W. , 1998: The National Severe Storms Laboratory Mesocyclone Detection Algorithm for the WSR-88D. Wea. Forecasting, 13 , 304–326.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Weisman, M. L., and Klemp J. B. , 1984: The structure and classification of numerically simulated convective storms in directionally varying wind shears. Mon. Wea. Rev., 112 , 2479–2498.

    • Crossref
    • Search Google Scholar
    • Export Citation

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

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Weisman, M. L., Davis C. , Wang W. , Manning K. W. , and Klemp J. B. , 2008: Experiences with 0–36-h explicit convective forecasts with the WRF-ARW model. Wea. Forecasting, 23 , 407–437.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Weiss, S. J., Kain J. S. , Levit J. J. , Baldwin M. E. , and Bright D. R. , 2004: Examination of several different versions of the WRF model for the prediction of severe convective weather: The SPC/NSSL Spring Program 2004. Preprints, 22nd Conf. on Severe Local Storms, Hyannis, MA, Amer. Meteor. Soc., 17.1. [Available online at http://ams.confex.com/ams/pdfpapers/82052.pdf.].

  • Zhang, D-L., Hsie E-Y. , and Moncrieff M. W. , 1988: A comparison of explicit and implicit prediction of convective and stratiform precipitating weather systems with a meso-β-scale numerical model. Quart. J. Roy. Meteor. Soc., 114 , 31–60.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 2019 580 28
PDF Downloads 1707 452 24