Editorial Type:
Article
Article Type:
Research Article

Dryline Position Errors in Experimental Convection-Allowing NSSL-WRF Model Forecasts and the Operational NAM

Brice E. Coffer School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Lindsay C. Maudlin School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Peter G. Veals School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Adam J. Clark Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma

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Print Publication:
01 Jun 2013
DOI:
https://doi.org/10.1175/WAF-D-12-00092.1
Page(s):
746–761
Restricted access

Abstract

This study evaluates 24-h forecasts of dryline position from an experimental 4-km grid-spacing version of the Weather Research and Forecasting Model (WRF) run daily at the National Severe Storms Laboratory (NSSL), as well as the 12-km grid-spacing North America Mesoscale Model (NAM) run operationally by the Environmental Modeling Center of NCEP. For both models, 0000 UTC initializations are examined, and for verification 0000 UTC Rapid Update Cycle (RUC) analyses are used. For the period 1 April–30 June 2007–11, 116 cases containing drylines in all three datasets were identified using a manual procedure that considered specific humidity gradient magnitude, temperature, and 10-m wind. For the 24-h NAM forecasts, no systematic east–west dryline placement errors were found, and the majority of the east–west errors fell within the range ±0.5° longitude. The lack of a systematic bias was generally present across all subgroups of cases categorized according to month, weather pattern, and year. In contrast, a systematic eastward bias was found in 24-h NSSL-WRF forecasts, which was consistent across all subgroups of cases. The eastward biases seemed to be largest for the subgroups that favored “active” drylines (i.e., those associated with a progressive synoptic-scale weather system) as opposed to “quiescent” drylines that tend to be present with weaker tropospheric flow and have eastward movement dominated by vertical mixing processes in the boundary layer.

Current affiliation: North Carolina State University, Raleigh, North Carolina.

Current affiliation: The University of Arizona, Tucson, Arizona.

Current affiliation: University of Utah, Salt Lake City, Utah.

Corresponding author address: Brice E. Coffer, Dept. of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Campus Box 8208, Raleigh, NC 27695-8208. E-mail: becoffer@ncsu.edu

Abstract

This study evaluates 24-h forecasts of dryline position from an experimental 4-km grid-spacing version of the Weather Research and Forecasting Model (WRF) run daily at the National Severe Storms Laboratory (NSSL), as well as the 12-km grid-spacing North America Mesoscale Model (NAM) run operationally by the Environmental Modeling Center of NCEP. For both models, 0000 UTC initializations are examined, and for verification 0000 UTC Rapid Update Cycle (RUC) analyses are used. For the period 1 April–30 June 2007–11, 116 cases containing drylines in all three datasets were identified using a manual procedure that considered specific humidity gradient magnitude, temperature, and 10-m wind. For the 24-h NAM forecasts, no systematic east–west dryline placement errors were found, and the majority of the east–west errors fell within the range ±0.5° longitude. The lack of a systematic bias was generally present across all subgroups of cases categorized according to month, weather pattern, and year. In contrast, a systematic eastward bias was found in 24-h NSSL-WRF forecasts, which was consistent across all subgroups of cases. The eastward biases seemed to be largest for the subgroups that favored “active” drylines (i.e., those associated with a progressive synoptic-scale weather system) as opposed to “quiescent” drylines that tend to be present with weaker tropospheric flow and have eastward movement dominated by vertical mixing processes in the boundary layer.

Current affiliation: North Carolina State University, Raleigh, North Carolina.

Current affiliation: The University of Arizona, Tucson, Arizona.

Current affiliation: University of Utah, Salt Lake City, Utah.

Corresponding author address: Brice E. Coffer, Dept. of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Campus Box 8208, Raleigh, NC 27695-8208. E-mail: becoffer@ncsu.edu
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  • Beebe, R. G., 1958: An instability line development as observed by the tornado research airplane. J. Meteor., 15, 278–282.

  • Benjamin, S. G., and Coauthors, 2004a: An hourly assimilation–forecast cycle: The RUC. Mon. Wea. Rev., 132, 495–518.

  • Benjamin, S. G., Grell G. A. , Brown J. M. , Smirnova T. G. , and Bleck R. , 2004b: Mesoscale weather prediction with the RUC hybrid isentropic–terrain-following coordinate model. Mon. Wea. Rev., 132, 473–494.

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

    • Search Google Scholar
    • Export Citation

  • Bluestein, H., 1993: Observations and Theory of Weather Systems. Vol. 2, Synoptic–Dynamic Meteorology in Midlatitudes, Oxford University Press, 594 pp.

  • Bothwell, P. D., Hart J. A. , and Thompson R. L. , 2002: An integrated three-dimensional objective analysis scheme in use at the Storm Prediction Center. Preprints, 21st Conf. on Severe Local Storms/19th Conf. on Weather Analysis and Forecasting/15th Conf. on Numerical Weather Prediction, San Antonio, TX, Amer. Meteor. Soc., JP3.1. [Available online at https://ams.confex.com/ams/pdfpapers/47482.pdf.]

  • Chen, F., and Dudhia J. , 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

  • Clark, A. J., Gallus W. A. Jr., Xue M. , and Kong F. , 2009: A comparison of precipitation forecast skill between small convection-allowing and large convection-parameterizing ensembles. Wea. Forecasting, 24, 1121–1140.

    • Search Google Scholar
    • Export Citation

  • Clark, A. J., Gallus W. A. Jr., Xue M. , and Kong F. , 2010: Growth of spread in convection-allowing and convection-parameterizing ensembles. Wea. Forecasting, 25, 594–612.

    • Search Google Scholar
    • Export Citation

  • Clark, A. J., and Coauthors, 2011: Probabilistic precipitation forecast skill as a function of ensemble size and spatial scale in a convection-allowing ensemble. Mon. Wea. Rev., 139, 1410–1418.

    • 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, 55–74.

    • Search Google Scholar
    • Export Citation

  • Coniglio, M. C., Elmore K. L. , Kain J. S. , Weiss S. J. , Xue M. , and Weisman M. L. , 2010: Evaluation of WRF model output for severe-weather forecasting from the 2008 NOAA Hazardous Weather Testbed Spring Experiment. Wea. Forecasting, 25, 408–427.

    • Search Google Scholar
    • Export Citation

  • Coniglio, M. C., Correia J. , Marsh P. T. , and Kong F. , 2013: Verification of convection-allowing WRF model forecasts of the planetary boundary layer using sounding observations. Wea. Forecasting, 28, 842–862.

    • Search Google Scholar
    • Export Citation

  • Crawford, T. M., and Bluestein H. B. , 1997: Characteristics of dryline passage. Mon. Wea. Rev., 125, 463–477.

  • Dodd, A. V., 1965: Dewpoint distribution in the contiguous United States. Mon. Wea. Rev., 93, 113–122.

  • 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.

    • Search Google Scholar
    • Export Citation

  • Fels, S. B., and Schwarzkopf M. D. , 1975: The simplified exchange approximation: A new method for radiative transfer calculations. J. Atmos. Sci., 32, 1475–1488.

    • Search Google Scholar
    • Export Citation

  • Ferrier, B. S., Jin Y. , Lin Y. , Black T. , Rogers E. , and DiMego G. , 2002: Implementation of a new grid-scale cloud and rainfall scheme in the NCEP Eta Model. Preprints, 19th Conf. on Weather Analysis and Forecasting/15th Conf. on Numerical Weather Prediction, San Antonio, TX, Amer. Meteor. Soc., 280–283.

  • Fujita, T. T., 1958: Structure and movement of a dry front. Bull. Amer. Meteor. Soc., 39, 574–582.

  • Geerts, B., 2008: Dryline characteristics near Lubbock, Texas, based on radar and West Texas Mesonet data for May 2005 and May 2006. Wea. Forecasting, 23, 392–406.

    • Search Google Scholar
    • Export Citation

  • Hane, C. E., 2004: Quiescent and synoptically-active drylines: A comparison based upon case studies. Meteor. Atmos. Phys., 86, 195–211.

    • Search Google Scholar
    • Export Citation

  • Hane, C. E., Ziegler C. L. , and Bluestein H. B. , 1993: Investigation of the dryline and convective storms initiated along the dryline: Field experiments during COPS-91. Bull. Amer. Meteor. Soc., 74, 2133–2145.

    • Search Google Scholar
    • Export Citation

  • Hane, C. E., Baldwin M. E. , Bluestein H. B. , Crawford T. M. , and Rabin R. M. , 2001: A case study of severe storm development along a dryline within a synoptically active environment. Part I: Dryline motion and an Eta Model forecast. Mon. Wea. Rev., 129, 2183–2204.

    • Search Google Scholar
    • Export Citation

  • Hoch, J., and Markowski P. , 2005: A climatology of springtime dryline position in the U.S. Great Plains region. J. Climate, 18, 2132–2137.

    • Search Google Scholar
    • Export Citation

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

  • Hoskins, B. J., and Bretherton F. P. , 1972: Atmospheric frontogenesis models: Mathematical formulation and solution. J. Atmos. Sci., 29, 11–37.

    • 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

  • 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.

  • Janjić, Z. I., 2003: A nonhydrostatic model based on a new approach. Meteor. Atmos. Phys., 82, 271–285.

  • Johnson, A., Wang X. , Kong F. , and Xue M. , 2011a: Hierarchical cluster analysis of a convection-allowing ensemble during the Hazardous Weather Testbed 2009 Spring Experiment. Part I: Development of the object-oriented cluster analysis method for precipitation fields. Mon. Wea. Rev., 139, 3673–3693.

    • Search Google Scholar
    • Export Citation

  • Johnson, A., Wang X. , Xue M. , and Kong F. , 2011b: Hierarchical cluster analysis of a convection-allowing ensemble during the Hazardous Weather Testbed 2009 Spring Experiment. Part II: Ensemble clustering over the whole experiment period. Mon. Wea. Rev., 139, 3694–3710.

    • 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, 931–952.

    • Search Google Scholar
    • Export Citation

  • Kain, J. S., and Coauthors, 2010a: Assessing advances in the assimilation of radar data and other mesoscale observations within a collaborative forecasting–research environment. Wea. Forecasting, 25, 1510–1521.

    • Search Google Scholar
    • Export Citation

  • Kain, J. S., Dembek S. R. , Weiss S. J. , Case J. L. , Levit J. J. , and Sobash R. A. , 2010b: Extracting unique information from high-resolution forecast models: Monitoring selected fields and phenomena every time step. Wea. Forecasting, 25, 1536–1542.

    • Search Google Scholar
    • Export Citation

  • Lacis, A. A., and Hansen J. E. , 1974: A parameterization for the absorption of solar radiation in the earth's atmosphere. J. Atmos. Sci., 31, 118–133.

    • Search Google Scholar
    • Export Citation

  • 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.

    • Search Google Scholar
    • Export Citation

  • Markowski, P. M., and Richardson Y. P. , 2010: Mesoscale Meteorology in Midlatitudes. Wiley-Blackwell, 407 pp.

  • Marsh, P. T., Kain J. S. , Lakshmanan V. , Clark A. J. , Hitchens N. M. , and Hardy J. , 2012: A method for calibrating deterministic forecasts of rare events. Wea. Forecasting, 27, 531–538.

    • Search Google Scholar
    • Export Citation

  • McGuire, E. L., 1962: The vertical structure of three drylines as revealed by aircraft traverses. National Severe Storms Laboratory Rep. 7, 10 pp.

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

    • Search Google Scholar
    • Export Citation

  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343–360.

  • Mlawer, E. J., Taubman S. J. , Brown P. D. , Iacono M. J. , and Clough S. A. , 1997: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the long-wave. J. Geophys. Res., 102 (D14), 16 663–16 682.

    • Search Google Scholar
    • Export Citation

  • Peterson, R. E., 1983: The west Texas dryline: Occurrence and behavior. Preprints, 13th Conf. on Severe Local Storms, Tulsa, OK, Amer. Meteor. Soc., J9–J11.

  • Pielke, R. A., Dalu G. A. , Snook J. S. , Lee T. J. , and Kittel T. G. F. , 1991: Nonlinear influence of mesoscale land use on weather and climate. J. Climate, 4, 1053–1069.

    • Search Google Scholar
    • Export Citation

  • Pietrycha, A. E., and Rasmussen E. N. , 2001: Observations of the Great Plains dryline utilizing mobile mesonet data. Preprints, Ninth Conf. on Mesoscale Processes, Fort Lauderdale, FL, Amer. Meteor. Soc., P5.23. [Available online at https://ams.confex.com/ams/pdfpapers/22296.pdf.]

  • R Development Core Team, cited 2012: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. [Available online at http://www.R-project.org.]

  • Rhea, J. O., 1966: A study of thunderstorm formation along dry lines. J. Appl. Meteor., 5, 59–63.

  • Richter, H., and Bosart L. F. , 2002: The suppression of deep moist convection near the southern Great Plains dryline. Mon. Wea. Rev., 130, 1665–1691.

    • Search Google Scholar
    • Export Citation

  • Roberts, N. M., and Lean H. W. , 2008: Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Mon. Wea. Rev., 136, 78–97.

    • Search Google Scholar
    • Export Citation

  • Rogers, E., and Coauthors, 2009: The NCEP North American Mesoscale modeling system: Recent changes and future plans. Preprints, 23rd Conf. on Weather Analysis and Forecasting/19th Conf. on Numerical Weather Prediction, Omaha, NE, Amer. Meteor. Soc., 2A.4. [Available online at https://ams.confex.com/ams/pdfpapers/154114.pdf.]

  • Schaefer, J. T., 1974a: The life cycle of the dryline. J. Appl. Meteor., 13, 444–449.

  • Schaefer, J. T., 1974b: A simulative model of dryline motion. J. Atmos. Sci., 31, 956–964.

  • Schaefer, J. T., 1986: The dryline. Mesoscale Meteorology and Forecasting, P. S. Ray, Ed., Amer. Meteor. Soc., 549–572.

  • Schultz, D. M., Weiss C. C. , and Hoffman P. M. , 2007: The synoptic regulation of dryline intensity. Mon. Wea. Rev., 135, 1699–1709.

  • 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, 3351–3372.

    • Search Google Scholar
    • Export Citation

  • Schwartz, C. S., and Coauthors, 2010: Toward improved convection-allowing ensembles: Model physics sensitivities and optimizing probabilistic guidance with small ensemble membership. Wea. Forecasting, 25, 263–280.

    • Search Google Scholar
    • Export Citation

  • Schwarzkopf, M. D., and Fels S. B. , 1991: The simplified exchange method revisited—An accurate, rapid method for computation of infrared cooling rates and fluxes. J. Geophys. Res., 96 (D5), 9075–9096.

    • 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.pdf.]

  • Sobash, R. A., Kain J. S. , Bright D. R. , Dean A. R. , Coniglio M. C. , and Weiss S. J. , 2011: Probabilistic forecast guidance for severe thunderstorms based on the identification of extreme phenomena in convection-allowing model forecasts. Wea. Forecasting, 26, 714–728.

    • Search Google Scholar
    • Export Citation

  • Sun, J., Trier S. B. , Xiao Q. , Weisman M. L. , Wang H. , Ying Z. , Xu M. , and Zhang Y. , 2012: Sensitivity of 0–12-h warm-season precipitation forecasts over the central United States to model initialization. Wea. Forecasting, 27, 832–855.

    • Search Google Scholar
    • Export Citation

  • Wakimoto, R. M., Murphey H. V. , Browell E. V. , and Ismail S. , 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, 231–249.

    • 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.

    • Search Google Scholar
    • Export Citation

  • Weiss, C. C., and Bluestein H. B. , 2002: Airborne pseudo–dual Doppler analysis of a dryline–outflow boundary intersection. Mon. Wea. Rev., 130, 1207–1226.

    • Search Google Scholar
    • Export Citation

  • Wolff, J. K., Ferrier B. S. , and Mass C. F. , 2012: Establishing closer collaboration to improve model physics for short-range forecasts. Bull. Amer. Meteor. Soc., 93, ES51–ES53.

    • Search Google Scholar
    • Export Citation

  • Wu, W. S., Purser R. J. , and Parrish D. F. , 2002: Three-dimensional variational analysis with spatially inhomogeneous covariances. Mon. Wea. Rev., 130, 2905–2916.

    • Search Google Scholar
    • Export Citation

  • Wyngaard, J. C., 2004: Toward numerical modeling in the “terra incognita.” J. Atmos. Sci., 61, 1816–1826.

  • Xue, M., and Martin W. J. , 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, 172–191.

    • Search Google Scholar
    • Export Citation

  • Ziegler, C. L., and Rasmussen E. N. , 1998: The initiation of moist convection at the dryline: Forecasting issues from a case study perspective. Wea. Forecasting, 13, 1106–1131.

    • Search Google Scholar
    • Export Citation

  • Ziegler, C. L., Lee T. J. , and Pielke R. A. , 1997: Convective initiation at the dryline: A modeling study. Mon. Wea. Rev., 125, 1001–1026.

    • Search Google Scholar
    • Export Citation
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