• Alapaty, K., R. Mathur, and T. Odman, 1998: Intercomparison of spatial interpolation schemes for use in nested grid models. Mon. Wea. Rev.,126, 243–249.

    • Crossref
    • Export Citation
  • Benjamin, S. G., and T. N. Carlson, 1986: Some effects of surface heating and topography on the regional severe storm environment. Part I: Three-dimensional simulations. Mon. Wea. Rev.,114, 307–328.

    • Crossref
    • Export Citation
  • Black, T., 1994: The new NMC mesoscale Eta model: Description and forecast examples. Wea. Forecasting,9, 265–278.

    • Crossref
    • Export Citation
  • Bosart, L. F., 1975: SUNYA experimental results in forecasting daily temperature and precipitation. Mon. Wea. Rev.,103, 1013–1020.

    • Crossref
    • Export Citation
  • Brooks, H. E., M. S. Tracton, D. J. Stensrud, G. Dimego, and Z. Toth, 1995: Short-range ensemble forecasting: Report from a workshop, 25–27 July 1994. Bull. Amer. Meteor. Soc.,76, 1617–1624.

  • Cahir, J. J., J. M. Norman, and D. A. Lowry, 1981: Use of a real time computer graphics system in analysis and forecasting. Mon. Wea. Rev.,109, 485–500.

    • Crossref
    • Export Citation
  • Clappier, A., 1998: A correction method for use in multidimensional time-splitting advection algorithms: Application to two- and three-dimensional transport. Mon. Wea. Rev.,126, 232–242.

    • Crossref
    • Export Citation
  • Dallavalle, J. P., 1996: A perspective on the use of model output statistics in objective weather forecasting. Preprints, 15th Conf. on Weather Analysis and Forecasting, Norfolk, VA, Amer. Meteor. Soc., 479–482.

  • Dimego, G. J., K. E. Mitchell, R. A. Petersen, J. E. Hoke, J. P. Gerrity, J. J. Tuccillo, R. L. Wobus, and H.-M. H. Juang, 1992: Changes to NMC’s Regional Analysis and Forecast System. Wea. Forecasting,7, 185–198.

    • Crossref
    • Export Citation
  • Fraedrich, K., and L. M. Leslie, 1987: Combining predictive schemes in short-term forecasting. Mon. Wea. Rev.,115, 1640–1644.

    • Crossref
    • Export Citation
  • Gerrity, J. F., 1977: The LFM model—1976: A documentation. NOAA Tech. Memo. NWS NMC 60, U.S. Dept. of Commerce, Washington, DC, 68 pp.

  • Gyakum, J. R., 1986: Experiments in temperature and precipitation forecasting for Illinois. Wea. Forecasting,1, 77–88.

    • Crossref
    • Export Citation
  • Hamill, T. M., and S. J. Colucci, 1997: Verification of Eta–RSM short-range ensemble forecasts. Mon. Wea. Rev.,125, 1312–1327.

    • Crossref
    • Export Citation
  • Hoke, J. E., N. A. Phillips, G. J. DiMego, J. J. Tuccillo, and J. G. Sela, 1989: The Regional Analysis and Forecast System of the National Meteorological Center. Wea. Forecasting,4, 323–334.

    • Crossref
    • Export Citation
  • Juang, H.-M., and M. Kanamitsu, 1994: The NMC nested regional spectral model. Mon. Wea. Rev.,122, 3–26.

    • Crossref
    • Export Citation
  • Kanamitsu, M., and Coauthors, 1991: Recent changes implemented into the Global Forecast System at NMC. Wea. Forecasting,6, 425–435.

    • Crossref
    • Export Citation
  • Klemp, J. B., and R. B. Wilhelmson, 1978: The simulation of three-dimensional convective storm dynamics. J. Atmos. Sci.,35, 1070–1095.

    • Crossref
    • Export Citation
  • Krishnamurti, T. N., C. M. Kishtawal, T. E. LaRow, D. R. Bachiochi, Z. Zhang, C. E. Williford, S. Gadgil, and S. Surendran, 1999: Improved weather and seasonal climate forecasts from multimodel superensemble. Science,285, 1548–1550.

    • Crossref
    • Export Citation
  • McCalla, C., and E. Kalnay, 1988: Short and medium range forecast skill and the agreement between operational models. Preprints, Eighth Conf. on Numerical Weather Prediction, Baltimore, MD, Amer. Meteor. Soc., 634–640.

  • Molteni, R., R. Buizza, T. N. Palmer, and T. Petroliagis, 1996: The ECMWF ensemble prediction system: Methodology and validation. Quart. J. Roy. Meteor. Soc.,122, 73–119.

    • Crossref
    • Export Citation
  • Mullen, S. L., and D. P. Baumhefner, 1988: Sensitivity to numerical simulations of explosive oceanic cyclogenesis to changes in physical parameterizations. Mon. Wea. Rev.,116, 2289–2329.

    • Crossref
    • Export Citation
  • National Weather Service, 1986: Modeling of physical processes in the Nested Grid Model. NWS Tech. Procedures Bull. 363, National Oceanic and Atmospheric Administration, 5 pp.

  • ——, 1987: Statistical correction for the NGM cold bias. Western Region Tech. Attachment No. 87-44, National Oceanic and Atmospheric Administration, 8 pp.

  • Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center’s spectral statistical-interpolation system. Mon. Wea. Rev.,120, 1747–1763.

    • Crossref
    • Export Citation
  • ——, J. Purser, E. Rogers, and Y. Lin, 1996: The regional 3D-variational analysis for the Eta model. Preprints, 11th Conf. on Numerical Weather Prediction, Norfolk, VA, Amer. Meteor. Soc., 454–455.

  • Rogers, E., D. G. Deaven, and G. J. DiMego, 1995: The regional analysis system for the operational “early” Eta model: Original 80-km configuration and recent changes. Wea. Forecasting,10, 810–825.

  • ——, T. L. Black, D. G. Deaven, G. J. DiMego, Q. Zhao, M. Baldwin, N. W. Junker, and Y. Lin, 1996: Changes to the operational“early” Eta analysis/forecast system at the National Centers for Environmental Prediction. Wea. Forecasting,11, 391–413.

    • Crossref
    • Export Citation
  • Rousseau, D., and P. Chapelet, 1986: A test of the Monte Carlo method using the WMO/CAS intercomparison project data. World Climate Research Programme Rep. 9, WMO/TD-No. 141, 6 pp.

  • Sanders, F., 1973: Skill in forecasting daily temperature and precipitation: Some experimental results. Bull. Amer. Meteor. Soc.,54, 1171–1179.

    • Crossref
    • Export Citation
  • Schlatter, T. W., 1975: Some experiments with a multivariate statistical objective analysis scheme. Mon. Wea. Rev.,103, 246–257.

    • Crossref
    • Export Citation
  • Stensrud, D. J., and J. M. Fritsch, 1994a: Mesoscale convective systems in weakly forced large-scale environments. Part II: Generation of a mesoscale initial condition. Mon. Wea. Rev.,122, 2068–2083.

  • ——, and ——, 1994b: Mesoscale convective systems in weakly forced large-scale environments. Part III: Numerical simulations and implications for operational forecasting. Mon. Wea. Rev.,122, 2084–2104.

    • Crossref
    • Export Citation
  • ——, H. E. Brooks, J. Du, M. S. Tracton, and E. Rogers, 1999: Using ensembles for short-range forecasting. Mon. Wea. Rev.,127, 433–446.

    • Crossref
    • Export Citation
  • Thompson, P. D., 1977: How to improve accuracy by combining independent forecasts. Mon. Wea. Rev.,105, 228–229.

    • Crossref
    • Export Citation
  • Toth, Z., and E. Kalnay, 1993: Ensemble forecasting at NMC: The generation of perturbations. Bull. Amer. Meteor. Soc.,74, 2317–2330.

    • Crossref
    • Export Citation
  • ——, and ——, 1997: Ensemble forecasting at NCEP and the breeding method. Mon. Wea. Rev.,125, 3297–3319.

    • Crossref
    • Export Citation
  • ——, ——, S. M. Tracton, R. Wobus, and J. Irwin, 1997: A synoptic evaluation of the NCEP ensemble. Wea. Forecasting,12, 140–153.

    • Crossref
    • Export Citation
  • ——, Y. Zhu, T. Marchok, M. S. Tracton, and E. Kalnay, 1998: Verification of the NCEP global ensemble forecasts. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., 286–289.

  • Tracton, S., and E. Kalnay, 1993: Ensemble forecasting at NMC: Operational implementation. Wea. Forecasting,8, 379–398.

  • ——, J. Du, Z. Toth, and H. Juang, 1998: Short-range ensemble forecasting (SREF) at NCEP/EMC. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., 269–272.

  • Verret, R., and N. Yacowar, 1989: Improvement of numerical weather element forecasts by combining forecasts from different procedures. Preprints, 11th Conf. on Probability and Statistics, Monterey, CA, Amer. Meteor. Soc., 58–63.

  • Vislocky, R. L., and G. S. Young, 1989: The use of perfect prog forecasts to improve model output statistics forecasts of precipitation probability. Wea. Forecasting,4, 202–209.

    • Crossref
    • Export Citation
  • ——, and J. M. Fritsch, 1995: Improved model output statistics forecasts through model consensus. Bull. Amer. Meteor. Soc.,76, 1157–1164.

    • Crossref
    • Export Citation
  • Winkler, R. L., A. H. Murphy, and R. W. Katz, 1977: The consensus of subjective probability forecasts: Are two, three, . . . heads better than one? Preprints, Fifth Conf. on Probability and Statistics, Las Vegas, NV, Amer. Meteor. Soc., 57–62.

  • Wobus, R. L., and E. Kalnay, 1995: Three years of operational prediction of forecast skill at NMC. Mon. Wea. Rev.,123, 2132–2148.

    • Crossref
    • Export Citation
  • Zhang, D.-L., and J. M. Fritsch, 1988: Numerical sensitivity experiments of varying model physics on the structure, evolution and dynamics of two mesoscale convective systems. J. Atmos. Sci.,45, 261–293.

    • Crossref
    • Export Citation
  • ——, and R. Harvey, 1995: Enhancement of extratropical cyclogenesis by a mesoscale convective system. J. Atmos. Sci.,52, 1107–1127.

    • Crossref
    • Export Citation
  • ——, J. S. Kain, J. M. Fritsch, and K. Gao, 1994: Comments on“Parameterization of convective precipitation in mesoscale numerical models: A critical review.” Mon. Wea. Rev.,122, 2222–2231.

    • Crossref
    • Export Citation
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Model Consensus

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  • 1 Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania
  • | 2 The Forecast Institute, State College, Pennsylvania
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Abstract

Consensus forecasts from the control runs of several operational numerical models are compared to 1) the control-run forecasts of the individual models that compose the consensus and to 2) other consensus forecasts generated by varying the initial conditions of the various individual models. It is found that the multimodel consensus is superior to the individual control runs and to the consensus forecasts constructed from ensembles of runs generated by varying model initial conditions. The source of the forecast improvement by model consensus is not the result of a simple cancellation of errors as a result of an overall positive bias in one model and an overall negative bias in another. Rather the main improvement stems from overlapping differences in the sign of the errors associated with forecasts of individual traveling disturbances. The results suggest that variations in model physics and numerics play a substantial role in generating the full spectrum of possible solutions that can arise in a given numerical forecast.

Corresponding author address: J. M. Fritsch, Department of Meteorology, 503 Walker Building, The Pennsylvania State University, University Park, PA 16802.

Email: fritsch@ems.psu.edu

Abstract

Consensus forecasts from the control runs of several operational numerical models are compared to 1) the control-run forecasts of the individual models that compose the consensus and to 2) other consensus forecasts generated by varying the initial conditions of the various individual models. It is found that the multimodel consensus is superior to the individual control runs and to the consensus forecasts constructed from ensembles of runs generated by varying model initial conditions. The source of the forecast improvement by model consensus is not the result of a simple cancellation of errors as a result of an overall positive bias in one model and an overall negative bias in another. Rather the main improvement stems from overlapping differences in the sign of the errors associated with forecasts of individual traveling disturbances. The results suggest that variations in model physics and numerics play a substantial role in generating the full spectrum of possible solutions that can arise in a given numerical forecast.

Corresponding author address: J. M. Fritsch, Department of Meteorology, 503 Walker Building, The Pennsylvania State University, University Park, PA 16802.

Email: fritsch@ems.psu.edu

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