Editorial Type:
Article
Article Type:
Research Article

The Operational Mesogamma-Scale Analysis and Forecast System of the U.S. Army Test and Evaluation Command. Part III: Forecasting with Secondary-Applications Models

Robert D. Sharman National Center for Atmospheric Research,** Boulder, Colorado

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Yubao Liu National Center for Atmospheric Research,** Boulder, Colorado

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Rong-Shyang Sheu National Center for Atmospheric Research,** Boulder, Colorado

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Thomas T. Warner National Center for Atmospheric Research,** Boulder, Colorado
Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado

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Daran L. Rife National Center for Atmospheric Research,** Boulder, Colorado

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James F. Bowers U.S. Army, Dugway Proving Ground, Dugway, Utah

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Charles A. Clough U.S. Army, Aberdeen Proving Ground, Aberdeen, Maryland

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Edward E. Ellison U.S. Army, White Sands Missile Range, White Sands, New Mexico

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Print Publication:
01 Apr 2008
DOI:
https://doi.org/10.1175/2007JAMC1655.1
Page(s):
1105–1122
Restricted access

Abstract

Output from the Army Test and Evaluation Command’s Four-Dimensional Weather System’s mesoscale model is used to drive secondary-applications models to produce forecasts of quantities of importance for daily decision making at U.S. Army test ranges. Examples of three specific applications—a sound propagation model, a missile trajectory model, and a transport and diffusion model—are given, along with accuracy assessments using cases in which observational data are available for verification. Ensembles of application model forecasts are used to derive probabilities of exceedance of quantities that can be used to help range test directors to make test go–no-go decisions. The ensembles can be based on multiple meteorological forecast runs or on spatial ensembles derived from different soundings extracted from a single meteorological forecast. In most cases, the accuracies of the secondary-application forecasts are sufficient to meet operational needs at the test ranges.

Corresponding author address: Robert Sharman, NCAR/RAL, P.O. Box 3000, Boulder, CO 80307-3000. Email: sharman@ucar.edu

Abstract

Output from the Army Test and Evaluation Command’s Four-Dimensional Weather System’s mesoscale model is used to drive secondary-applications models to produce forecasts of quantities of importance for daily decision making at U.S. Army test ranges. Examples of three specific applications—a sound propagation model, a missile trajectory model, and a transport and diffusion model—are given, along with accuracy assessments using cases in which observational data are available for verification. Ensembles of application model forecasts are used to derive probabilities of exceedance of quantities that can be used to help range test directors to make test go–no-go decisions. The ensembles can be based on multiple meteorological forecast runs or on spatial ensembles derived from different soundings extracted from a single meteorological forecast. In most cases, the accuracies of the secondary-application forecasts are sufficient to meet operational needs at the test ranges.

Corresponding author address: Robert Sharman, NCAR/RAL, P.O. Box 3000, Boulder, CO 80307-3000. Email: sharman@ucar.edu

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Journal of Applied Meteorology and Climatology

  • American National Standards Institute, 1983: Airblast characteristics for single point explosions in air with a guide to evaluation of atmospheric propagation and effects. ANSI S2.20-1983, Acoustic Society of America, 32 pp.

  • Appleman, H. S., 1953: The formation of exhaust condensation trails by jet aircraft. Bull. Amer. Meteor. Soc., 34 , 14–20.

  • Barnum, B. H., and Coauthors, 2004: Forecasting dust storms using the CARMA-dust model and MM5 weather data. Environ. Model. Softw., 19 , 129–140.

    • Search Google Scholar
    • Export Citation

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

  • Bernstein, B. C., F. McDonough, M. K. Politovich, B. G. Brown, T. P. Ratvasky, D. R. Miller, C. A. Wolff, and G. Cunning, 2005: Current icing potential: Algorithm description and comparison with aircraft observations. J. Appl. Meteor., 44 , 969–986.

    • Search Google Scholar
    • Export Citation

  • Burk, S. D., T. Haack, L. T. Rogers, and L. J. Warner, 2003: Island wake dynamics and wake influence on the evaporation duct and radar propagation. J. Appl. Meteor., 42 , 349–367.

    • Search Google Scholar
    • Export Citation

  • Chang, J. C., P. Franzese, K. Chayantrakom, and S. R. Hanna, 2003: Evaluations of CALPUFF, HPAC, and VLSTRACK with two mesoscale field datasets. J. Appl. Meteor., 42 , 453–466.

    • Search Google Scholar
    • Export Citation

  • Clough, C., J. K. Leurs, and E. J. Hall, 2000: Development of an acoustic ray-trace model, high-resolution boundary-layer measurements, and meso-Γ-scale forecasts driven by off-range, blast-noise management requirements. Preprints, Ninth Conf. on Aviation, Range, and Aerospace Meteorology, Orlando, FL, Amer. Meteor. Soc., 415–420.

  • Davis, C., B. Brown, and R. Bullock, 2006: Object-based verification of precipitation forecasts. Part I: Methodology and application to mesoscale rain areas. Mon. Wea. Rev., 134 , 1772–1784.

    • Search Google Scholar
    • Export Citation

  • Etkin, B., 1972: Dynamics of Atmospheric Flight. John Wiley and Sons, 579 pp.

  • Frehlich, R. G., 2006: Adaptive data assimilation to include the spatial variations in observation error. Quart. J. Roy. Meteor. Soc., 132 , 1225–1257.

    • Search Google Scholar
    • Export Citation

  • Frehlich, R. G., and R. Sharman, 2003: Improving the small scale turbulence structure for fluid dynamics computations. Proc. 41st AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, AIAA Paper 2003-0195.

  • Grell, G. A., J. Dudhia, and D. R. Stauffer, 1995: A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR/TN-398, NCAR, 122 pp.

  • Heimann, D., and G. Gross, 1999: Coupled simulation of meteorological parameters and sound levels in a narrow valley. Appl. Acoust., 56 , 73–100.

    • Search Google Scholar
    • Export Citation

  • Hole, L. R., and H. M. Mohr, 1999: Modeling of sound propagation in the atmospheric boundary layer: Application of the MIUU mesoscale model. J. Geophys. Res., 104 , 11891–11901.

    • Search Google Scholar
    • Export Citation

  • Kalnay, E., 2003: Atmospheric Modeling, Data Assimilation and Predictability. Cambridge University Press, 342 pp.

  • Kerry, G., D. J. Saunders, and A. G. Sills, 1987: The use of meteorological profiles to predict the peak sound-pressure level at distance from small explosions. J. Acoust. Soc. Amer., 81 , 888–896.

    • Search Google Scholar
    • Export Citation

  • Krol, H. R., 1973: Intensity calculations along a single ray. J. Acoust. Soc. Amer., 53 , 864–868.

  • Lighthill, J., 1978: Waves in Fluids. Cambridge University Press, 504 pp.

  • Liu, Y., M. Xu, J. Hacker, T. Warner, and S. Swerdlin, 2007: A WRF and MM5-based 4-D Mesoscale Ensemble Data Analysis and Prediction System (E-RTFDDA) developed for ATEC operational applications. Preprints, 18th Conf. on Numerical Weather Prediction, Park City, UT, Amer. Meteor. Soc., 7B.7.

  • Liu, Y., and Coauthors, 2008a: The operational mesogamma-scale analysis and forecast system of the U.S. Army Test and Evaluation Command. Part I: Overview of the modeling system, the forecast products, and how the products are used. J. Appl. Meteor. Climatol., 47 , 1077–1092.

    • Search Google Scholar
    • Export Citation

  • Liu, Y., and Coauthors, 2008b: The operational mesogamma-scale analysis and forecast system of the U.S. Army Test and Evaluation Command. Part II: Interrange comparison of the accuracy of model analyses and forecasts. J. Appl. Meteor. Climatol., 47 , 1093–1104.

    • Search Google Scholar
    • Export Citation

  • Mass, C. F., D. Ovens, K. Westrick, and B. A. Colle, 2002: Does increasing horizontal resolution produce more skillful forecasts? Bull. Amer. Meteor. Soc., 83 , 407–430.

    • Search Google Scholar
    • Export Citation

  • McKeen, S., and Coauthors, 2007: Evaluation of several PM2.5 forecast models using data collected during the ICARTT/NEAQS 2004 field study. J. Geophys. Res., 112 .D10S20, doi:10.1029/2006JD007608.

    • Search Google Scholar
    • Export Citation

  • Rife, D. L., C. A. Davis, and Y. Liu, 2004: Predictability of low-level winds by mesoscale meteorological models. Mon. Wea. Rev., 132 , 2553–2569.

    • Search Google Scholar
    • Export Citation

  • Schomer, P. D., 2001: A statistical description of blast sound propagation. Noise Control Eng. J., 49 , 79–87.

  • Schomer, P. D., and G. A. Luz, 1994: A revised statistical analysis of blast sound propagation. Noise Control Eng. J., 42 , 95–100.

  • Schomer, P. D., L. R. Wagner, L. J. Benson, E. Buchta, K-W. Hirsch, and D. Krahé, 1994: Human and community response to military sounds: Results from field-laboratory tests of small-arms, tracked vehicle, and blast sounds. Noise Control Eng. J., 42 , 71–84.

    • Search Google Scholar
    • Export Citation

  • Schumann, U., 1996: On conditions for contrail formation from aircraft exhausts. Meteor. Z., 5 , 4–23.

  • Sharman, R., C. Tebaldi, G. Wiener, and J. Wolff, 2006: An integrated approach to mid- and upper-level turbulence forecasting. Wea. Forecasting, 21 , 268–287.

    • Search Google Scholar
    • Export Citation

  • Stauffer, D. R., and N. L. Seaman, 1994: Multiscale four-dimensional data assimilation. J. Appl. Meteor., 33 , 416–434.

  • Stoelinga, M. T., and T. T. Warner, 1999: Nonhydrostatic, mesobeta-scale model simulations of cloud ceiling and visibility for an East Coast winter precipitation event. J. Appl. Meteor., 38 , 385–404.

    • Search Google Scholar
    • Export Citation

  • Sykes, R. I., and R. S. Gabruk, 1997: A second-order closure model for the effect of averaging time on turbulent plume dispersion. J. Appl. Meteor., 36 , 1038–1045.

    • Search Google Scholar
    • Export Citation

  • Thompson, R. J., 1972: Ray theory for an inhomogeneous moving medium. J. Acoust. Soc. Amer., 51 , 1675–1682.

  • Thompson, R. J., 1974a: Ray-acoustic intensity in a moving medium I. J. Acoust. Soc. Amer., 55 , 729–732.

  • Thompson, R. J., 1974b: Ray-acoustic intensity in a moving medium II. J. Acoust. Soc. Amer., 55 , 733–737.

  • Turton, J. D., D. A. Bennetts, and D. J. W. Nazer, 1988a: The Larkhill noise assessment model. Part I: Theory and formulation. Meteor. Mag., 117 , 145–154.

    • Search Google Scholar
    • Export Citation

  • Turton, J. D., D. A. Bennetts, and D. J. W. Nazer, 1988b: The Larkhill noise assessment model. Part II: Assessment and use. Meteor. Mag., 117 , 169–179.

    • Search Google Scholar
    • Export Citation

  • Warner, T. T., R-S. Sheu, J. F. Bowers, R. I. Sykes, G. C. Dodd, and D. S. Henn, 2002: Ensemble simulations with coupled atmospheric dynamic and dispersions models: Illustrating uncertainties in dosage simulations. J. Appl. Meteor., 41 , 488–504.

    • Search Google Scholar
    • Export Citation
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