Editorial Type:
Article
Article Type:
Research Article

Combined Winds and Turbulence Prediction System for Automated Air-Traffic Management Applications

Jung-Hoon Kim NASA Ames Research Center, and Oak Ridge Associated Universities, Moffett Field, California

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William N. Chan NASA Ames Research Center, Moffett Field, California

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Banavar Sridhar NASA Ames Research Center, Moffett Field, California

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

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Print Publication:
01 Apr 2015
DOI:
https://doi.org/10.1175/JAMC-D-14-0216.1
Page(s):
766–784
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Abstract

A time-lagged ensemble of energy dissipation rate (EDR)-scale turbulence metrics is evaluated against in situ EDR observations from commercial aircraft over the contiguous United States and applied to air-traffic management (ATM) route planning. This method uses the Graphic Turbulence Guidance forecast methodology with three modifications. First, it uses the convection-permitting-scale (Δx = 3 km) Advanced Research version of the Weather Research and Forecasting Model (ARW) to capture cloud-resolving-scale weather phenomena. Second, turbulence metrics are computed for multiple ARW forecasts that are combined at the same forecast valid time, resulting in a time-lagged ensemble of multiple turbulence metrics. Third, probabilistic turbulence forecasts are provided on the basis of the ensemble results, which are applied to the ATM route planning. Results show that the ARW forecasts match well with observed weather patterns and the overall performance skill of the ensemble turbulence forecast when compared with the observed data is superior to any single turbulence metric. An example wind-optimal route (WOR) is computed using areas experiencing ≥10% probability of encountering severe-or-greater turbulence. Using these turbulence data, lateral turbulence avoidance routes starting from three different waypoints along the WOR from Los Angeles International Airport to John F. Kennedy International Airport are calculated. The examples illustrate the trade-off between flight time/fuel used and turbulence avoidance maneuvers.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Dr. Jung-Hoon Kim, NASA Postdoctoral Program Fellow, Aviation Systems Division, NASA Ames Research Center, Mail code: 210-10, Moffett Field, CA 94035-1000. E-mail: jung-hoon.kim@nasa.gov; jhkim99@me.com

Abstract

A time-lagged ensemble of energy dissipation rate (EDR)-scale turbulence metrics is evaluated against in situ EDR observations from commercial aircraft over the contiguous United States and applied to air-traffic management (ATM) route planning. This method uses the Graphic Turbulence Guidance forecast methodology with three modifications. First, it uses the convection-permitting-scale (Δx = 3 km) Advanced Research version of the Weather Research and Forecasting Model (ARW) to capture cloud-resolving-scale weather phenomena. Second, turbulence metrics are computed for multiple ARW forecasts that are combined at the same forecast valid time, resulting in a time-lagged ensemble of multiple turbulence metrics. Third, probabilistic turbulence forecasts are provided on the basis of the ensemble results, which are applied to the ATM route planning. Results show that the ARW forecasts match well with observed weather patterns and the overall performance skill of the ensemble turbulence forecast when compared with the observed data is superior to any single turbulence metric. An example wind-optimal route (WOR) is computed using areas experiencing ≥10% probability of encountering severe-or-greater turbulence. Using these turbulence data, lateral turbulence avoidance routes starting from three different waypoints along the WOR from Los Angeles International Airport to John F. Kennedy International Airport are calculated. The examples illustrate the trade-off between flight time/fuel used and turbulence avoidance maneuvers.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Dr. Jung-Hoon Kim, NASA Postdoctoral Program Fellow, Aviation Systems Division, NASA Ames Research Center, Mail code: 210-10, Moffett Field, CA 94035-1000. E-mail: jung-hoon.kim@nasa.gov; jhkim99@me.com
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Journal of Applied Meteorology and Climatology

  • Bluestein, H. B., 1992: Principles of Kinematics and Dynamics. Vol. I, Synoptic–Dynamic Meteorology in Midlatitudes, Oxford University Press, 431 pp.

  • Brown, R., 1973: New indices to locate clear-air turbulence. Meteor. Mag., 102, 347–360.

  • Bryson, A. E., and Y. C. Ho, 1975: Applied Optimal Control. Taylor and Francis, 481 pp.

  • Buldovskii, G. S., S. A. Bortnikov, and M. V. Rubinshtejn, 1976: Forecasting zones of intense turbulence in the upper troposphere. Meteor. Gidrol., 2, 9–18.

    • Search Google Scholar
    • Export Citation

  • Cornman, L. B., C. S. Morse, and G. Cunning, 1995: Real-time estimation of atmospheric turbulence severity from in-situ aircraft measurements. J. Aircr., 32, 171–177, doi:10.2514/3.46697.

    • Search Google Scholar
    • Export Citation

  • DeLaura, R., and J. Evans, 2006: An exploratory study of modeling en route pilot convective storm flight deviation behavior. Preprints, 12th Conf. on Aviation, Range, and Aerospace Meteorology, Atlanta, GA, Amer. Meteor. Soc., P12.6. [Available online at https://ams.confex.com/ams/pdfpapers/103755.pdf.]

  • Frehlich, R., and R. D. Sharman, 2004: Estimates of turbulence from numerical weather prediction model output with applications to turbulence diagnosis and data assimilation. Mon. Wea. Rev., 132, 2308–2324, doi:10.1175/1520-0493(2004)132<2308:EOTFNW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Gill, P. G., 2014: Objective verification of World Area Forecast Centre clear air turbulence forecasts. Meteor. Appl., 21, 3–11, doi:10.1002/met.1288.

    • Search Google Scholar
    • Export Citation

  • Gill, P. G., and A. J. Stirling, 2013: Introducing convection to World Area Forecast Centre turbulence forecasts. Meteor. Appl., 20, 107–114, doi:10.1002/met.1315.

    • Search Google Scholar
    • Export Citation

  • ICAO, 2010: Meteorological service for international air navigation. Annex 3, Convention on International Civil Aviation, 17th ed., ICAO, 206 pp.

  • 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.

  • Jardin, M. R., and A. E. Bryson, 2001: Neighboring optimal aircraft guidance in winds. J. Guid. Control Dyn., 24, 710–715, doi:10.2514/2.4798.

    • Search Google Scholar
    • Export Citation

  • Jardin, M. R., and A. E. Bryson, 2012: Methods for computing minimum-time paths in strong winds. J. Aircr., 35, 165–171.

  • Kim, J.-H., and H.-Y. Chun, 2010: A numerical study of clear-air turbulence (CAT) encounters over South Korea on 2 April 2007. J. Appl. Meteor. Climatol., 49, 2381–2403, doi:10.1175/2010JAMC2449.1.

    • Search Google Scholar
    • Export Citation

  • Kim, J.-H., and H.-Y. Chun, 2011: Statistics and possible sources of aviation turbulence over South Korea. J. Appl. Meteor. Climatol., 50, 311–324, doi:10.1175/2010JAMC2492.1.

    • Search Google Scholar
    • Export Citation

  • Kim, J.-H., and H.-Y. Chun, 2012: A numerical simulation of convectively induced turbulence above deep convection. J. Appl. Meteor. Climatol., 51, 1180–1200, doi:10.1175/JAMC-D-11-0140.1.

    • Search Google Scholar
    • Export Citation

  • Kim, J.-H., H.-Y. Chun, R. D. Sharman, and T. L. Keller, 2011: Evaluations of upper-level turbulence diagnostics performance using the Graphical Turbulence Guidance (GTG) system and pilot reports (PIREPs) over East Asia. J. Appl. Meteor. Climatol., 50, 1936–1951, doi:10.1175/JAMC-D-10-05017.1.

    • Search Google Scholar
    • Export Citation

  • Kim, J.-H., H.-Y. Chun, R. D. Sharman, and S. B. Trier, 2014: The role of vertical shear on aviation turbulence within cirrus bands of a simulated western Pacific Ocean. Mon. Wea. Rev., 142, 2794–2813, doi:10.1175/MWR-D-14-00008.1.

    • Search Google Scholar
    • Export Citation

  • Knox, J. A., D. W. McCann, and P. D. Williams, 2008: Application of the Lighthill–Ford theory of spontaneous imbalance to clear-air turbulence forecasting. J. Atmos. Sci., 65, 3292–3304, doi:10.1175/2008JAS2477.1.

    • Search Google Scholar
    • Export Citation

  • Krozel, J., V. Klimenko, and R. D. Sharman, 2011: Analysis of clear-air turbulence avoidance maneuvers. Air Traffic Control Quart., 4, 147–168.

    • Search Google Scholar
    • Export Citation

  • Lane, T. P., and R. D. Sharman, 2008: Some influences of background flow conditions on the generation of turbulence due to gravity wave breaking above deep convection. J. Appl. Meteor. Climatol., 47, 2777–2796, doi:10.1175/2008JAMC1787.1.

    • Search Google Scholar
    • Export Citation

  • Lane, T. P., and R. D. Sharman, 2014: Intensity of thunderstorm-generated turbulence revealed by large-eddy simulation. Geophys. Res. Lett., 41, 2221–2227, doi:10.1002/2014GL059299.

    • Search Google Scholar
    • Export Citation

  • Lane, T. P., R. D. Sharman, T. L. Clark, and H.-M. Hsu, 2003: An investigation of turbulence generation mechanisms above deep convection. J. Atmos. Sci., 60, 1297–1321, doi:10.1175/1520-0469(2003)60<1297:AIOTGM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Lane, T. P., J. D. Doyle, R. Plougonven, M. A. Shapiro, and R. D. Sharman, 2004: Observations and numerical simulations of inertia–gravity waves and shearing instabilities in the vicinity of a jet stream. J. Atmos. Sci., 61, 2692–2706, doi:10.1175/JAS3305.1.

    • Search Google Scholar
    • Export Citation

  • Lane, T. P., J. D. Doyle, R. D. Sharman, M. A. Shapiro, and C. D. Watson, 2009: Statistics and dynamics of aircraft encounters of turbulence over Greenland. Mon. Wea. Rev., 137, 2687–2702, doi:10.1175/2009MWR2878.1.

    • Search Google Scholar
    • Export Citation

  • Lane, T. P., R. D. Sharman, S. B. Trier, R. G. Fovell, and J. K. Williams, 2012: Recent advances in the understanding of near-cloud turbulence. Bull. Amer. Meteor. Soc., 93, 499–515, doi:10.1175/BAMS-D-11-00062.1.

    • Search Google Scholar
    • Export Citation

  • Lester, P. F., 1994: Turbulence: A New Perspective for Pilots. Jeppesen Sanderson, 212 pp.

  • Lindborg, E., 1999: Can the atmospheric kinetic energy spectrum be explained by two-dimensional turbulence? J. Fluid Mech., 388, 259–288, doi:10.1017/S0022112099004851.

    • Search Google Scholar
    • Export Citation

  • McNally, D., K. Sheth, C. Gong, J. Love, C. H. Lee, S. Sahlman, and J. Cheng, 2012: Dynamic weather routes: A weather avoidance system for near-term trajectory-based operations. 28th Int. Congress of the Aeronautical Sciences (ICAS), Brisbane, Australia, ICAS 2012, 18 pp. [Available online at http://www.icas.org/ICAS_ARCHIVE/ICAS2012/PAPERS/366.PDF.]

  • Mellor, G. L., and T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys., 20, 851–875, doi:10.1029/RG020i004p00851.

    • 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 atmosphere: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16 663–16 682, doi:10.1029/97JD00237.

    • Search Google Scholar
    • Export Citation

  • Ng, H. K., S. Grabbe, and A. Mukherjee, 2009: Design and evaluation of a dynamic programming flight routing algorithm using the Convective Weather Avoidance Model. AIAA Guidance, Navigation, and Control Conf., Chicago, IL, American Institute of Aeronautics and Astronautics, AIAA-2009-5862. [Available online at http://www.aviationsystemsdivision.arc.nasa.gov/publications/2009/AF2009178.pdf.]

  • Ng, H. K., B. Sridhar, S. Grabbe, and N. Chen, 2011: Cross-polar aircraft trajectory optimization and the potential climate impact. 30th Digital Avionics Systems Conf. (DASC), Seattle, WA, Institute of Electrical and Electronics Engineers, 15 pp. [Available online at http://www.aviationsystemsdivision.arc.nasa.gov/publications/2011/DASC2011_Ng.pdf.]

  • Ng, H. K., B. Sridhar, and S. Grabbe, 2012: A practical approach for optimizing aircraft trajectories in winds. 31st Digital Avionics Systems Conf., Williamsburg, VA, Institute of Electrical and Electronics Engineers, 14 pp. [Available online at http://www.aviationsystemsdivision.arc.nasa.gov/publications/2012/DASC2012_Ng.pdf.]

  • Palopo, K., R. D. Windhorst, S. Suharwardy, and H.-T. Lee, 2010: Wind optimal routing in the National Airspace System. J. Aircr., 47, 1584–1592, doi:10.2514/1.C000208.

    • Search Google Scholar
    • Export Citation

  • Reap, R. M., 1996: Probability forecasts of clear-air turbulence for the contiguous U.S. National Weather Service Office of Meteorology Technology Procedures Bull. 430, 15 pp.

  • Roach, W. T., 1970: On the influence of synoptic development on the production of high level turbulence. Quart. J. Roy. Meteor. Soc., 96, 413–429, doi:10.1002/qj.49709640906.

    • Search Google Scholar
    • Export Citation

  • Sharman, R. D., C. Tebaldi, G. Wiener, and J. Wolff, 2006: An integrated approach to mid- and upper-level turbulence forecasting. Wea. Forecasting, 21, 268–287, doi:10.1175/WAF924.1.

    • Search Google Scholar
    • Export Citation

  • Sharman, R. D., J. D. Doyle, and M. A. Shapiro, 2011: An investigation of a commercial aircraft encounter with severe clear-air turbulence over western Greenland. J. Appl. Meteor. Climatol., 51, 311–324.

    • Search Google Scholar
    • Export Citation

  • Sharman, R. D., S. B. Trier, T. P. Lane, and J. D. Doyle, 2012: Sources and dynamics of turbulence in the upper troposphere and lower stratosphere: A review. Geophys. Res. Lett., 39, L12803, doi:10.1029/2012GL051996.

    • Search Google Scholar
    • Export Citation

  • Sharman, R. D., L. B. Cornman, G. Meymaris, J. Pearson, and T. Farrar, 2014: Description and derived climatologies of automated in situ eddy-dissipation-rate reports of atmospheric turbulence. J. Appl. Meteor. Climatol., 53, 1416–1432, doi:10.1175/JAMC-D-13-0329.1.

    • Search Google Scholar
    • Export Citation

  • Skamarock, W. C., and J. B. Klemp, 2008: A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. J. Comput. Phys., 227, 3465–3485, doi:10.1016/j.jcp.2007.01.037.

    • Search Google Scholar
    • Export Citation

  • Smirnova, T. G., J. M. Brown, S. G. Benjamin, and D. Kim, 2000: Parameterization of cold-season processes in the MAPS land-surface scheme. J. Geophys. Res., 105, 4077–4086, doi:10.1029/1999JD901047.

    • Search Google Scholar
    • Export Citation

  • Sridhar, B., H. K. Ng, and N. Y. Chen, 2011: Aircraft trajectory optimization and contrails avoidance in the presence of winds. J. Guidance, Control, Dyn.,34, 1577–1584, doi:10.2514/1.53378.

  • Steiner, M., R. Bateman, D. Megenhardt, Y. Liu, M. Pocernich, and J. Krozel, 2010: Translation of ensemble weather forecasts into probabilistic air traffic capacity impact. Air Traffic Control Quart., 18, 229–254.

    • Search Google Scholar
    • Export Citation

  • Thompson, G., R. M. Rasmussen, and K. Manning, 2004: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis. Mon. Wea. Rev., 132, 519–542, doi:10.1175/1520-0493(2004)132<0519:EFOWPU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Trier, S. B., and R. D. Sharman, 2009: Convection-permitting simulations of the environment supporting widespread turbulence within the upper-level outflow of a mesoscale convective system. Mon. Wea. Rev., 137, 1972–1990, doi:10.1175/2008MWR2770.1.

    • Search Google Scholar
    • Export Citation

  • Trier, S. B., R. D. Sharman, R. G. Fovell, and R. G. Frehlich, 2010: Numerical simulation of radial cloud bands within the upper-level outflow of an observed mesoscale convective system. J. Atmos. Sci., 67, 2990–2999, doi:10.1175/2010JAS3531.1.

    • Search Google Scholar
    • Export Citation

  • Williams, P. D., and M. M. Joshi, 2013: Intensification of winter transatlantic aviation turbulence in response to climate change. Nat. Climate Change, 3, 644–648, doi:10.1038/nclimate1866.

    • Search Google Scholar
    • Export Citation
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