Initial-Condition Sensitivities and the Predictability of Downslope Winds

Patrick A. Reinecke Department of Atmospheric Sciences, University of Washington, Seattle, Washington

Search for other papers by Patrick A. Reinecke in
Current site
Google Scholar
PubMed
Close
and
Dale R. Durran Department of Atmospheric Sciences, University of Washington, Seattle, Washington

Search for other papers by Dale R. Durran in
Current site
Google Scholar
PubMed
Close
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

The sensitivity of downslope wind forecasts to small changes in initial conditions is explored by using 70-member ensemble simulations of two prototypical windstorms observed during the Terrain-Induced Rotor Experiment (T-REX). The 10 weakest and 10 strongest ensemble members are composited and compared for each event.

In the first case, the 6-h ensemble-mean forecast shows a large-amplitude breaking mountain wave and severe downslope winds. Nevertheless, the forecasts are very sensitive to the initial conditions because the difference in the downslope wind speeds predicted by the strong- and weak-member composites grows to larger than 28 m s−1 over the 6-h forecast. The structure of the synoptic-scale flow one hour prior to the windstorm and during the windstorm is very similar in both the weak- and strong-member composites.

Wave breaking is not a significant factor in the second case, in which the strong winds are generated by a layer of high static stability flowing beneath a layer of weaker mid- and upper-tropospheric stability. In this case, the sensitivity to initial conditions is weaker but still significant. The difference in downslope wind speeds between the weak- and strong-member composites grows to 22 m s−1 over 12 h. During and one hour before the windstorm, the synoptic-scale flow exhibits appreciable differences between the strong- and weak-member composites. Although this case appears to be more predictable than the wave-breaking event, neither case suggests that much confidence should be placed in the intensity of downslope winds forecast 12 or more hours in advance.

* Current affiliation: Naval Research Laboratory, Monterey, California.

Corresponding author address: Patrick A. Reinecke, Naval Research Laboratory, 7 Grace Hopper Avenue, Monterey, CA 93943-5502. Email: alex.reinecke@nrlmry.navy.mil

This article included in the Terrain-Induced Rotor Experiment (T-Rex) special collection.

Abstract

The sensitivity of downslope wind forecasts to small changes in initial conditions is explored by using 70-member ensemble simulations of two prototypical windstorms observed during the Terrain-Induced Rotor Experiment (T-REX). The 10 weakest and 10 strongest ensemble members are composited and compared for each event.

In the first case, the 6-h ensemble-mean forecast shows a large-amplitude breaking mountain wave and severe downslope winds. Nevertheless, the forecasts are very sensitive to the initial conditions because the difference in the downslope wind speeds predicted by the strong- and weak-member composites grows to larger than 28 m s−1 over the 6-h forecast. The structure of the synoptic-scale flow one hour prior to the windstorm and during the windstorm is very similar in both the weak- and strong-member composites.

Wave breaking is not a significant factor in the second case, in which the strong winds are generated by a layer of high static stability flowing beneath a layer of weaker mid- and upper-tropospheric stability. In this case, the sensitivity to initial conditions is weaker but still significant. The difference in downslope wind speeds between the weak- and strong-member composites grows to 22 m s−1 over 12 h. During and one hour before the windstorm, the synoptic-scale flow exhibits appreciable differences between the strong- and weak-member composites. Although this case appears to be more predictable than the wave-breaking event, neither case suggests that much confidence should be placed in the intensity of downslope winds forecast 12 or more hours in advance.

* Current affiliation: Naval Research Laboratory, Monterey, California.

Corresponding author address: Patrick A. Reinecke, Naval Research Laboratory, 7 Grace Hopper Avenue, Monterey, CA 93943-5502. Email: alex.reinecke@nrlmry.navy.mil

This article included in the Terrain-Induced Rotor Experiment (T-Rex) special collection.

Save
  • Anthes, R. A., 1984: Predictability of mesoscale meteorological phenomena. Predictability of Fluid Motions, G. Holloway and B. J. West, Eds., American Institute of Physics, 247–270.

    • Search Google Scholar
    • Export Citation
  • Anthes, R. A., Y. Kuo, D. P. Baumhefner, R. M. Errico, and T. W. Bettge, 1985: Prediction of mesoscale atmospheric motions. Advances in Geophyics, Vol. 28B, Academic Press, 159–202.

    • Search Google Scholar
    • Export Citation
  • Barker, D. M., W. Huang, Y-R. Guo, A. J. Bourgeois, and Q. N. Xiao, 2004: A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Wea. Rev., 132 , 897914.

    • Search Google Scholar
    • Export Citation
  • Clark, T. L., and W. R. Peltier, 1977: On the evolution and stability of finite amplitude mountain waves. J. Atmos. Sci., 34 , 17151730.

    • Search Google Scholar
    • Export Citation
  • Clark, T. L., W. D. Hall, R. M. Kerr, L. Radke, F. M. Ralph, P. J. Neiman, and D. Levinson, 2000: Origins of aircraft-damaging clear-air turbulence during the 9 December 1992 Colorado downslope windstorm: Numerical simulations and comparison with observations. J. Atmos. Sci., 57 , 11051131.

    • Search Google Scholar
    • Export Citation
  • Colle, B. A., and C. F. Mass, 1998: Windstorms along the western side of the Washington Cascade Mountains. Part I: A high-resolution observational and modeling study of the 12 February 1995 event. Mon. Wea. Rev., 126 , 2852.

    • Search Google Scholar
    • Export Citation
  • Dirren, S., R. D. Torn, and G. J. Hakim, 2007: A data assimilation case study using a limited-area ensemble Kalman filter. Mon. Wea. Rev., 135 , 14551473.

    • Search Google Scholar
    • Export Citation
  • Doyle, J. D., and M. A. Shapiro, 2000: A multi-scale simulation of an extreme downslope windstorm over complex topography. Meteor. Atmos. Phys., 74 , 83101.

    • Search Google Scholar
    • Export Citation
  • Doyle, J. D., and R. B. Smith, 2003: Mountain waves over the Hohe Tauren: Influence of upstream diabatic effects. Quart. J. Roy. Meteor. Soc., 129 , 799823.

    • Search Google Scholar
    • Export Citation
  • Doyle, J. D., and C. A. Reynolds, 2008: Implications of regime transition for mountain-wave-breaking predictability. Mon. Wea. Rev., 136 , 52115223.

    • Search Google Scholar
    • Export Citation
  • Doyle, J. D., and Coauthors, 2000: An intercomparison of model-predicted wave breaking for the 11 January 1972 Boulder windstorm. Mon. Wea. Rev., 128 , 900914.

    • Search Google Scholar
    • Export Citation
  • Durran, D. R., 1986: Another look at downslope windstorms. Part I: The development of analogs to supercritical flow in an infinitely deep, continuously stratified fluid. J. Atmos. Sci., 43 , 25272543.

    • Search Google Scholar
    • Export Citation
  • Durran, D. R., 1992: Two-layer solutions to Long’s equation for vertically propagating mountain waves: How good is linear theory? Quart. J. Roy. Meteor. Soc., 118 , 415433.

    • Search Google Scholar
    • Export Citation
  • Evensen, G., 2003: The ensemble Kalman filter: Theoretical formulation and practical implementation. Ocean Dyn., 53 , 343367.

  • Gaspari, G., and S. E. Cohn, 1999: Construction of correlation functions in two and three dimensions. Quart. J. Roy. Meteor. Soc., 125 , 723757.

    • Search Google Scholar
    • Export Citation
  • Grubišić, V., and Coauthors, 2008: The Terrain-Induced Rotor Experiment: A field campaign overview including observational highlights. Bull. Amer. Meteor. Soc., 89 , 15131533.

    • Search Google Scholar
    • Export Citation
  • Hamill, T. M., 2001: Interpretation of rank histograms for verifying ensemble forecasts. Mon. Wea. Rev., 129 , 550560.

  • Hamill, T. M., 2006: Ensemble-based atmospheric data assimilation: A tutorial. Predictability of Weather and Climate, T. Palmer and R. Hagedorn, Eds., Cambridge University Press, 124–156.

    • Search Google Scholar
    • Export Citation
  • Hamill, T. M., J. S. Whitaker, and C. Snyder, 2001: Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter. Mon. Wea. Rev., 129 , 27762790.

    • Search Google Scholar
    • Export Citation
  • Hodur, R. M., 1997: The Naval Research Laboratory’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS). Mon. Wea. Rev., 125 , 14141430.

    • Search Google Scholar
    • Export Citation
  • Houtekamer, P. L., and H. L. Mitchell, 2001: A sequential ensemble Kalman filter for atmospheric data assimilation. Mon. Wea. Rev., 129 , 123127.

    • Search Google Scholar
    • Export Citation
  • Jiang, Q., and J. D. Doyle, 2009: The impact of moisture on mountain waves during T-REX. Mon. Wea. Rev., in press.

  • Klemp, J. B., and D. K. Lilly, 1975: The dynamics of wave-induced downslope winds. J. Atmos. Sci., 32 , 320339.

  • Klemp, J. B., and R. B. Wilhelmson, 1978: The simulation of three-dimensional convective storm dynamics. J. Atmos. Sci., 35 , 10701096.

    • Search Google Scholar
    • Export Citation
  • Lilly, D. K., 1978: A severe downslope windstorm and aircraft turbulence event induced by a mountain wave. J. Atmos. Sci., 35 , 5979.

  • Lilly, D. K., and E. J. Zipser, 1972: The Front Range windstorm of January 11, 1972. Weatherwise, 25 , 5663.

  • Lorenz, E. N., 1969: The predictability of a flow which possesses many scales of motion. Tellus, 21 , 289307.

  • Mitchell, H. L., and P. L. Houtekamer, 2002: Ensemble size, balance, and model-error representation in an ensemble Kalman filter. Mon. Wea. Rev., 130 , 27912808.

    • Search Google Scholar
    • Export Citation
  • Nance, L. B., and B. R. Coleman, 2000: Evaluating the use of a nonlinear two-dimensional model in downslope windstorm forecasts. Wea. Forecasting, 15 , 717729.

    • Search Google Scholar
    • Export Citation
  • Nastrom, G. D., and D. C. Fritts, 1992: Sources of mesoscale variability of gravity waves. Part I: Topographic excitation. J. Atmos. Sci., 49 , 101110.

    • Search Google Scholar
    • Export Citation
  • Peltier, W. R., and T. L. Clark, 1979: The evolution and stability of finite-amplitude mountain waves II: Surface wave drag and severe downslope windstorms. J. Atmos. Sci., 36 , 14981529.

    • Search Google Scholar
    • Export Citation
  • Reinecke, P. A., and D. R. Durran, 2009: The over-amplification of gravity waves in numerical solutions to flow over topography. Mon. Wea. Rev., 137 , 15331549.

    • Search Google Scholar
    • Export Citation
  • Torn, R. D., and G. J. Hakim, 2008: Performance characteristics of a pseudo-operational ensemble Kalman filter. Mon. Wea. Rev., 136 , 39473963.

    • Search Google Scholar
    • Export Citation
  • Torn, R. D., and G. J. Hakim, 2009: Ensemble data assimilation applied to RAINEX observations of Hurricane Katrina. Mon. Wea. Rev., 137 , 27712783.

    • Search Google Scholar
    • Export Citation
  • Torn, R. D., G. J. Hakim, and C. Snyder, 2006: Boundary conditions for a limited-area ensemble Kalman filter. Mon. Wea. Rev., 134 , 24902502.

    • Search Google Scholar
    • Export Citation
  • Whitaker, J. S., and T. M. Hamill, 2002: Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130 , 19131924.

  • Whitaker, J. S., G. P. Compo, X. Wei, and T. M. Hamill, 2004: Reanalysis without radiosondes using ensemble data assimilation. Mon. Wea. Rev., 132 , 11901200.

    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences. Academic Press, 627 pp.

  • Zhang, F., C. Snyder, and J. Sun, 2004: Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter. Mon. Wea. Rev., 132 , 12381253.

    • Search Google Scholar
    • Export Citation
  • Zhang, F., Y. Weng, J. A. Sippel, Z. Meng, and C. H. Bishop, 2009: Cloud-resolving hurricane initialization and prediction through assimilation of Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 137 , 21052125.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 3315 2501 1360
PDF Downloads 450 87 7