• Atkinson, B. W., and M. Zhu, 2005: Radar-duct and boundary-layer characteristics over the area of the gulf. Quart. J. Roy. Meteor. Soc., 131, 19231953.

    • Search Google Scholar
    • Export Citation
  • Atkinson, B. W., and M. Zhu, 2006: Coastal effects on radar propagation in atmospheric ducting conditions. Meteor. Appl., 13, 5362.

  • Atkinson, B. W., J.-G. Li, and R. S. Plant, 2001: Numerical modeling of the propagation environment in the atmospheric boundary layer over the Persian Gulf. J. Appl. Meteor., 40, 586603.

    • Search Google Scholar
    • Export Citation
  • Bean, B., and E. Dutton, 1968: Radio Meteorology. Dover, 435 pp.

  • Brooks, I. M., and D. P. Rogers, 2000: Aircraft observations of the mean and turbulent structure of a shallow boundary layer over the Persian Gulf. Bound.-Layer Meteor., 95, 189210.

    • Search Google Scholar
    • Export Citation
  • Brooks, I. M., A. K. Goroch, and D. P. Rogers, 1999: Observations of strong surface radar ducts over the Persian Gulf. J. Appl. Meteor., 38, 12931310.

    • Search Google Scholar
    • Export Citation
  • Burk, S. D., and W. T. Thompson, 1995: Mesoscale modeling of refractive conditions in a complex coastal environment. Proc. Conf. on Propagation Assessment in Coastal Environment, Bremerhaven, Germany, AGARD/NATO, 40.1–40.7.

    • Search Google Scholar
    • Export Citation
  • Burk, S. D., and W. T. Thompson, 1997: Mesoscale modeling of summertime refractive conditions in the Southern California Bight. J. Appl. Meteor., 36, 2231.

    • Search Google Scholar
    • Export Citation
  • Cummings, J. A., 2005: Operational multivariate ocean data assimilation. Quart. J. Roy. Meteor. Soc., 131, 35833604.

  • Davies, T., M. J. P. Cullen, A. J. Malcolm, M. H. Mawson, A. Staniforth, A. A. White, and N. Wood, 2005: A new dynamical core for the Met Office’s global and regional modelling of the atmosphere. Quart. J. Roy. Meteor. Soc., 131, 17591782.

    • Search Google Scholar
    • Export Citation
  • Edwards, J. M., and A. Slingo, 1996: Studies with a flexible new radiation code. I: Choosing a configuration for a large-scale model. Quart. J. Roy. Meteor. Soc., 122, 689719.

    • Search Google Scholar
    • Export Citation
  • Essery, R., M. Best, and P. Cox, 2001: MOSES 2.2 technical documentation. Hadley Centre Tech. Rep. 30, 31 pp.

  • Golding, B. W., 1987: The U.K. Meteorological Office mesoscale model. Bound.-Layer Meteor., 41, 91107.

  • Golding, B. W., 1990: The Meteorological Office mesoscale model. Meteor. Mag., 119, 8196.

  • Gregory, D., and P. R. Rowntree, 1990: A mass flux convection scheme with representation of cloud ensemble characteristics and stability-dependent closure. Mon. Wea. Rev., 118, 14831506.

    • Search Google Scholar
    • Export Citation
  • Haack, T., and S. T. Burk, 2001: Summertime marine refractivity conditions along coastal California. J. Appl. Meteor., 40, 673687.

  • Haack, T., C. Wang, S. Garrett, A. Glazer, J. Mailhot, and R. Marshall, 2010: Mesoscale modeling of boundary layer refractivity and atmospheric ducting. J. Appl. Meteor. Climatol., 49, 24372457.

    • Search Google Scholar
    • Export Citation
  • Lock, A. P., A. R. Brown, M. R. Bush, G. M. Martin, and R. N. B. Smith, 2000: A new boundary layer mixing scheme. Part I: Scheme description and single-column model tests. Mon. Wea. Rev., 128, 31873199.

    • Search Google Scholar
    • Export Citation
  • Lystad, S., and T. Tjelta, 1995: High-resolution meteorological grid for clear air propagation modelling in northern coastal regions. Proc. Conf. on Propagation Assessment in Coastal Environment, Bremerhaven, Germany, AGARD/NATO, 41.1–41.12.

    • Search Google Scholar
    • Export Citation
  • Orlanski, I., 1975: A rational subdivision of scales for atmospheric processes. Bull. Amer. Meteor. Soc., 56, 527530.

  • Panofsky, H. A., and G. W. Brier, 1958: Some Applications of Statistics to Meteorology. The Pennsylvania State University, 224 pp.

  • Reynolds, R. W., N. A. Rayner, T. M. Smith, D. C. Stokes, and W. Wang, 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15, 16091625.

    • Search Google Scholar
    • Export Citation
  • Stapleton, J., V. Wiss, D. Shanklin, T. Nguyen, E. Burgess, W. Thornton, and T. Brown, 2001: Radar propagation modeling assessment using measured refractivity and directly sensed propagation ground truth—Wallops Island, VA 2000. Tech. Rep. NSWCDD/TR-01/132, 49 pp.

    • Search Google Scholar
    • Export Citation
  • Wilson, D. R., and S. P. Ballard, 1999: A microphysically based precipitation scheme for the U.K. Meteorological Office Unified Model. Quart. J. Roy. Meteor. Soc., 125, 16071636.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 5 5 5
PDF Downloads 3 3 3

Effects of Initial and Boundary Conditions of Mesoscale Models on Simulated Atmospheric Refractivity

View More View Less
  • 1 * Joint Centre for Mesoscale Meteorology, Met Office, Reading, United Kingdom
  • | 2 Defence Outcomes, Met Office, Exeter, United Kingdom
  • | 3 Naval Research Laboratory, Monterey, California
  • | 4 Civil Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, Surrey, United Kingdom
  • | 5 Naval Surface Warfare Center, Dahlgren, Virginia
Restricted access

Abstract

Radar ducting is caused by sharp vertical changes in temperature and, especially, water vapor at the top of the atmospheric boundary layer, both of which are sensitive to variations in the underlying surface conditions, local mesoscale weather, and synoptic weather patterns. High-resolution numerical weather prediction (NWP) models offer an alternative to observation to determine boundary layer (BL) structure and to assess the spatial variability of radar ducts. The benefit of using NWP models for simulating ducting conditions very much depends on the initial state of sea surface temperature (SST) and the model spinup time, both of which have a great impact on BL structure. This study investigates the effects of variation of NWP-model initial conditions and simulation length on the accuracy of simulating the atmosphere’s refractive index over the Wallops Island, Virginia, region, which has pronounced SST variability and complex BL structure. The Met Office Unified Model (MetUM) with horizontal resolution of 4 km (4-km model) was used to simulate the atmospheric environment when observations were made during the Wallops-2000 experiment. Sensitivity tests were conducted in terms of the variability of SST and model spinup time. The evaluation of the model results was focused on low-level moisture, temperature, and surface ducting characteristics including the frequency, strength, and the height of the ducting layer. When provided with more accurate SST and adequate simulation length, the MetUM 4-km model demonstrated an improved ability to predict the observed ducting.

Corresponding author address: Changgui Wang, Met Office, JCMM, Reading, RG6 6BB, United Kingdom. E-mail: chang.wang@metoffice.gov.uk

Abstract

Radar ducting is caused by sharp vertical changes in temperature and, especially, water vapor at the top of the atmospheric boundary layer, both of which are sensitive to variations in the underlying surface conditions, local mesoscale weather, and synoptic weather patterns. High-resolution numerical weather prediction (NWP) models offer an alternative to observation to determine boundary layer (BL) structure and to assess the spatial variability of radar ducts. The benefit of using NWP models for simulating ducting conditions very much depends on the initial state of sea surface temperature (SST) and the model spinup time, both of which have a great impact on BL structure. This study investigates the effects of variation of NWP-model initial conditions and simulation length on the accuracy of simulating the atmosphere’s refractive index over the Wallops Island, Virginia, region, which has pronounced SST variability and complex BL structure. The Met Office Unified Model (MetUM) with horizontal resolution of 4 km (4-km model) was used to simulate the atmospheric environment when observations were made during the Wallops-2000 experiment. Sensitivity tests were conducted in terms of the variability of SST and model spinup time. The evaluation of the model results was focused on low-level moisture, temperature, and surface ducting characteristics including the frequency, strength, and the height of the ducting layer. When provided with more accurate SST and adequate simulation length, the MetUM 4-km model demonstrated an improved ability to predict the observed ducting.

Corresponding author address: Changgui Wang, Met Office, JCMM, Reading, RG6 6BB, United Kingdom. E-mail: chang.wang@metoffice.gov.uk
Save