• Alapaty, K., , N. L. Seaman, , D. S. Niyogi, , and A. F. Hanna, 2001: Assimilating surface data to improve the accuracy of atmospheric boundary layer simulations. J. Appl. Meteor., 40 , 20682082.

    • Search Google Scholar
    • Export Citation
  • Barnes, S. L., 1964: A technique for maximizing details in numerical weather map analysis. J. Appl. Meteor., 3 , 396409.

  • Benoit, R., , M. Desgagne, , P. Pellerin, , S. Pellerin, , Y. Chartier, , and S. Desjardins, 1997: The Canadian MC2: A semi-Lagrangian, semi-implicit wideband atmospheric model suited for finescale process studies and simulation. Mon. Wea. Rev., 125 , 23822415.

    • Search Google Scholar
    • Export Citation
  • Bergeron, G., , R. Laprise, , D. Caya, , A. Robert, , M. Giguere, , R. Benoit, , and Y. Chartier, 1994: Formulation of Mesoscale Compressible Community (MC2) model. Internal Rep., Cooperative Centre for Research in Mesometeorology, 165 pp.

  • Bloom, S. C., , L. L. Takacs, , A. M. da Silva, , and D. Ledvina, 1996: Data assimilation using incremental analysis updates. Mon. Wea. Rev., 124 , 12561271.

    • Search Google Scholar
    • Export Citation
  • Bratseth, A. M., 1986: Statistical interpolation by means of successive corrections. Tellus, 38A , 439447.

  • Brewster, K. A., 1996: Application of a Bratseth analysis scheme including Doppler radar data. Preprints, 15th Conf. on Weather Forecasting and Analysis, Norfolk, VA, Amer. Meteor. Soc., 92–95.

  • Brewster, K. A., 2003: Phase-correcting data assimilation and application to storm-scale numerical weather prediction. Part II: Application to a severe storm outbreak. Mon. Wea. Rev., 131 , 493507.

    • Search Google Scholar
    • Export Citation
  • Deng, X., , and R. Stull, 2005: A mesoscale analysis method for surface potential temperature in mountainous and coastal terrain. Mon. Wea. Rev., 133 , 389408.

    • Search Google Scholar
    • Export Citation
  • Hacker, J., , and C. Snyder, 2005: Ensemble Kalman filter assimilation of fixed screen-height observations in a parameterized PBL. Mon. Wea. Rev., 133 , 32603275.

    • Search Google Scholar
    • Export Citation
  • Laprise, R., , D. Caya, , G. Bergeron, , and M. Giguère, 1997: The formulation of the André Robert MC2 (mesoscale compressible community) model. Numerical Methods in Atmospheric and Oceanic Modelling: The André J. Robert Memorial Volume, C. A. Lin, R. Laprise, and H. Ritchie, Eds., Atmosphere–Ocean Series, Canadian Meteorological and Oceanographic Society/NRC Research Press, 195–220.

  • Miller, P. A., , and S. G. Benjamin, 1992: A system for the hourly assimilation of surface observations in mountainous and flat terrain. Mon. Wea. Rev., 120 , 23422359.

    • Search Google Scholar
    • Export Citation
  • Ruggiero, F. H., , K. D. Sashegyi, , R. V. Madala, , and S. Raman, 1996: The use of surface observations in four-dimensional data assimilation using a mesoscale model. Mon. Wea. Rev., 124 , 10181033.

    • Search Google Scholar
    • Export Citation
  • Ruggiero, F. H., , G. D. Modica, , and A. E. Lipton, 2000: Assimilation of satellite imager data and surface observations to improve analysis of circulations forced by cloud shading contrasts. Mon. Wea. Rev., 128 , 434448.

    • Search Google Scholar
    • Export Citation
  • Stauffer, D. R., , N. L. Seaman, , and F. S. Binkowski, 1991: Use of four-dimensional data assimilation in a limited-area mesoscale model. Part II: Effects of data assimilation within the planetary boundary layer. Mon. Wea. Rev., 119 , 734754.

    • Search Google Scholar
    • Export Citation
  • Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Kluwer Academic, 666 pp.

  • Stull, R. B., 2000: Meteorology for Scientists and Engineers. 2d ed. Brooks/Cole, 502 pp.

  • Xue, M., , K. K. Droegemeier, , and V. Wong, 2000: The Advanced Regional Prediction System (ARPS)—A multi-scale nonhydrostatic atmospheric simulation and prediction model. Part I: Model dynamics and verification. Meteor. Atmos. Phys., 75 , 161193.

    • Search Google Scholar
    • Export Citation
  • Xue, M., , K. Brewster, , D. Weber, , K. W. Thomas, , F. Kong, , and E. Kemp, 2002: Real-time storm-scale forecast support for IHOP 2002 at CAPS. Preprints, 15th Conf. on Numerical Weather Prediction and 19th Conf. on Weather Analysis and Forecasting, San Antonio, TX, Amer. Meteor. Soc., CD-ROM, 4B.3.

  • Yee, S. Y. K., , and A. J. Jackson, 1988: Blending of surface and rawinsonde data in mesoscale objective analysis. AFGL Tech. Rep. 88-0144, Air Force Geophysics Laboratory, Hanscom AFB, MA, 31 pp. [NTIS ADA203984.].

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 14 14 2
PDF Downloads 11 11 3

Assimilating Surface Weather Observations from Complex Terrain into a High-Resolution Numerical Weather Prediction Model

View More View Less
  • 1 University of British Columbia, Vancouver, British Columbia, Canada
© Get Permissions
Restricted access

Abstract

An anisotropic surface analysis method based on the mother–daughter (MD) approach has been developed to spread valley station observations to grid points in circuitous steep valleys. In this paper, the MD approach is further refined to allow spreading the mountain-top observations to grid points near neighboring high ridges across valleys. Starting with a 3D first guess from a high-resolution mesoscale model forecast, surface weather observations are assimilated into the boundary layer, and pseudo-upper-air data (interpolated from the coarser-resolution analyses from major operational centers) are assimilated into the free atmosphere. Incremental analysis updating is then used to incorporate the final analysis increments (the difference between the final analysis and the first guess) into a high-resolution numerical weather prediction model. The MD approaches (including one with shoreline refinement) are compared with other objective analysis methods using case examples and daily mesoscale real-time forecast runs during November and December 2004. This study further confirms that the MD approaches outperform the other methods, and that the shoreline refinement achieves better analysis quality than the basic MD approach. The improvement of mountain-top refinement over the basic MD approach increases with the percentage of mountain-top stations, which is usually low. Higher skill in predicting near-surface potential temperature is found when surface information is spread upward throughout the boundary layer instead of at only the bottom model level. The results show improved near-surface forecasts of temperature and humidity that are directly assimilated into the model, but poorer forecasts of near-surface winds and precipitation, which are not assimilated into the model.

Corresponding author address: Xingxiu Deng, Numerical Weather Prediction Division, Canadian Meteorological Centre, Environment Canada, 2121 Trans-Canada Highway, Dorval, QC H9P 1J3, Canada. Email: xingxiu.deng@ec.gc.ca

Abstract

An anisotropic surface analysis method based on the mother–daughter (MD) approach has been developed to spread valley station observations to grid points in circuitous steep valleys. In this paper, the MD approach is further refined to allow spreading the mountain-top observations to grid points near neighboring high ridges across valleys. Starting with a 3D first guess from a high-resolution mesoscale model forecast, surface weather observations are assimilated into the boundary layer, and pseudo-upper-air data (interpolated from the coarser-resolution analyses from major operational centers) are assimilated into the free atmosphere. Incremental analysis updating is then used to incorporate the final analysis increments (the difference between the final analysis and the first guess) into a high-resolution numerical weather prediction model. The MD approaches (including one with shoreline refinement) are compared with other objective analysis methods using case examples and daily mesoscale real-time forecast runs during November and December 2004. This study further confirms that the MD approaches outperform the other methods, and that the shoreline refinement achieves better analysis quality than the basic MD approach. The improvement of mountain-top refinement over the basic MD approach increases with the percentage of mountain-top stations, which is usually low. Higher skill in predicting near-surface potential temperature is found when surface information is spread upward throughout the boundary layer instead of at only the bottom model level. The results show improved near-surface forecasts of temperature and humidity that are directly assimilated into the model, but poorer forecasts of near-surface winds and precipitation, which are not assimilated into the model.

Corresponding author address: Xingxiu Deng, Numerical Weather Prediction Division, Canadian Meteorological Centre, Environment Canada, 2121 Trans-Canada Highway, Dorval, QC H9P 1J3, Canada. Email: xingxiu.deng@ec.gc.ca

Save