Assimilating Surface Weather Observations from Complex Terrain into a High-Resolution Numerical Weather Prediction Model. Deng, Xingxiu; Stull, Roland B.
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 mountaintop 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. Copyright 2007 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/) or from the AMS at 617-227-2425 or email@example.com.
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