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Rujin Shen, Elmar R. Reiter, and James F. Bresch

Abstract

The influence of sensible heating from the earth's surface on the development of summertime vortices over the Tibetan Plateau was investigated using a numerical model. It was found that sensible heating could cause local intensification of vortices over high elevations and sometimes act in combination with topography to block intrusions of cold air. Sensible heating can play an important role, not indicated by its magnitude, when it is combined with topography and the proper synoptic situation. Sensible heating had a greater impact over higher elevations, areas with strong cold advection, and areas under the upper-tropospheric jet stream. Sensible heating tends to destabilize an air column, permitting downward transfer of westerly momentum in the vicinity of the jet stream and causing an increase in cyclonic vorticity in the lower troposphere north of the upper-level jet. During the premonsoon period, when the upper-level jet was located over the southern plateau, sensible heating acted to intensify plateau vortices. After the transition into the summer monsoon period, the jet was north of the plateau and sensible heating had only localized and gradual effects on plateau vortices.

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Rujin Shen, Elmar R. Reiter, and James F. Bresch

Abstract

The initialization of numerical prediction models usually requires the transformation of variables observed in a p-coordinate system into some other coordinate frame of reference (e.g., α-coordinates or Θ-coordinates). Such transformations require the application of interpolation or curve-fitting techniques. The present study demonstrates that the choice of an appropriate interpolation scheme can become a critical issue for the skill of a low-resolution prediction model. First we show that the interpolation scheme, when applied to more than one meteorological variable, should satisfy the balance requirements that exist between these variables. Not all of the currently used schemes meet this condition. Next we provide evidence indicating that interpolation schemes used to convert p-into α-coordinates, and then back into p-coordinates, do not necessarily replicate the original, observed field distributions of these meteorological variables. Such double transformations usually are required, because the numerical output in model coordinates has to be translated back to p-coordinates for verification of model results. Because of the limitations of certain interpolation procedures, even a correct model prediction may exhibit low predictive skill because of errors introduced in this final coordinate transformation process.

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