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Surface Potential Temperature as an Analysis and Forecasting Tool

  • Eric G. Hoffman
Chapter
Part of the Meteorological Monographs book series (METEOR, volume 33, No. 55)

Abstract

In the last decade, Fred Sanders was often critical of current surface analysis techniques. This led to his promoting the use of surface potential temperatures to distinguish between fronts, baroclinic troughs, and nonfrontal baroclinic zones, and to the development of a climatology of surface baroclinic zones. In this paper, criticisms of current surface analysis techniques and the usefulness of surface potential temperature analyses are discussed. Case examples are used to compare potential temperature analyses and current National Centers for Environmental Prediction analyses.

The 1-yr climatology of Sanders and Hoffman is reconstructed using a composite technique. Annual and seasonal mean potential temperature analyses over the continental United States, southern Canada, northern Mexico, and adjacent coastal waters are presented. In addition, gridpoint frequencies of moderate and strong potential temperature gradients are calculated. The results of the mean potential temperature analyses show that moderate and strong surface baroclinic zones are favored along the coastlines and the slopes of the North American cordillera. Additional subsynoptic details, not found in Sanders and Hoffman, are identified. The availability of the composite results allows for the calculation of potential temperature gradient anomalies. It is shown that these anomalies can be used to identify significant frontal baroclinic zones that are associated with weak potential temperature gradients. Together the results and reviews in this paper show that surface potential temperature analyses are a valuable forecasting and analysis tool allowing analysts to distinguish and identify fronts, baroclinic troughs, and nonfrontal baroclinic zones.

Keywords

Potential Temperature Potential Vorticity Eastern Slope Sierra Nevada Mountain Potential Temperature Gradient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© American Meteorological Society 2008

Authors and Affiliations

  1. 1.Department of Chemical, Earth, Atmospheric, and Physical SciencesPlymouth State UniversityPlymouthUSA

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