What are the Best Thermodynamic Quantity and Function to Define a Front in Gridded Model Output

Fronts can be computed from gridded datasets such as numerical model output and reanalyses, resulting in automated surface frontal charts and climatologies. Defining automated fronts requires quantities (e.g., potential temperature, equivalent potential temperature, wind shifts) and kinematic functions (e.g., gradient, thermal front parameter, frontogenesis). Which are the most appropriate to use in different applications remains an open question. This question is investigated using two quantities (potential temperature, equivalent potential temperature) and three functions (magnitude of the horizontal gradient, thermal front parameter, frontogenesis) from both the context of real-time surface analysis and climatologies from 38 years of reanalyses. The strengths of potential temperature to identify fronts are that it represents the thermal gradients and its direct association with the kinematics and dynamics of fronts. Although climatologies using potential temperature show features associated with extratropical cyclones in the storm tracks, climatologies using equivalent potential temperature include moisture gradients within air masses, most notably at low latitudes that are unrelated to the traditional definition of a front, but may be representative of a broader definition of an airmass boundary. These results help to explain previously published frontal climatologies featuring maxima of fronts in the subtropics and tropics. The best function depends upon the purpose of the analysis, but Petterssen frontogenesis is attractive, both for real-time analysis and long-term climatologies, in part because of its link to the kinematics and dynamics of fronts. Finally, this study challenges the conventional definition of a front as an airmass boundary and suggests that a new, dynamically based definition would be useful for some applications.