An Automated System for the Analysis of Gravity Waves and Other Mesoscale Phenomena

Abstract

An automated near-real-time system for the surface analysis of gravity waves and other mesoscale phenomena is developed, tested, and applied to several cases. Five-minute observations from the Automated Surface Observing System (ASOS) network provide the primary source of data for the mesoanalysis system. ASOS time series data are downloaded, subjected to considerable quality control, bandpass filtered, and objectively analyzed using a time-to-space conversion (TSC) adaptation of the traditional Barnes scheme. The resultant analyses, which can resolve features in the ASOS network with wavelengths as short as 150 km and at 15-min intervals, are made available as animated contoured fields. Even though this mesoanalysis system was designed primarily for gravity wave detection, it is capable of resolving other kinds of mesoscale phenomena and allowing the analyst to monitor their changing structure. The effectiveness of the system is demonstrated with two recent events selected from several cases that have been analyzed. The first case consisted of a gravity wave train that propagated through the Ohio River valley and produced multiple precipitation bands. The second event involved a complex family of mesohighs and wake lows associated with a convective system over the southeastern United States. Variations in the surface wind field and precipitation distribution are related to the mesoscale pressure field in both cases. The ability of this mesoanalysis system to monitor mesoscale phenomena resides in the successful application of TSC principles to high temporal resolution surface data. Although the TSC assumption may not be strictly valid in more complex situations, for many applications this mesoanalysis system offers critical information needed for making accurate nowcasts, with the caveat that the means by which ASOS 5-min data are made available can be improved.