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 \with wavelengths as short as 150 km and at 15-min intervals, are made available as animated contoured fields. This mesoanalysis system is capable of resolving many kinds of mesoscale phenomena and allows the forecaster to monitor their changing structure and intensity. The effectiveness of the system is demonstrated with two recent events selected from the several cases that have been analyzed. The first case consists of a gravity wave train that produced multiple precipitation bands. The second event involves 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 analysis 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. Furthermore, this analysis system could be implemented within the context of the Local Analysis and Prediction System (LAPS) on the Advanced Weather Interactive Processing System (AWIPS), and so take advantage of the graphical user interface to allow shift forecasters to easily choose a suite of applicable advection vectors for the analysis. This automated mesoanalysis system has taken what has traditionally been a many-month process of analyzing gravity waves and other mesoscale phenomena and made it possible to complete very detailed mesoanalyses in a matter of only ~4h behind real-time. If high temporal resolution ASOS data were made available over the Internet instead of only by modem and a spatial bandpass filter replaced the temporal bandpass filter used herein, the analysis system could be run continuously while very closely approaching real-time. An even brighter future of performing extremely detailed mesoanalyses in real-time lies in the expected increase in the density of the surface-observing network. The Oklahoma Mesonet and similar state mesonetworks either in place or under development can produce incredible detail in the analysis fields, and will soon be available to the forecaster on AWIPS.