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Measurements of atmospheric pressure by mesoscale transects of vehicle platforms such as the National Severe Storms Lab (NSSL) mobile mesonets have previously been collected in various targeted field campaigns. The challenges involved were specifically documented in the very different environments of tornadogenesis (Markowski et al., 2002) and orographic foehn winds (Raab and Mayr 2008). In recent years, the Jackson State University Mobile Meteorology Unit (MMU) has been developed with broad ranging applications in mind. Barometric pressure was originally expected only to be used for calculation of potential temperature over transects with significant elevation change. Previous studies have determined a dynamic change in measured pressure due to vehicle motion relative to the air that varies quadratically with speed, in agreement with theoretical expectations. This quadratic relationship is examined for the MMU under a variety of conditions. In order to consider least squares regression of this relationship, it was necessary to also have accurate speed and elevation data. Since even quite small elevation changes can produce measurable pressure changes, it was considered necessary to reduce pressures in each transect to the mean elevation using the methodology of Markowski et al. (2002). This required a combination of digital elevation model (DEM) and geographic positioning system (GPS) data to have sufficiently accurate elevations matched to the locations of the pressure measurements. Speed relative to ground from the GPS was used in place of actual air flow speed. Cases to be discussed include transects from approximately 20 to 200 km in length: approximately uniform conditions in flat terrain; crossing of orographic barriers; and cold fronts. Differences between pressure data collected with and without a pressure port are also considered. The impacts for determination of mesoscale pressure gradients, potential temperature, and other derived quantities will be evaluated. 

North American drylines are distinct air mass boundaries that have often been examined for their relation to the initiation of severe convective storms. Three cases of drylines occurring in synoptically quiescent environments are analyzed using data obtained from a single mobile platform in concert with data from operational synoptic and mesoscale observing systems. Very distinct moisture contrasts were noted in a nocturnal April case in mountainous terrain in the Trans-Pecos region of West Texas. The other two cases revealed multi-step moisture transitions within synoptically diffuse moisture gradients. Their evolution over time suggests that such multi-step patterns may be associated with diurnal and geographic forcing transitions, as well as positioning of deep moist convection. 

Two cases of differently oriented frontal systems within Mississippi are investigated using data from a mobile vehicle-mounted observing system in addition to standard atmospheric data sources. Results highlight the capability of the mobile system to diagnose thermodynamic features at a wide range of spatial scales. Widely recognized frontal characteristics are noted in the data, together with some variations. Variations include a lack of strong relationship between frontal position and rainfall bands when examined at small scales. In one case a seemingly anomalous narrow band of significantly lower humidity was identified within about 20 km of the front. These results are indicative of the need for multi-scale data sources and for careful consideration of departures from classical models of phenomena for specific cases. 

High spatial/temporal resolution mobile transects were used to examine the thermal and moisture structure of the sea-breeze front (SBF) along the Mississippi coast during August 2014 and 2015. Compared to most similar studies, conditions were much warmer and more humid. Results show a 1-2 g/kg increase in mixing ratio across the mature SBF zone, and up to a 2.5°C temperature decrease. When SBF radar fine lines are identifiable, their position agrees very well with surface thermodynamic changes. Although temperatures were cooler at the coast, microscale offsets in location of thermal, moisture, and radiative features are noted in the vicinity of the SBF, particularly when the sea-breeze system is relatively weak or immature. At times, it seems that strong solar insolation causes the temperature to rise temporarily within the transition zone behind the kinematic SBF. These results are at variance with most other diagnostic studies. Some thermodynamic variations are noted within the marine air mass in connection to minor water bodies such as Biloxi Bay. The potential for passage of the SBF to at least temporarily increase human heat stress as described by heat index is also noted. 

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models.