Global Science & Technology Inc, (GST) provides the National and Oceanic Atmospheric Administration (NOAA) mobile platform environmental observations as part of the National Mesonet program. GST's Mobile Platform Environmental Data (MoPED) system acquires mobile platform data from participating commercial fleets, whose vehicles sample environmental conditions along major transportation routes, critical surface infrastructure (i.e., highway interchanges, bridges) and urban and neighborhood areas. The mobile platform observations include vehicle and equipment metadata in order to provide context to the reported environmental observations. MoPED disseminates the vehicle's environmental data and metadata to NOAA's Meteorological Assimilation Data Ingest System (MADIS).

The mobile platform observations increase both the temporal and spatial resolution of surface weather observations – both of which are key objectives of the National Mesonet program. The mobile platform observations ‘fill in the gaps' between fixed site stations, which improves situational awareness for forecasters, particularly where the vehicles probe conditions at the microscale level and delineate areas of precipitation not detected by radar. This paper includes several examples where mobile platforms detect areas of precipitation, distinguish precipitation intensity, and detect sunny versus cloudy conditions. These examples are in addition to the microscale reporting of ambient air temperature, pavement temperature, relative humidity, and barometric pressure. Derived parameters (such as dewpoint and sea level pressure) are created from the direct observational data.

Mobile platform observations are highly accurate. Ambient air temperatures are generally within a couple degrees Celsius of Automated Surface Observing System (ASOS) and Road Weather Information System (RWIS) nearby sites that the vehicles pass. The instrumentation is capable of detecting near 100% relative humidity values in precipitation and fog.

Because mobile platforms act as probes, they inherently will find temperature differences that change with elevation or areas of valley fog, for example. Data differences between mobile platforms and nearby ASOS and RWIS are expected because the vehicles are dynamically sampling territory that has different vegetative characteristics than the ‘control' sites.

In addition to environmental data specific to meteorology, MoPED also acquires vehicle data, some of which might augment the directly sampled data made by third-party environmental sensors that are installed on the vehicle. Initial results indicate that third-party instrumentation is more resolved and precise than vehicle-based data. Furthermore, certain vehicle data attributes might be seen on the Controller Area Network (CAN) bus – the vehicle's communications network – however, many of these attributes are ascribed with values such as “not available” or top of range (i.e., road temperature of 1775C), which indicates the message exists, but the sampling does not. Several examples of vehicle data from a representative fleet will be included in this paper.