Scientific research and public service require ground-based measurements of precipitation density, type and rate. But the sought-after accuracy remains elusive and measurements tend to be too sparse to represent high spatial variability or rapidly evolving storms. Existing ground-based weather stations remain bulky and expensive, composed of assemblages of instruments, each dedicated to a specific task and operated using proprietary algorithms and methods requiring dedicated trained personnel. For this Phase I study, Particle Flux Analytics will mature a highly capable, small, automated weather sensor aimed at solving these challenges. The SnowPixel is a pixelated 24×24 micro- hotplate array that provides a video heat map of environmental cooling signatures. In Phase I, the SnowPixel system will be redesigned for automated adaptive sampling of both winds and hydrometeor evaporation. Signal analysis algorithms and processor control will be developed for the SnowPixel to yield coincident statistics of mass, frequency, and density of individual snow and rain particles, along with bulk precipitation rate, density, and type, and the direction and speed of wind gusts. Planned activities include laboratory testing and field deployment at a site in Utah as well as at an established DOE ARM measurement site in the Southern Great Plains. At the conclusion of Phase I, Particle Flux Analytics aims to bring to market a disruptive beta- prototype SnowPixel device, introducing sophisticated, small, automated, weather stations for the scientific, weather, agricultural, insurance, military, and transportation safety sectors. A broad customer base has already been established.
