UrbaNet: publc/private partnership

In 2006, NOAA's Air Resources Laboratory (ARL) initiated an urban meteorology research program, UrbaNet, collaborating with AWS Convergence Technologies to explore the utility of using local meteorological networks for improved all-hazards urban forecasts. Under Congressional direction, initial studies focused on the Washington D.C. region as well as ten additional U.S. metropolitan areas. NOAA/ARL's research defining the utility of the private network data has focused on (1) examining the quality of the obtained from the AWS network through development of spatial assessment techniques using the ARL National Capital Region testbed as control observations, (2) extending NOAA's HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT4) dispersion and mesoscale model performance for urban areas using increased density of observational data, (3) developing techniques to nudge forecasts with surface observations, and (4) coupling surface mean and turbulence observations to develop probabilistic dispersion forecasts. Based on studies conducted so far, AWS network observation procedures have been modified to satisfy the NOAA/ASOS data requirements providing data suited to dispersion forecasting needs at over 1000 surface observing stations in eleven urban areas. ARL took first steps to assimilate AWS and ARL data into numerical and statistical models to improve dispersion forecast tools. Forecast nudging techniques using Model Output Statistics (MOS) have shown promise in nudging forecast out to 18 hours. Coupling of AWS surface observations with turbulence observations from ARL's testbed has also demonstrated the utility of probabilistic dispersion forecasts. This work targets one specific need – to extend NOAA's dispersion forecasting capabilities into urban areas.