Assimilation of LIDAR Backscatter and Wind Data into and Atmospheric Transport and Dispersion Model

This presentation will provide an overview of a recent investigation into the utilization of elastic backscatter LIDAR measurements to improve near range atmospheric transport and dispersion (AT&D) predictions for airborne contaminants. In many releases of toxic materials into the atmosphere, there is often little or no in-situ meteorological information available and the specifics of the quantity and/or release rate for the event are largely unknown.  This scenario requires an analyst to make estimates of the required AT&D inputs to inform a resulting downwind contaminant concentration prediction.  Given these limitations, it is posited that measurements collected by a LIDAR system which can provide aerosol cloud detections and coincident wind information could be utilized reduce the associated uncertainty in the analyst’s downwind contaminant prediction.  To test this hypothesis, LIDAR retrievals from the Real-time Eye-safe Visualization Evaluation and Analysis Lidar (REVEAL) instrument, developed by Spectral Sensor Solutions, obtained from the recent S/K Challenge II field campaign at Dugway Proving Grounds, were used to develop/evaluate methods for directly assimilating these data into the Second-order Closure Integrated PUFF (SCIPUFF) model. The effectiveness of these methods are evaluated against available observations and overall performance is compared for similar operational scenarios where LIDAR data was unavailable. Results from a recent real-time demonstration of this capability at the S/K Challenge III field trials will also be shown.