The use of lidar-detected smoke puff evolution for dispersion calculations

Dispersion modelling is a key component of modern emergency responses to catastrophic atmospheric releases. However, periodic algorithmic advances are needed to effectively use new datasets acquired with modern remote sensing instruments. This work demonstrates that coherent Doppler lidar can be used to provide valuable new inputs for dispersion models. While related research seeks to retrieve other required inputs for dispersion modelling systems, for example velocity vectors from radial velocities, this paper assembles and contextualizes analytical and algorithmic approaches for an improved understanding of dispersion characteristics in specific atmospheric scenarios using Doppler lidar data. Longitudinal (along-wind), lateral (cross-wind), and vertical dispersion parameters are calculated and used to estimate eddy diffusivities based on Gaussian curve fitting and first-order closure. Empirical relations based on similarity theory are used to verify these estimates, and reasonable agreement is found between the two approaches. Several improvements are also suggested for the lidar scanning techniques to facilitate retrieval of dispersion parameters.