COMPARISON OF THE LANGRANGIAN FOOTPRINT MODEL LPDM-B WITH AN ANALYTICAL FOOTPRINT MODEL Research Note N. KLJUN 1,⋆ , R. KORMANN 2 , M. W. ROTACH 1 and F. X. MEIXER 2 1 Institute for Atmospheric and Climate Science ETH, Zurich, Switzerland; 2 Max-Planck-Institut für Chemie, Mainz, Germany (Received in final form 14 January 2002) Abstract. We compare flux and concentration footprint estimates of a three-dimensional Lagrangian stochastic dispersion model applying backward trajectories with the results of an analytical footprint model by Kormann and Meixner. The comparison is performed for varying stability regimes of the surface layer as well as for different measurement heights. In general, excellent correspondence is found. Keywords: Backward trajectories, Boundary-layer stability, Lagrangian stochastic particle disper- sion model, Planetary boundary layer, Source area, Surface layer. 1. Introduction Recently, several methods to derive footprint estimates have been proposed. These methods can be classified in stochastic Lagrangian and analytical approaches, and large-eddy simulations. Lagrangian models describe the diffusion of a scalar by a stochastic differential equation (e.g., Leclerc and Thurtell, 1990; Horst and Weil, 1992; Flesch et al., 1995; Rannik et al., 2000; Kljun et al., 2002), while analytical models are based on solutions of the diffusion equation by applying a K-theory model (e.g., Schuepp et al., 1990; Schmid and Oke, 1990; Wilson and Swaters, 1991; Horst and Weil, 1992; Kormann and Meixner, 2001). An example of foot- print predictions using large-eddy simulations can be found in Leclerc et al. (1997). Schmid (2002) provides a review of footprint models and their applications. Since footprint estimates – both in extension and intensity – are highly de- pendent on the height of the measurement, wind velocity, surface roughness, heterogeneity of the underlying surfaces, and atmospheric stability, a model evalu- ation under varying environmental conditions would be very important. However, the availability of applicable experimental data sets with sufficient resolution is very limited so far. Thus, here we compare footprint estimates predicted by a Lag- rangian and an analytical model. One of the strengths of Lagrangian models is that, if properly constructed and given correct velocity statistics, they can be applied in ⋆ Present affiliation: Biometeorology Group, University of British Columbia, Vancouver, Canada. E-mail: natascha.kljun@ubc.ca Boundary-Layer Meteorology 106: 349–355, 2003. © 2003 Kluwer Academic Publishers. Printed in the Netherlands.