4.15
A Lagrangian Footprint Model for Stratifications Ranging from Stable to Convective
Natascha Kljun, Swiss Federal Institute of Technology, Zurich, Switzerland; and M. W. Rotach and H. P. Schmid
A quantitative description of the surface flux budgets of atmospheric trace gases on a regional scale is far from trivial, as any source near the ground could potentially contribute to a measured concentration or flux at a given receptor. The size of this upwind surface area of influence (footprint) for a measured trace gas flux or concentration is governed by the height of the measurement, the surface roughness, atmospheric stability and the turbulent velocity fluctuations.
There is a need for models which can be used to design experiments under various environmental and experimental conditions (i.e., different measurement heights, thermal stratification and surface properties) and to simplify the interpretation of results. However, most of the analytical models to predict footprints are limited to the surface layer, whereas all the footprint models based on a Lagrangian particle model fulfill the well-mixed condition only for one given stability regime.
The present footprint model is of the Lagrangian type and employs a recently established approach using backward trajectories of particles. It is based on a 3-dimensional Lagrangian Stochastic Particle Dispersion model satisfying the well-mixed condition continuously for stable to convective conditions, as well as for receptors above the surface layer (e.g., for use in connection with aircraft measurements). For the first time in a footprint model, a density kernel method is introduced. This allows for a significant reduction in the number of simulated particles for the same accuracy.
As a first step, the approach is evaluated indirectly by comparing the model results with corresponding estimates of the well-established analytical footprint models FSAM and SAM. Although FSAM/SAM are theoretically restricted to moderate stratification within the surface layer, they are often used under convective conditions, as no other simple model for unstable conditions exists so far.
The simulations indicate that the two models are in good agreement within the surface layer. As expected, the predicted footprints differ under strongly unstable conditions and for receptors above the surface layer. The more unstable the stratification, the larger the difference between the two models in the peak location and size of the footprint. This is due to the fact that the surface layer model - in contrast to the present Lagrangian approach - does not take into account the skewness of the vertical velocity under convective conditions with the associated consequences on dispersion.
Session 4, Convective Boundary Layers (Bls)
Wednesday, 9 August 2000, 10:15 AM-4:45 PM
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