A Simple Parameterisation for Flux Footprint Predictions

Flux footprint functions estimate the location and relative importance ofpassive scalar sources influencing flux measurements at a given receptorheight. These footprint estimates strongly vary in size, depending on receptorheight, atmospheric stability, and surface roughness. Reliable footprintcalculations from, e.g., Lagrangian stochastic models or large-eddy simulationsare computationally expensive and cannot readily be computed for long-termobservational programs. To facilitate more accessible footprint estimates, ascaling procedure is introduced for flux footprint functions over a range ofstratifications from convective to stable, and receptor heights ranging fromnear the surface to the middle of the boundary layer. It is shown that, whenapplying this scaling procedure, footprint estimates collapse to an ensembleof similar curves. A simple parameterisation for the scaled footprint estimatesis presented. This parameterisation accounts for the influence of the roughnesslength on the footprint and allows for a quick but precise algebraic footprintestimation.