Experimental evaluation of analytical and Lagrangian surface-layer flux footprint models

Abstract

Three surface-layer flux footprint models have been evaluated with the results of an SF6 tracer release experiment specifically designed to test such models. They are a Lagrangian stochastic model, an analytical model, and a simplified derivative of the analytical model. Vertical SF6 fluxes were measured by eddy correlation at four distances downwind of a near-surface crosswind line source in an area of homogeneous sagebrush. The mean fluxes were calculated for 136 half-hour test periods and compared to the fluxes predicted by the footprint models. All three models gave similar predictions and good characterizations of the footprint over the stability range -0.01 < ZO/L < 0.005. The predictions of the three models were within the limits of the uncertainty of the experimental measurements in all but a few cases within this stability range. All three models are unconditionally recommended for determining the area defined by the footprint over short vegetative canopies in this range. They are also generally appropriate for estimating flux magnitudes within the limits of experimental uncertainties. Most of the mean differences observed between the measured and predicted fluxes at each of the four towers reflect a tendency for the measured fluxes to be greater than those predicted by the three models. Rigorous verification of the models in strongly stable conditions was complicated by the need to obtain very accurate measurements of small fluxes in only marginally stationary conditions. Verification in strongly unstable conditions was hampered by the limited number of appropriate data.

Assessing eddy-covariance flux tower location bias across the Fluxnet-Canada Research Network based on remote sensing and footprint modelling

“…The SAFE model is developed on the basis of the two-dimensional Eulerian advection-diffusion equation (Horst and Weil, 1992) and its analytical solution relies on a sophisticated formulation of van Ulden (1978) using parameterization methods in Gryning et al (1987), Finn et al (1996) and Kormann and Meixner (2001). This analytical solution takes into account atmospheric stability and uses the wind velocity power law above the canopy, allowing it to be applicable to all conditions of atmospheric stability.…”

“…Although many advances have been made in footprint modelling and experimental validation (e.g. Leclerc and Thurtell, 1990;Wilson and Swaters, 1991;Horst and Weil, 1994;Finn et al, 1996;Kormann and Meixner, 2001;Leclerc et al, 2003), the influence of the variability of footprint and vegetation heterogeneities on EC flux measurements has not yet been investigated fully.…”

Towards standards for measuring greenhouse gas fluxes from agricultural fields using instrumented towers

“…Models used to predict flux footprint range from Gaussian based analytical models Horst andWeil 1992, 1994;Kaharabata et al 1997Kaharabata et al , 1999, to Lagrangian stochastic models (Raupach 1989;Leclerc and Thurtell 1990;Wilson and Swaters 1991) -both forward and backward (Flesch and Wilson 1995;Flesch 1996), and large eddy simulation models ). More recently, experiments have been conducted to verify the model -predicted footprints (Finn et al 1996;Kaharabata et al 1997;Leclerc et al 2003a, b;Cooper et al 2003).…”

Sources of variability in mercury flux measurements

“…These low sampling heights were chosen to minimize the footprint measured at the intakes. This gradient measurement system was designed to look at small footprints, typically with 25 m of fetch, which is realistic for the given sampling heights, surface roughness, and wind characteristics [Finn et al, 1996]. The fetch (upwind distance over which surface characteristics are representative of those at the observation point) at Steamboat Springs at the UG-GSC site was reasonably fiat in most directions and was sparsely vegetated with desert sagebrush (Artemisia tridentata), with number densities varying significantly with wind sector.…”