Abstract
Abstract. A field study was undertaken to investigate the accuracy of two micrometeorological flux footprint models for calculating the gas emission rate from a synthetic 10 × 10 m surface area source, based on the vertical flux of gas measured at fetches of 15 to 50 m downwind of the source. Calculations were made with an easy-to-use tool based on the Kormann–Meixner analytical model and with a more sophisticated Lagrangian stochastic dispersion model. A total of 59 testable 10 min observation periods were measured over 9 d. On average, both models underestimated the actual release rate by approximately 30 %, mostly due to large underestimates at the larger fetches. The accuracy of the model calculations had large period-to-period variability, and no statistical differences were observed between the two models in terms of overall accuracy.
Highlights
Micrometeorological techniques such as eddy covariance and flux–gradient methods measure a vertical flux of gas in the atmosphere, which can be used to deduce the flux from an underlying surface area of interest
As opposed to larger source areas, the small area should amplify the differences between the models and increase the relative uncertainty in the footprint calculations
From an end-user’s perspective, our results show that both the KM and the Lagrangian stochastic (LS) model returned reasonably accurate flux footprint estimates on average, for the shorter measurement fetches
Summary
Micrometeorological techniques such as eddy covariance and flux–gradient methods measure a vertical flux of gas in the atmosphere, which can be used to deduce the flux from an underlying surface area of interest. If the area of interest has a limited spatial extent or is located some distance from the atmospheric measurement, the relationship between the two fluxes can be complex, as the measured flux may be capturing a dynamic mixture of surface fluxes from both inside and outside the area of interest. In these cases, flux footprint modelling can be used to quantify the relationship between the measured atmospheric flux and the surface flux from the area of interest. While more rigorous footprint models are clearly more defensible, the simpler KM model has the advantage of rapid analysis and the existence of software tools that make its application more accessible to non-specialists (Neftel et al, 2008)
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