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Abstract
The low-frequency contribution to the systematic and random sampling errors in single-tower eddy-covariance flux measurements is investigated using large-eddy simulation (LES). We use a continuous LES integration that covers a full year of realistic weather conditions over Cabauw, the Netherlands, and emulate eddy-covariance measurements. We focus on the daytime flux imbalance, when the turbulent flux is sufficiently resolved. Averaged over the year, daytime single-tower eddy-covariance flux measurements lead to a significant systematic underestimation of the turbulent flux. This underestimation depends on the averaging period and measurement height. For a 3600-s averaging period at 16-m height, the systematic underestimation reduces to a few percent, but for 900-s averaged tall-tower measurements at 100-m height, the fluxes are systematically underestimated by over 20 %. The year-long dataset facilitates an investigation into the environmental conditions that influence the eddy-covariance flux imbalance. The imbalance problem is found to vary widely from day to day, strongly dependent on the flow regime. In general, the imbalance problem reduces with increased mean wind speed, but days having the largest imbalance (over twice the average) are characterized by roll vortices that occur for average wind speeds, typically having a boundary-layer height (zi) to Obukhov length (L) ratio of 10<?zi/L<100.
Highlights
Turbulent fluxes, responsible for the vertical transport of heat, humidity, momentum and trace gases through the atmosphere and between surface and atmosphere, are among the most important boundary-layer processes that have to be modelled in numerical weather and climate models
We have extended the work of Kanda et al (2004) and Steinfeld et al (2007), who used large-eddy simulation (LES) to study the eddy-covariance (EC) flux imbalance in terms of flow properties
We confirm the presence of a significant systematic bias in EC flux measurements for all measurement periods and measurement heights, after averaging over a full year
Summary
Responsible for the vertical transport of heat, humidity, momentum and trace gases through the atmosphere and between surface and atmosphere, are among the most important boundary-layer processes that have to be modelled in numerical weather and climate models. Using LES, Kanda et al (2004) emulated EC observations in a clear convective boundary layer, and found a systematic underestimation in single-tower EC fluxes ranging between roughly 5 and 25 % (at a measurement height of 100 m) due to turbulent organized structures, depending on wind speed. The filter functions in Eq 10 fall off around f = 1/T , which implies that any non-zero mean flux at larger time scales is underestimated This creates systematic sampling errors, which represent a bias to the mean sampled value. Effects of surface inhomogeneities or large-scale gradients are not represented in the LES run and are not considered
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