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. The eddy covariance (EC) technique has emerged as the prevailing method to observe the ecosystem–atmosphere exchange of gases, heat and momentum. ECmeasurements require rigorous data processing to derive the fluxes that can be used to analyse exchange processes at the ecosystem–atmosphereinterface. Here we show that two common post-processing steps (time-lag estimation via cross-covariance maximisation and correction for limitedfrequency response of the EC measurement system) are interrelated, and this should be accounted for when processing EC gas flux data. These findingsare applicable to EC systems employing closed- or enclosed-path gas analysers which can be approximated to be linear first-order sensors. These ECmeasurement systems act as low-pass filters on the time series of the scalar χ (e.g. CO2, H2O), and this induces a time lag(tlpf) between vertical wind speed (w) and scalar χ time series which is additional to the travel time of the gas signal in thesampling line (tube, filters). Time-lag estimation via cross-covariance maximisation inadvertently accounts also for tlpf and henceoverestimates the travel time in the sampling line. This results in a phase shift between the time series of w and χ, which distorts themeasured cospectra between w and χ and hence has an effect on the correction for the dampening of the EC flux signal at high frequencies. Thisdistortion can be described with a transfer function related to the phase shift (Hp) which is typically neglected when processing ECflux data. Based on analyses using EC data from two contrasting measurement sites, we show that the low-pass-filtering-induced time lag increasesapproximately linearly with the time constant of the low-pass filter, and hence the importance of Hp in describing the high-frequencyflux loss increases as well. Incomplete description of these processes in EC data processing algorithms results in flux biases of up to 10 %, withthe largest biases observed for short towers due to the prevalence of small-scale turbulence. Based on these findings, it is suggested that spectralcorrection methods implemented in EC data processing algorithms are revised to account for the influence of low-pass-filtering-induced time lag.

atmospheric measurement techniques

The high-frequency response correction of eddy covariance fluxes – Part 1: An experimental approach and its interdependence with the time-lag estimation