On the impact of wave-like disturbances on turbulent fluxes and turbulence statistics in nighttime conditions: a case study
Abstract. The interpretation of flux measurements in nocturnal conditions is typically fraught with challenges. This paper reports on how the presence of wave-like disturbances in a time series, can lead to an overestimation of turbulence statistics, errors when calculating the stability parameter, erroneous estimation of the friction velocity u* used to screen flux data, and errors in turbulent flux calculations. Using time series of the pressure signal from a microbarograph, wave-like disturbances at an AmeriFlux site are identified. The wave-like disturbances are removed during the calculation of turbulence statistics and turbulent fluxes. Our findings suggest that filtering eddy-covariance data in the presence of wave-like events prevents both an~overestimation of turbulence statistics and errors in turbulent flux calculations. Results show that large-amplitude wave-like events, events surpassing three standard deviations, occurred on 18% of the nights considered in the present study. Remarkably, on flux towers located in a very stably stratified boundary-layer regime, the presence of a gravity wave can enhance turbulence statistics more than 50%. In addition, the presence of the disturbance modulates the calculated turbulent fluxes of CO2 resulting in erroneous turbulent flux calculations of the order of 10% depending on averaging time and pressure perturbation threshold criteria. Furthermore, the friction velocity u* was affected by the presence of the wave, and in at least one case, a 10% increase caused u* to exceed the arbitrary 0.25 m s−1 threshold used in many studies. This results in an unintended bias in the data selected for analysis in the flux calculations. The impact of different averaging periods was also examined and found to be variable specific. These early case study results provide an insight into errors introduced when calculating "purely" turbulent fluxes. These results could contribute to improving modeling efforts by providing more accurate inputs of both turbulent kinetic energy, and isolating the turbulent component of u* for flux selection in the stable nocturnal boundary layer.