Horizontal and Vertical Turbulent Fluxes Forced by a Gravity Wave Event in the Nocturnal Atmospheric Surface Layer Over the Amazon Forest

A nocturnal gravity wave was detected over a south-western Amazon forest during the Large-Scale Biosphere–Atmosphere experiment in Amazonia (LBA) in the course of the dry-to-wet season campaign on October 2002. The atmospheric surface layer was stably stratified and had low turbulence activity, based on friction velocity values. However, the passage of the wave, an event with a period of about 180–300 s, caused negative turbulent fluxes of carbon dioxide (CO₂) and positive sensible heat fluxes, as measured by the eddy-covariance system at 60 m (≈30 m above the tree tops). The evolution of vertical profiles of air temperature, specific humidity and wind speed during the wave movement revealed that cold and drier air occupied the sub-canopy space while high wind speeds were measured above the vegetation. The analysis of wind speed and scalars high frequency data was performed using the wavelet technique, which enables the decomposition of signals in several frequencies allowed by the data sampling conditions. The results showed that the time series of vertical velocity and air temperature were −90° out of phase during the passage of the wave, implying no direct vertical transport of heat. Similarly, the time series of vertical velocity and CO₂ concentration were 90° out of phase. The wave was not directly associated with vertical fluxes of this variable but the mixing induced by its passage resulted in significant exchanges in smaller scales as measured by the eddy-covariance system. The phase differences between horizontal velocity and both air temperature and CO₂ concentration were, respectively, zero and 180°, implying phase and anti-phase relationships. As a result, the wave contributed to positive horizontal fluxes of heat and negative horizontal fluxes of carbon dioxide. Such results have to be considered in nocturnal boundary-layer surface-atmosphere exchange schemes for modelling purposes.