The nocturnal flow at the site is characterized by the superposition of turbulent and nonturbulent fluctuations. In a fully turbulent night, such as 15 November 2015 (Fig. 1), there is a clear dominant wind direction at all levels. In this case, it is very rare that the horizontal wind components switch sign above the canopy. In contrast, during the intermittent night of 14 November 2015 (Fig. 2), there is no dominant wind direction at any level above the canopy, as both horizontal components switch sign many times throughout the night. Low-frequency fluctuations are superposed on the turbulent fluctuations, causing the mean wind direction to change quadrants frequently throughout the night. Such fluctuations have been recently attributed to submeso flow (Mahrt, 2009), while in the pollutant dispersion community similar phenomena are often referred to as meandering (Oettl et al., 2005). The most relevant difference between the two nights regards the magnitude of the turbulent mixing (Table 1). All relevant turbulence statistics are significantly larger on 15 November than on 14 November. The relative difference of the turbulence statistics between nights increases steadily in the vertical. As an example, TKE at 41 m is 3.4 times larger in the turbulent night than in the intermittent case, while at 80 m, TKE is 8.2 times larger in the turbulent night. Similar increases occur for the corresponding ratios of σ_w and $({\stackrel{\mathrm{‾}}{u^{\prime }{w}^{\prime }}}^{\mathrm{2}}+{\stackrel{\mathrm{‾}}{v^{\prime }{w}^{\prime }}}^{\mathrm{2}}{)}^{\mathrm{1}/\mathrm{4}}$ between the two nights.

Another interesting characteristic that indicates a contrast between the two nights shown in Fig. 1 and Fig. 2 regards the degree of vertical coupling across the levels, a phenomenon that has been observed by van Gorsel et al. (2011), Oliveira et al. (2013), and Jocher et al. (2017). In the turbulent night, temperatures were always similar between the levels of 41 and 55 m, while at 80 m, it was slightly warmer, but with the same cooling tendency throughout the period. CO₂ was correspondingly similar between 22 and 41 m, with the same tendencies and slightly lower values at 80 m. Although the mean trend is similar at 22 and 41 m, substantial, short time deviations towards higher CO₂ values were observed at 22 m (Fig. 1d). This is in line with the higher variability in CO₂ values in the lower canopy, as can be seen from the profiles (Fig. 3a). This higher variability and stronger gradient (in both CO₂ and O₃) in the lower canopy point to a decoupling of the sub-canopy even in the turbulent night. As the 22 m level is within the maximum of the leaf area index (LAI) (∼ 24 m), which separates the upper canopy from the lower canopy, it will be influenced by both regimes. The gradients between 24 and 38 m are always positive for O₃ and negative for CO₂. This can be related to the reactivity of O₃ as it reacts with compounds emitted from the soil (mainly NO) and plants (alkenes) and is not only taken up by stomata but is also deposited to leaf surfaces in considerable amounts, especially under humid conditions (Fuentes and Gillespie, 1992; Rummel et al., 2007). At night, CO₂ is emitted by soils and plants due to respiration, causing a negative gradient.

All quantities showed much larger variation across the levels in the intermittent night (Fig. 2). Furthermore, sporadic events of coupling occurred during bursts of intermittent turbulence (Fig. 2, shaded areas). It has been assumed that the turbulent bursts occurred whenever σ_w > 0.15 ms⁻¹. During these events of coupling, the gradients of temperature and CO₂ concentration became sporadically smaller across the vertical, except for the 80 m level, indicating that the coupling induced by the events extended over a layer shallower than 80 m. In general, the temporal evolution of all scalars shows a monotonic increase (in CO₂) or decrease (in temperature and O₃) throughout the turbulent night at all levels (Fig. 1). In the intermittent night, on the other hand, large increases and decreases in all scalars occur in small periods of time at all levels, except at 80 m. As CO₂ has a clear source at the ground and O₃ has a clear sink at the ground, one can identify from the profiles whether air is coming from aloft or from below (Fig. 4). Air from above is rich in O₃ and lower in CO₂, whereas air from below is rich in CO₂ but depleted in O₃. From this perspective, in the first event air is mixed down from aloft, while in the second event air is mixed both upward and downward from the canopy top. In the third event, air is first mixed down and finally there is a burst of air going upwards from the canopy. At 80 m, temperature (Fig. 2b) and CO₂ (Fig. 2d) show much smaller fluctuations than at the other levels. This is further evidence that the stable boundary layer (SBL) thickness is shallower during the intermittent night, such that the canopy exchange fluxes do not affect the state of the atmosphere at 80 m. This fact contrasts strongly with the steady trends in both scalars at 80 m during the turbulent night (Fig. 1b and Fig. 1d), which indicates that in this case, this level is fully coupled through turbulence to the canopy top. While in the turbulent nighttime, scalar fluxes did not vary substantially throughout the period (Fig. 5a, c, e, and g), the most intense turbulent fluxes of sensible heat (Fig. 5b), CO₂ (Fig. 5d), O₃ (Fig. 5f), and latent heat (Fig. 5h) during the intermittent night occurred during these coupling periods (Table 2).

Previous studies have reported that nonturbulent modes of the flow only become relevant when turbulence is weak (Acevedo et al., 2014), a likely consequence of the diffusive nature of turbulence destroying the nonturbulent temporal and spatial variability in the atmospheric variables. This relationship between the turbulent and nonturbulent modes of the flow is illustrated by the TKE spectrum during both nights (Fig. 6). In the turbulent case, most of the energy is associated with turbulence, so that the most energetic timescale is near 10 s at all levels, except for 80 m (Fig. 6a). At this level, the longest timescales are the most energetic, but the 10 s turbulent maximum and a cospectral gap (near 100 s) are still evident. In contrast, in the intermittent night of 14 November, at all levels most energy prevails on the longest timescales provided by the decomposition method. This energy is associated with the low-frequency fluctuations responsible for the variability in the wind direction visible in Fig. 2a and Fig. 2c. These spectra confirm that when fully turbulent conditions prevail, the energy of the nonturbulent, low-frequency modes of the flow is reduced considerably. The cospectra of the fluxes of sensible heat (Fig. 7a, d, f, and i), CO₂ (Fig. 7b, g, and j), O₃ (Fig. 7e), and latent heat (Fig. 7c, h, and k) confirm the enhanced turbulent exchange of all quantities in the turbulent night compared to the intermittent one. They also show that, consistently to what occurs with TKE, the nonturbulent exchange of these scalars is enhanced in the intermittent case. In particular, a significant low-frequency flux of CO₂ occurs at 22 m in the intermittent night, such that the total flux at this level is larger during the intermittent night (4.0 µmol m² s⁻¹, Table 3) than during the turbulent one (1.1 µmol m² s⁻¹) when all scales of the motion that are captured by the decomposition window are considered. This is in line with the idea that nonturbulent motions better penetrate the canopy. The same occurs for latent heat, which shows a mean flux of 8.8 W m⁻² in the intermittent night and of 2.8 W m⁻² in the turbulent night when all scales are considered. Even for 5 min fluxes, the larger fluxes still occur in the intermittent night (1.7 vs. 1.0 µmol m² s⁻¹ in the turbulent night for CO₂ and 3.8 vs. 2.5 W m⁻² for latent heat), but the differences are smaller. These numbers show that the low-frequency contributions dominate the exchange of CO₂ and moisture in the interior of the forest in the intermittent night. Santos et al. (2016) found that the dominant timescales of the vertical velocity fluctuations and sensible heat flux within an Amazonian rain forest canopy (at a different site) are shifted towards larger values than those above it. Our results support these findings, adding the information that the exchanges of CO₂ and humidity within the canopy are also dominated by nonturbulent contribution at very stable nights. It is likely that the same process affects other scalars, such as O₃, whose concentrations are perturbed by intermittent events as shown in Fig. 4b.

Another interesting contrast between the turbulent and intermittent nights can be seen for the sensible heat (Fig. 7a), CO₂ (Fig. 7b), and latent heat (Fig. 7c) cospectra at 80 m, which show an almost total absence of turbulent fluxes (timescale smaller than 100 s) of these quantities at this height in the intermittent case. This result explains the reduced fluctuations in temperature (Fig. 2b) and CO₂ (Fig. 2d) at 80 m in the intermittent night, adding evidence to the suggestion that the SBL may be rather shallow in that night, possibly such that the 80 m level is near its top. The large fluctuations in water vapor at 80 m (Fig. 2f) may be related to the enhanced low-frequency flux of this quantity during this night (Fig. 7c).

Figure 8 shows the spectra and cospectra of the turbulent fluctuations and fluxes averaged over the entire period of 15 nights. The distinction between turbulent and nonturbulent fluctuations across the vertical is evident in the averaged TKE spectra (Fig. 8a). On average, a timescale around 100 s separates the two types of fluctuations. This can be seen by the fact that S_TKE decreases with height above the canopy, following what typically happens to turbulent fluctuations in the stable boundary layer (Kruijt et al., 2000; Santos et al., 2016) only for timescales smaller than 100 s. For longer timescales, S_TKE increases with height. This result has been previously shown by Andreae et al. (2015) at the same tower but for a different period. The average cospectra of all scalars show the largest turbulent fluxes at 41 m, with a sharp maximum on a timescale around 30 s. Within the canopy, systematic positive fluxes of CO₂ and latent heat happen on all timescales. The magnitude increases with increasing timescale. Therefore, this is an indication that the CO₂ and humidity exchanges in the interior of the forest may be, to a large extent, caused by nonturbulent motion. This process will be further investigated later in this paper when the scale dependence of the fluxes is compared to the stability within and above the canopy. The average sensible heat cospectrum at 22 m is negative for timescales smaller than 50 s and positive for larger timescales. Santos et al. (2016) showed that sensible heat fluxes near the forest floor are positive for all timescales, while they are negative for all timescales at the canopy top. At intermediate heights, they tend to be like those shown in Fig. 8c. These authors also showed that the height within the canopy where the total sensible heat flux switches sign from upward at lower levels to downward at higher levels is stability dependent, increasing as it becomes more stable.

The comparison of the fluxes determined with 5 min and 109 min time windows and their stability dependence for the entire period of 15 nights provides interesting information on the scalar exchange processes within and above the canopy. Sensible heat flux at 22 m (Fig. 9i) switches sign at intermediate stability for both 5 min and 109 min averaging periods. This is in agreement with the result obtained by Santos et al. (2016) that the height where the sensible heat flux switches sign is stability dependent. In the present case, the critical value at which the 5 min sensible heat flux at 22 m switches sign is 0.25. At the same height, CO₂ (Fig. 9j) and latent heat (Fig. 9k) fluxes are similar with both averaging times at near-neutral conditions but become appreciably larger with 109 min windows than with 5 min windows as conditions become more stable. This result confirms the idea that the CO₂ and humidity exchange within the canopy at very stable conditions are dominated by processes with long timescales. At 41 m (Fig. 9e–h), 55 m (Fig. 9d), and 80 m (Fig. 9a–c), the 109 min fluxes of scalars are more erratic, sometimes with no clear dependence on Ri_can. The 5 min fluxes, on the other hand, show a tendency to decrease in magnitude with stability at all heights above the canopy. The 5 min TKE decreases with stability at all levels (Fig. 10), but at 80 m it becomes near 0 for Ri_can>0.2. This is the same range of stability for which the 5 min fluxes of heat and CO₂ are virtually suppressed, indicating that in these very stable conditions the stable boundary layer thickness may be close to 80 m or shallower. When the same quantities are compared to Ri_top (Fig. 11), the most significant difference is that the 109 min fluxes at 41 m (Fig. 11e–h, black lines) and 55 m (Fig. 11d, black line) show a more systematic dependence on stability. This result indicates that the low-frequency exchange at the canopy top and above is controlled by the stability over a large distance above the forest.

The 0.25-Ri_can threshold, over which the 22 m turbulent sensible heat flux switches sign, is used to classify each series as weakly stable (Ri_can≤0.25) or very stable (Ri_can>0.25). The average spectra for each of these classes are shown in Fig. 12. At all levels, the low-frequency TKE is almost independent of stability, as for timescales larger than 100 s the TKE spectra of the very stable series approach those of the weakly stable ones. For smaller timescales, on the other hand, a significant distinction prevails, with TKE being many times larger under weakly stable conditions than during very stable conditions. The turbulent portions of the scalar fluxes above the canopy (41 m and above) respond accordingly, always being much larger in magnitude in the weakly stable cases (Fig. 13).

At 22 m, the criterion for classifying the time series ensures that the sensible heat flux on small timescales must be negative under the weakly stable conditions and positive under the very stable ones. This is shown in Fig. 13i, but it is remarkable that even in the weakly stable cases, there is a range of timescales for which the sensible heat flux within the canopy is upward. This range is also observed (however broader) in the very stable class, although in this case the negative maximum associated with turbulent exchange is absent. This result shows that low-frequency exchange of heat within the canopy is consistently upward, regardless of stability. Therefore, the main control exerted by stability regards the depth within the canopy where the downward turbulent heat flux penetrates (Santos et al., 2016). The total 22 m fluxes of CO₂ (Fig. 13j) are larger in the very stable class than in the weakly stable one, which is mainly caused by the contribution of timescales larger than 100 s, corroborating the results from the case studies (Sect. 3). For latent heat (Fig. 13k), the total flux is slightly larger in the weakly stable cases, and this result is mainly caused by the contributions of fluxes with timescales smaller than 100 s.

All data used in this study are kept in the ATTO Databases at Instituto de Pesquisas da Amazônia and Max Planck Institut für Chemie. The overall project description can be found at http://www.mpic.de/en/research/collaborative-projects/atto.html. Data access can be requested from the coauthors responsible for maintaining the dataset: Matthias Sörgel (m.soergel@mpic.de) and Alessandro Araújo (alessandro.araujo@gmail.com).

The authors declare that they have no conflict of interest.

This article is part of the special issue “Amazon Tall Tower Observatory (ATTO) Special Issue”. It is not associated with a conference.