Abstract

A 140-m micrometeorological tower has been operating since August 2016 at 4 km from the coastline and 250 m from a thermal power plant that releases heat from its 20-m stacks in southeastern Brazil. The measurements include 11 levels of turbulence observations and 10 levels of slow-response temperature and humidity. The observed atmospheric structure is largely dependent on the wind direction with respect to the power plant. When winds blow from the plant to the tower, the air layer between 20 and 60 m of the atmosphere may be warmed by as much as 2°C. In these circumstances there are events when the emissions pass directly by the tower. They allow the analysis of turbulence structures of thermal plumes generated from the plant’s heat release in comparison with those generated by the surface heating. In the more common case of winds blowing from the tower to the plant, the observations allow a detailed description of the local atmospheric boundary layer. During the day, vertical profiles of turbulent quantities and their spectral distributions show a cycle controlled by interactions between the land and oceanic surfaces, such as a thermal internal boundary layer. At night, there is a systematic tendency of progressive stabilization throughout the period, suitable for the analysis of the boundary layer transition from weakly to very stable conditions. The data also grant the inference of detailed vertical profiles of turbulent diffusion coefficients directly from observations.

A 140-m micrometeorological tower provides detailed observations of the vertical structure of the mean and turbulent fields of meteorological variables of a coastal region in southeastern Brazil, and reveals the extent to which a nearby power plant affects the local atmospheric boundary layer.

Micrometeorological studies have historically relied on observations at towers as a primary source of experimental data on turbulent and mean quantities in the lowest meters of the atmospheric boundary layer. The main advantage of the micrometeorological tower is the easy access with flexibility to adjust the experimental setup that best fits the needs of any given research project. Tower observations, on the other hand, are vertically limited to the “tower layer” (Panofsky 1973), which very rarely exceeds the heights of 30–50 m.

Historically, micrometeorological models rely strongly on similarity relationships, which are important for allowing inferences of vertical profiles based on observations made in idealized conditions (Kaimal et al. 1976; Caughey and Palmer 1979; Caughey et al. 1979). However, the conditions of horizontal homogeneity, stationarity, and fully developed turbulence, on which similarity theory is based, are often violated in the real-world atmospheric boundary layer. In recent years the study of heterogeneous surfaces and nonstationary and intermittent turbulence have, in fact, become some of the major areas of micrometeorological research. It is not certain how vertical profiles obtained under these conditions deviate from those found in undisturbed situations. For this reason it is desirable that observations in heterogeneous environments cover as high a portion of the atmospheric boundary layer as possible. Remote sensing observation methods, such as sodar, lidar, and wind profilers, have largely evolved in recent years (Beyrich 1997; Cohn and Angevine 2000; Coulter and Kallistratova 2004; Tucker et al. 2009) and allow sampling the entire atmospheric boundary layer. However, such methods provide information with limited temporal and vertical resolutions, besides having higher uncertainties than in situ observations, such as those provided by towers. Furthermore, contrary to towers, they do not provide raw turbulence data that allow a detailed analysis of the complex features of turbulence signals.

An example of a consolidated tall micrometeorological tower is the 213-m mast operating continually in Cabauw, the Netherlands, since 1972. Its contribution to fundamental micrometeorological knowledge is vast. It includes the experimental basis on which the local similarity theory, applied to stable boundary layers with continuous turbulence, has been established by Nieuwstadt (1984) and the more recent developments on the transitions between weakly and very stable boundary layers (Van de Wiel et al. 2012, 2017). Another example is the Boulder Atmospheric Observatory, a 300-m tower that operated from 1978 to 2016 (Kaimal and Gaynor 1983) and has provided the observational framework for advances in distinct fields of meteorology, such as micrometeorology (Finnigan et al. 1984; Panofsky 1984), instrumentation (Kaimal and Gaynor 1991), and air quality (Sievering 1982). More recently, the Zotino Tall Tower Observatory, a 302-m tower, has been deployed in central Siberia, with detailed observations of air chemistry and meteorology (Heimann et al. 2014). The Amazon Tall Tower Observatory in Brazil, which started operating in 2017, provides high-resolution vertical profiles of atmospheric concentrations of different chemical species and of turbulent and mean atmospheric quantities from a 329-m tower (Andreae et al. 2015).

In August 2016, a highly instrumented micrometeorological site started operating in southeastern Brazil. The most important platform deployed is a 140-m tower with 11 levels of turbulence observations, which provide a detailed characterization of the vertical structure of the atmospheric boundary layer up to higher heights than are commonly available in similar micrometeorological studies until recently. The tower is installed 4 km from the coastline, next to a thermal power plant. Both these facts make this a pioneer initiative, as no previous similarly detailed observations of the turbulent field have been performed either at the vicinity of a source of pollutants or at a coastal region.

The study is sponsored by Linhares Geração SA, a Brazilian energy company, and has the major objectives of improving the understanding of dispersion patterns in the complex environment where the power plant is located. The achievement of this broader purpose demands an accurate description of the local atmospheric boundary layer, and that includes a number of phenomena that are not entirely understood by the micrometeorological community, such as a thermal internal boundary layer (TIBL; Garratt 1990), very stable boundary layers, and submeso flow, described in the present manuscript.

The experimental site provides the characterization of the local micrometeorology from the surface to 140 m. During daytime, this tower height allows observations of the thermal internal boundary layer up to a height where quantities are well mixed. At night, when moderate to intense winds determine weakly stable conditions, the tower covers a significant portion of the entire stable boundary layer (SBL). Under low-wind nocturnal conditions, the entire SBL may be within the tower height, allowing the investigation of the complex interactions between turbulent and nonturbulent modes of the flow that typically arise in such situations (Sun et al. 2015; Cava et al. 2017). Furthermore, it allows the direct determination of turbulent parameters that are applied in Eulerian and Lagrangian dispersion models. Usually, such a determination relies on similarity relationships that are expressed in terms of surface measurements alone. In this case, its effectiveness is evaluated from the comparison between observed concentration data and those simulated by the similarity-based models. With the high-tower observations, on the other hand, they may act as direct input into simple expressions that locally provide the dispersion parameters. Besides, they may provide improved dispersion parameterizations, which in the present case are specially applied to a coastal environment, given that the terrain and heterogeneity characteristics are included in the observed turbulence properties. The observations from the tower can be used to quantify the extent to which the power plant affects thermodynamic structures of the local atmospheric boundary layer, a knowledge that may be used to introduce these effects in dispersion models. Being located 4 km from the coast, the data also provide understanding on how the marine and coastal environments influence the atmospheric boundary layer at the tower site.

LOCAL CHARACTERISTICS AND MEASUREMENTS.

The tower (19°31´53˝S, 39°48´03˝W) is situated in the township of Linhares, Espírito Santo State, southeastern Brazil (Fig. 1a), 4 km from the coast (visible in Fig. 1e), in a region where the coastline is oriented from south-southwest to north-northeast (Figs. 1b,c). The continental area around the tower is flat for more than 30 km from the site, and the terrain elevation starts to increase gradually to the west beyond 30 km from the site, reaching 900 m at 150 km from the site. The tower is 245 m north of the 13.8-m-high main building of a thermoelectric power plant operated by Linhares Geração SA (Fig. 1d). Heat, gases, and aerosols are released from 20-m-high stacks from the main building. At the east side of the tower, there is a small woodland (visible in Figs. 1d,e), with a 9-m average height for the highest trees.

Fig. 1.

(a) Location of the tower (blue star) with respect to South America. (b) Regional and (c) local topography and location of the tower with respect to the coastline. (d),(e) Photographs of the site.

Fig. 1.

(a) Location of the tower (blue star) with respect to South America. (b) Regional and (c) local topography and location of the tower with respect to the coastline. (d),(e) Photographs of the site.

The measurements at the tower (Table 1) include turbulence observations at 11 levels with a higher vertical resolution near the surface and equally spaced intervals of 19 m above 20 m. At 20 m, fast-response observations of H2O and CO2 allow the determination of latent heat and CO2 fluxes. Vertical profiles of the concentrations of these two gases are also observed between the surface and 20 m by atmospheric profilers. Slow-response observations include temperature and humidity profiles at the full extension of the tower, with the purpose of providing a detailed characterization of the local thermal structure, and soil temperature and moisture profiles down to 1.1-m depth. Additional observations include air pressure, precipitation, and short- and longwave radiation components. Observations of most variables started 6 August 2016 and are scheduled to run for two complete years. The results presented in this manuscript refer to the first 11 months of observations, between August 2016 and June 2017.

Table 1.

Details on the instrumentation deployed.

Details on the instrumentation deployed.
Details on the instrumentation deployed.

The meridional (north–south) component of the winds plays a dominant role in this study because it determines whether winds blow past the tower before the power plant or otherwise. The site is located at a transition region between tropical and subtropical climates. The most relevant large-scale weather systems are the South American monsoon (Carvalho et al. 2004), responsible for most local precipitation, and the arrival of cold fronts originating in the extratropical portion of the continent. The semipermanent Atlantic high pressure system is responsible for moist-air advection toward the region, which sometimes causes stratiform precipitation. This dynamic climatology causes local winds from two prevailing directions. The most important one is a northeast wind associated with the semipermanent high pressure centered east of the site. The second most important wind direction is from the south, typically in postfrontal conditions. On average, 30 frontal systems arrive at the region each year, being more frequently in the winter months (Andrade 2015) so that northeasterlies prevail between September and February, while southerlies and southeasterlies dominate in the other months. The period of observations reported here was drier than normal, with a total precipitation of 775.6 mm from August 2016 to June 2017; the normal is 1,093.5 mm for the period. The wind regime, on the other hand, followed the normal pattern with northerly meridional components from August 2016 to February 2017 and southerly components prevailing between March and June 2017 (Table 2).

Table 2.

Wind directions observed in the different months of the project.

Wind directions observed in the different months of the project.
Wind directions observed in the different months of the project.

THE EFFECT OF THE POWER PLANT ON THE LOCAL ATMOSPHERIC BOUNDARY LAYER.

The observations at the tower are largely affected by wind direction, especially with respect to the nearby power plant. When winds have a northerly meridional component, they blow past the tower before they reach the plant. In this case, classical boundary layer profiles are observed from the surface to the tower top. Under northerly wind conditions, nocturnal potential temperature profiles are highly dependent on wind speed (Fig. 2a); that is, more intense winds reduce the surface thermal inversion as they mix the SBL. In this situation, the potential temperature lapse rate near the surface ranges from near 0.1 K m−1 under very weak winds to near neutral when the nocturnal winds are intense. During the day with northerly winds, unstable thermal profiles are commonly observed throughout the entire tower layer, with the most unstable layer in the lowest 40 m. (Fig. 2c). These diurnal thermal profiles are almost independent of northerly wind speed. When southerly winds prevail, the observations show that the heat emitted by the plant causes significant impacts on the local atmospheric boundary layer. At night, when southerly flow is intense enough, a warmed layer is evident between 20 m, which is the stacks’ height of the heat release, and 60 m (Fig. 2b). The heating may be large enough to cause the layer between 60 and 120 m to become unstable at night; that is, the heat release from the power plant may have significant impacts on the thermodynamics in dispersion models. Modeling studies of these impacts are currently being carried out by scientists involved in the project using large-eddy simulation. During daytime, thermal profiles indicate an elevated heat source, especially for relatively strong southerly winds in comparison with the temperature profiles with northerly winds when only the surface heating exists (Fig. 2c). In addition, daytime thermal profiles are highly dependent on wind speed, which indicates that heat advection plays an important role in the vertical variation of temperature.

Fig. 2.

Average vertical profiles of potential temperature with respect to its value at 132 m for (a),(b) nocturnal and (c),(d) diurnal periods, with (left) northerly and (right) southerly meridional wind components for 10 different classes of wind speed, according to the legend in each panel.

Fig. 2.

Average vertical profiles of potential temperature with respect to its value at 132 m for (a),(b) nocturnal and (c),(d) diurnal periods, with (left) northerly and (right) southerly meridional wind components for 10 different classes of wind speed, according to the legend in each panel.

Another interesting phenomenon when thermal plumes from the plant pass by the tower is an abrupt enhancement of fluctuations of temperature and the three wind components measured by the sonic anemometers. An example of such occurrence is seen in the time series starting at 1200 LST 6 October 2016 (Fig. 3). The 75-m wind direction diagram (Fig. 3a) shows that during the first 40 min of the period, winds came from the southeast. A slight shift toward the south was accompanied by a very large increase in the fluctuations of the wind component in the mean wind direction u (Fig. 3b) and temperature T (Fig. 3d). Those large fluctuations persisted for nearly 80 min until the wind direction changed back to southeasterly. This phenomenon associated with upstream wind from heated plumes occurs frequently during days with southerly winds and is often observed at all the observation levels except some bottom levels. Such occurrences are frequent during days with a southerly wind component and often span the entire extension of the tower, except for its lowest levels. A spectral analysis shows that both the u-wind component (Fig. 3c) and temperature (Fig. 3e) signals keep the properties of turbulence, such as the Kolmogorov power law in the inertial subrange, despite the increase of spectral energy that reaches an order of magnitude in comparison with the corresponding spectra from the undisturbed measurements.

Fig. 3.

(a) Wind direction at 75 m as a function of time, given by radial scale. (b) Time series of longitudinal wind component and (c) its power spectra. (d) Time series of temperature and (e) its power spectra. In (b)–(e), the colors relate to different time intervals shown in (a).

Fig. 3.

(a) Wind direction at 75 m as a function of time, given by radial scale. (b) Time series of longitudinal wind component and (c) its power spectra. (d) Time series of temperature and (e) its power spectra. In (b)–(e), the colors relate to different time intervals shown in (a).

In the literature most of the studies on the characteristics of isolated thermal plumes were carried out by means of aircraft observations with foci on measurements of chemical compositions (Sandroni et al. 1981; Springston et al. 2005). Therefore, the direct observation of emission plumes by a micrometeorological tower constitutes a very relevant and pioneer aspect of the observations. It allows for the determination of characteristics of plumes, such as their thickness, persistence at a given wind direction, and their dependence on ambient air stability and wind field. Optimistically, the data during these occurrences may also provide information on intrinsic turbulent characteristics of plumes during entrainment and detrainment processes, and radial variations of temperature and turbulence kinetic energy (TKE) within plumes, which may be used to improve plume-rise models and, consequently, dispersion models by considering plume properties. The observations may also provide direct evidence of the occurrence of peculiar dispersion phenomena, such as looping and fumigation.

MICROMETEOROLOGICAL CHARACTERISTICS.

Winds with northerly meridional components are more common at the site, especially in the summer months (Table 2). Under these conditions, the tower is a tall micrometeorological observatory of the local conditions, undisturbed by the nearby power plant. In particular, it provides a very rich characterization of the lower atmospheric boundary layer at a coastal environment.

The typical diurnal evolution of mean quantities does not vary significantly for northerly winds, as the arrival of cold fronts is the most significant large-scale meteorological phenomenon that affects the site, which is more common during autumn and winter than the other seasons. Therefore, the diurnal composites of mean (Fig. 4) and turbulent (Fig. 6) quantities for days with prevailing northerly winds are fairly representative of the conditions for a large number of the specific days of the project. During the daytime, the typical winds are from the northeast, which characterizes them as onshore winds, coming from the coastline. After 1200 LST, there is almost no directional shear over the entire tower layer as a result of convective mixing (Fig. 4b), and mean winds stronger than 5 m s−1 are observed at levels as low as 10 m (Fig. 4a). As previously shown in Fig. 2c, an unstable layer dominates the entire extension of the tower in the afternoon (Fig. 4c). The evening transition happens typically at 1800 LST, when the wind direction starts shifting toward the north and wind speeds start to decrease sharply. Cooling starts slowly after the transition, but a strong thermal stratification sets up after 0000 LST, when wind speeds are less than 2 m s−1 below 20 m. The wind direction after 0000 LST is typically from the north. All patterns shown in Fig. 4 happen throughout the year, with reduced seasonal dependence. The (monthly averaged for days with northerly winds) daily minimum temperature at 2 m varies from 19.4° (May) to 24.2°C (December), while the average daily maximum temperature varies from 31.2° (June) to 36.2°C (January). Similarly, the (monthly averaged for days with northerly winds) maximum wind speed observed at the tower varies from 10.0 (June) to 12.7 m s−1 (October).

Fig. 4.

Average daily cycle of (a) wind speed, (b) wind direction, (c) potential temperature, and (d) specific humidity at the different heights for days with a northerly meridional wind component during the entire period.

Fig. 4.

Average daily cycle of (a) wind speed, (b) wind direction, (c) potential temperature, and (d) specific humidity at the different heights for days with a northerly meridional wind component during the entire period.

When southerly winds prevail, the presence of the power plant affects some meteorological variables, as described in the previous section. The daily cycle from a day with southerly winds when the plant was not operating illustrates how the conditions are appreciably different in that situation (Fig. 5). The main differences include more intense winds at higher levels (Fig. 5a), which intensify the mixing and prevent the formation of a very stable layer later during the night (Fig. 5c). This fact and increased cloudiness cause a reduced temperature range with respect to what is observed during northerly winds (Fig. 4c). The enhanced cloudiness also causes specific humidity to increase with height (Fig. 5d).

Fig. 5.

Daily cycle of (a) wind speed, (b) wind direction, (c) potential temperature, and (d) specific humidity at the different heights for 22 Sep 2016. A 72-min running mean has been applied to the original average time series from each level.

Fig. 5.

Daily cycle of (a) wind speed, (b) wind direction, (c) potential temperature, and (d) specific humidity at the different heights for 22 Sep 2016. A 72-min running mean has been applied to the original average time series from each level.

The sensible heat flux at 1 m reaches an average maximum of 250 W m−2 at local noon and decays fairly rapidly in the vertical (Fig. 6a). A linear decrease of sensible heat flux with height is evident only in the upper half of the tower layer. The height where the linear decrease of the sensible heat flux extrapolates upward to zero, zconv, may be used as a surrogate for the height of the capping inversion zi, based on tower data alone (Fig. 6a; black dots with scale on the right axis). This estimation is based on the well-established linear heat flux profile in the convective boundary layer, supported by both observations (Kaimal et al. 1976; Caughey and Palmer 1979) and numerical modeling (Nieuwstadt et al. 1984; Van Heerwaarden et al. 2017). Interestingly, such an extrapolation indicates a consistent growth of the mixed layer early in the morning, such that its thickness exceeds 600 m at 1000 LST. This is similar to what is typically observed for continental mixed layers in their earlier stages of growth (Tennekes 1973). After 1000 LST, however, when the wind direction shifts to onshore flow (Fig. 4b), the height where the heat flux convergence becomes smaller and tends to be, on average, around 300 m during the afternoon. This value is consistent with previous studies of coastal mixing layers, based on aircraft observations (Shao et al. 1991; McElroy and Smith 1991; Källstrand and Smedman 1997; Luhar et al. 1998). McElroy and Smith (1991) found the TIBL to be a few hundred meters thick, only reaching more than 1 km thick at a distance farther than 40 km from the coast. A single highly instrumented tall tower is a very useful tool for characterizing the TIBL. The tower height and the high vertical resolution of turbulence observations permit the determination of the TIBL thickness based on sensible heat flux extrapolation, as shown in Fig. 6a. Although its Eulerian nature does not allow for direct observation of the spatial structure of the layer, it allows for understanding other features, such as the onset of the TIBL at the tower location, and how the local boundary layer evolves in the vertical prior to that moment. Furthermore, the long-term nature of the observations will permit detailed understanding of how the TIBL thickness and its evolution depend on other properties, such as the background flow and the boundary layer thermal structure, as well as relating these properties to local observations of turbulent and mean quantities.

Fig. 6.

As in Fig. 4, but for (a) sensible heat flux, (b) TKE, (c) standard deviation of horizontal wind components , and (d) standard deviation of vertical wind component.

Fig. 6.

As in Fig. 4, but for (a) sensible heat flux, (b) TKE, (c) standard deviation of horizontal wind components , and (d) standard deviation of vertical wind component.

The TKE, defined as

 
formula

at the lowest levels, averaged over the days with northerly winds, reaches a maximum at 1500 LST. During the daytime, TKE decreases sharply with height only for the lowest 60 m, above which level it decreases slowly with height (Fig. 6b). This is caused by an interesting contrast between its contribution from the horizontal and vertical wind components. Near the surface, TKE is dominated by horizontal turbulence, as indicated by the composites of

 
formula

which decreases sharply with height (Fig. 6c). In contrast, above 80 m, the vertical component σw (Fig. 6d) becomes more important. These patterns are in agreement with those found in some experiments where these quantities have been sampled across the entire convective boundary layer (CBL; Caughey and Palmer 1979; Caughey 1984) as well as with results from large-eddy simulations (Mason 1989; Degrazia et al. 2012). The variances of the turbulent wind components are key parameters in air dispersion models, but they are very rarely observed at levels higher than a few meters above the surface. Therefore, these observations may be directly used in Eulerian and Lagrangian dispersion models. The average magnitudes of the convective velocity scale

 
formula

and friction velocity

 
formula

are also presented in Fig. 6d, using values observed at 5 m and zconv as a surrogate for the mixed-layer depth in the w* estimation.

The structure of the atmospheric boundary layer during nocturnal (Fernando and Weil 2010; Mahrt 2014) and transitional periods (Angevine 2008; Lothon et al. 2014; Wingo and Knupp 2015) has been the subject of major micrometeorological research in recent years. The Linhares tower provides detailed information on the turbulence vertical structure in these circumstances (Fig. 7).

Fig. 7.

As in Fig. 4, but only for transitional and nocturnal periods, and for (a) potential temperature, (b) wind speed, (c) sensible heat flux, and (d) TKE.

Fig. 7.

As in Fig. 4, but only for transitional and nocturnal periods, and for (a) potential temperature, (b) wind speed, (c) sensible heat flux, and (d) TKE.

The composites show that the sensible heat flux switches sign around 1800 LST within 15 min among all vertical levels in the early evening (Fig. 7c). On the other hand, the potential temperature drops much faster near the surface than aloft, such that above 80 m a slightly unstable layer persists after 1800 LST (Fig. 7a), when the heat flux at the same level has already become downward. Blay-Carreras et al. (2014) reported on a sensible heat flux switching sign before the vertical temperature gradient switched sign near the surface, indicating the occurrence of countergradient heat fluxes at those levels. This phenomenon can be investigated with the present data in great detail by looking at individual cases. Furthermore, the composites in Fig. 7 also suggest the occurrence of a persistent countergradient heat flux in the residual layer. In contrast with what happens in the evening transition period, a sensible heat flux switches sign first at the surface during the morning transition (Fig. 7c). On average, such a sign change happens at 0600 LST near the surface but only more than an hour later at the highest levels in the tower. The specific humidity composite, provided solely by data from the thermohygrometers (Fig. 4d), shows local maxima near the surface during both morning and evening transitions. The evening maximum has been found to be associated with the mixed-layer collapse at a time when latent heat fluxes are positive (Acevedo and Fitzjarrald 2001). The morning maximum is likely a consequence of a similar process—evaporation into a very shallow convective boundary layer, which is still in its earlier growth stages. In both cases, the tower offers the unique opportunity for investigating the phenomena with a large number of occurrences, and with a detailed perspective on their vertical structure.

In between the evening and morning transitions, the SBL regime at Linhares is characterized by progressive stabilization as the night progresses. The continuous surface cooling certainly determines this behavior, but the wind direction also plays an important role. In the beginning of the nocturnal period, onshore winds are still present (Fig. 4b). As winds turn northerly, the airmass trajectory becomes more continental, favoring warm advection at the upper levels. Consequently, weakly stable conditions with continuous turbulence, moderate thermal gradients, fairly intense winds, and downward heat fluxes are commonly observed during the first half of the night (until 0000 LST). The downward heat flux at 5 m reaches an average maximum of −12 W m−2 around 2100 LST, consistent with the observation that such a maximum value occurs in intermediate stability (Malhi 1995; Mahrt et al. 1998), as the heat flux is reduced by weak vertical temperature gradients in near-neutral conditions and by the decreased turbulence in the very stable case. During the second half of the nighttime, very stable conditions dominate, with weak or intermittent turbulence associated with drastic reductions of mean wind speeds and the establishment of an intense thermal inversion, which, on average, reaches near 0.03 K m−1 over the lowest 100 m. The clear contrast between the two halves of the nighttime indicates that this dataset may be very suitable for studying regime transitions in the SBL. The existence of two regimes with remarkably different properties in the SBL has been established in studies such as those by André and Mahrt (1982) and Mahrt et al. (1998). Recently, Sun et al. (2012), Van de Wiel et al. (2012), and Acevedo et al. (2016) have shown that there is a wind speed threshold above which the SBL is weakly stable with fully developed turbulence, and below which it is very stable, with calm or intermittent turbulence. In particular, Sun et al. (2012) showed that only in the fully turbulent regime does TKE increase steadily with wind speed. In the very stable regime, this increase is more subtle and TKE is much more variable for a given value of wind speed (Acevedo et al. 2016). At the Linhares tower, the progressive stratification of the SBL along the time is illustrated by the relationship between the hourly averaged turbulence velocity scale VTKE ≡ TKE1/2 and wind speed (Fig. 8). This diagram indicates that the very stable regime with weak turbulence, only weakly dependent on wind speed, sets up after 0200 LST. This is when the average absolute heat flux (Fig. 6c) and TKE (Fig. 6d) cease decreasing and assume an average small value for the remainder of the night. During any specific night, more complex situations occur, especially after the very stable regime is established, and intermittent turbulence bursts may happen. They can originate either at the surface or at higher levels, affecting the local stratification and mean winds as they propagate through the SBL.

Fig. 8.

Average dependence of the turbulence velocity scale on mean wind speed for the nocturnal period. Individual dots represent averages for each minute of the daily cycle, while numbers are the hourly averages. Only nights with a northerly meridional wind component during the entire period have been considered.

Fig. 8.

Average dependence of the turbulence velocity scale on mean wind speed for the nocturnal period. Individual dots represent averages for each minute of the daily cycle, while numbers are the hourly averages. Only nights with a northerly meridional wind component during the entire period have been considered.

The composites (Figs. 4, 6, and 7) therefore indicate the existence of four distinct daily regimes at the site. Their turbulence characteristics can be further detailed looking at their spectral distributions in terms of temporal scales. Average multiresolution (Mallat 1989; Howell and Mahrt 1997) TKE spectra show not only the contrast between turbulent and nonturbulent (submeso) modes of the flow, but also their vertical structure and how they evolve along the day (Fig. 9). Furthermore, these spectra provide the characteristic turbulent time scales, which are necessary parameters in Lagrangian dispersion models (Rodean 1996). Just after sunrise and before 1000 LST, when a continental CBL starts its growth, a TKE spectral peak is evident only at the lowest 10 m of the tower, at temporal scales between 1 and 10 s (Fig. 9a). Above that height, spectral density increases monotonically with time scale, such that the most energetic scales are longer than 1,000 s, dominated by nonturbulent fluctuations that have been recently referred to as submeso flow (Mahrt 2009; Acevedo et al. 2014; Cava et al. 2017). The next regime of the daily cycle typically starts at 1000 LST, when the wind direction shifts toward the northeast (Fig. 4b), causing onshore flow at the site. This is the period when a shallow TIBL, on average 300 m deep (as estimated from the heat flux convergence in Fig. 6a), occurs. The largest wind magnitudes (Fig. 4a) and TKE intensities (Fig. 6b) of the daily cycle happen in this period, with large values at the top of the tower, which is about the middle of the TIBL at this time. In this period, the turbulent peak of the TKE spectrum is evident over the entire tower layer (Fig. 9b). Below 10 m, it is situated at time scales between 1 and 10 s, and above that height, it shifts to scales between 10 and 100 s. The shorter turbulence time scales near the surface are likely associated with the proximity to the ground and the existing obstructions. The increase of the time scale with height was also observed at the 1999 Cooperative Atmosphere–Surface Exchange Study (CASES-99) site (Sun et al. 2016). After sunset around 1800 LST, an SBL develops, on average. This is the start of the third regime, characterized by fully developed turbulence in a stable environment, and the diagram of VTKE versus V indicates that it lasts, on average, until 0200 LST (Fig. 8). Northeasterly winds indicate that onshore flow is still present (Fig. 4b). The temporal scales of the flow in this period (Fig. 9c) are generally similar to what happens in the afternoon but with smaller spectral energies. Finally, between 0200 and 0600 LST a very stable boundary layer is present, and the TKE spectral energies are severely reduced over the entire tower layer (Fig. 9d). Nevertheless, a turbulence peak can be identified at most heights, and its temporal scale between 1 and 10 s is almost invariant in the vertical. Above 10 m, most of the energy is in the low-frequency end of the spectrum, characterizing submeso flow.

Fig. 9.

Average multiresolution spectra of TKE as a function of time scale and height, according to the logarithmic color scale. Only days with a northerly meridional wind component during the entire period have been considered.

Fig. 9.

Average multiresolution spectra of TKE as a function of time scale and height, according to the logarithmic color scale. Only days with a northerly meridional wind component during the entire period have been considered.

SUMMARY.

Initial results obtained from a 140-m micrometeorological observatory in southeastern Brazil have been presented and discussed. The site is a coastal location next to a thermal power plant. It has been shown that a large variety of micrometeorological phenomena are observed in detail at the tower. These include the following:

  1. modification of the local atmospheric boundary layer by the heat released by the power plant;

  2. observations of thermal plumes from the plant when they flow directly toward the tower;

  3. a thermal internal boundary layer (TIBL), around 300 m deep, during the afternoon period as a result of the onshore flow;

  4. mean and turbulent quantities during the morning and afternoon transitions;

  5. two nocturnal boundary layer regimes, a weakly stable one in the first part of the nighttime and a very stable one in the second part, as well as the transitions between them; and

  6. spectral distributions of the variables, which tell the dominant scales of the flow.

Ultimately, the observations aim to improve models of atmospheric dispersion and, more generally, conceptual models of the atmospheric boundary layer, as it is affected by the surface variation, such as those induced by the coast or by the power plant, and are subject to diurnal, seasonal, and synoptic temporal cycles. The knowledge acquired with the project therefore has a twofold purpose: it provides the direct observations necessary to feed the dispersion models and, possibly more importantly, it offers the understanding of newly identified patterns caused by both the power plant and the coast.

Both the raw and processed data obtained during this project will be made publicly available in December 2018.

ACKNOWLEDGMENTS

The study was developed within the context of a research and development project sponsored by the companies Linhares Geração S.A. and Termelétrica Viana S.A. (APLPED6932_PROJETOPED_0114), and named “Desenvolvimento de um modelo operacional para simulação em tempo real da dispersão atmosférica de poluentes emitidos por termelétrica a gás natural.” The project is within the context of the investment program in research and development, regulated by the Brazilian National Agency for Electric Energy. The authors are deeply thankful for all of the support provided by these companies for the development of the present work.

REFERENCES

REFERENCES
Acevedo
,
O. C.
, and
D. R.
Fitzjarrald
,
2001
:
The early evening surface-layer transition: Temporal and spatial variability
.
J. Atmos. Sci.
,
58
,
2650
2667
, https://doi.org/10.1175/1520-0469(2001)058<2650:TEESLT>2.0.CO;2.
Acevedo
,
O. C.
,
F. D.
Costa
,
P. E. S.
Oliveira
,
F. S.
Puhales
,
G. A.
Degrazia
, and
D. R.
Roberti
,
2014
:
The influence of submeso processes on stable boundary layer similarity relationships
.
J. Atmos. Sci.
,
71
,
207
225
, https://doi.org/10.1175/JAS-D-13-0131.1.
Acevedo
,
O. C.
,
L.
Mahrt
,
F. S.
Puhales
,
F. D.
Costa
,
L. E.
Medeiros
, and
G. A.
Degrazia
,
2016
:
Contrasting structures between the decoupled and coupled states of the stable boundary layer
.
Quart. J. Roy. Meteor. Soc.
,
142
,
693
702
, https://doi.org/10.1002/qj.2693.
Andrade
,
K. M.
,
2015
:
Climatologia e comportamento dos sistemas frontais sobre a América do Sul. M.S. thesis, Dept. of Meteorology
,
Instituto Nacional de Pesquisas Espaciais
, 185 pp., http://mtc-m16b.sid.inpe.br/col/sid.inpe.br/jeferson/2005/06.15.17.12/doc/publicacao.pdf.
André
,
J. C.
, and
L.
Mahrt
,
1982
:
The nocturnal surface inversion and influence of clear-air radiative cooling
.
J. Atmos. Sci.
,
39
,
864
878
, https://doi.org/10.1175/1520-0469(1982)039<0864:TNSIAI>2.0.CO;2.
Andreae
,
M. O.
, and Coauthors
,
2015
:
The Amazon Tall Tower Observatory (ATTO): Overview of pilot measurements on ecosystem ecology, meteorology, trace gas, and aerosols
.
Atmos. Chem. Phys.
,
15
,
10 723
10 776
, https://doi.org/10.5194/acp-15-10723-2015.
Angevine
,
W. M.
,
2008
:
Transitional, entraining, cloudy and coastal boundary layers
.
Acta Geophysyca
,
56
,
2
20
, https://doi.org/10.2478/s11600-007-0035-1.
Beyrich
,
F.
,
1997
:
Mixing height estimation from sodar data—A critical discussion
.
Atmos. Environ.
,
31
,
3941
3953
, https://doi.org/10.1016/S1352-2310(97)00231-8.
Blay-Carreras
,
E.
,
E. R.
Pardyjak
,
D.
Pino
,
D. C.
Alexander
,
F.
Lohou
, and
M.
Lothon
,
2014
:
Countergradient heat flux observations during the evening transition period
.
Atmos. Chem. Phys.
,
14
,
9077
9085
, https://doi.org/10.5194/acp-14-9077-2014.
Carvalho
,
L. M.
,
C.
Jones
, and
B.
Liebmann
,
2004
:
The South Atlantic convergence zone: Intensity, form, persistence, and relationships with intraseasonal to interannual activity and extreme rainfall
.
J. Climate
,
17
,
88
108
, https://doi.org/10.1175/1520-0442(2004)017<0088:TSACZI>2.0.CO;2.
Caughey
,
S. J.
,
1984
: Observed characteristics of the atmospheric boundary layer. Atmospheric turbulence and air pollution modelling, F. T. M. Nieuwstadt and H. van Dop, Eds., Atmospheric and Oceanographic Sciences Library, Vol. 1, 107–158. Springer, Dordrecht, https://doi.org/10.1007/978-94-010-9112-1_4.
Caughey
,
S. J.
, and
S. G.
Palmer
,
1979
:
Some aspects of turbulence structure through the depth of the convective boundary layer
.
Quart. J. Roy. Meteor. Soc.
,
105
,
811
827
, https://doi.org/10.1002/qj.49710544606.
Caughey
,
S. J.
,
J. C.
Wyngaard
, and
J. C.
Kaimal
,
1979
:
Turbulence in the evolving stable boundary layer
.
J. Atmos. Sci.
,
36
,
1041
1052
, https://doi.org/10.1175/1520-0469(1979)036<1041:TITESB>2.0.CO;2.
Cava
,
D.
,
L.
Mortarini
,
U.
Giostra
,
R.
Richardone
, and
D.
Anfossi
,
2017
:
A wavelet analysis of low-wind-speed submeso motions in a nocturnal boundary layer
.
Quart. J. Roy. Meteor. Soc.
,
143
,
661
669
, https://doi.org/10.1002/qj.2954.
Cohn
,
S. A.
, and
W. M.
Angevine
,
2000
:
Boundary layer height and entrainment zone thickness measured by lidars and wind-profiling radars
.
J. Appl. Meteor.
,
39
,
1233
1247
, https://doi.org/10.1175/1520-0450(2000)039<1233:BLHAEZ>2.0.CO;2.
Coulter
,
R. L.
, and
M. A.
Kallistratova
,
2004
:
Two decades of progress in SODAR techniques: A review of 11 ISARS proceedings
.
Meteor. Atmos. Phys.
,
85
,
3
19
, https://doi.org/10.1007/s00703-003-0030-2.
Degrazia
,
G. A.
,
U.
Rizza
,
F. S.
Puhales
,
G. S.
Welter
,
O. C.
Acevedo
, and
S.
Maldaner
,
2012
:
Employing Taylor and Heisenberg subfilter viscosities to simulate turbulent statistics in LES models
.
Physica A
,
391
,
1020
1031
, https://doi.org/10.1016/j.physa.2011.09.015.
Fernando
,
H. J. S.
, and
J. C.
Weil
,
2010
:
Whither the stable boundary layer? A shift in the research agenda
.
Bull. Amer. Meteor. Soc.
,
91
,
1475
1484
, https://doi.org/10.1175/2010BAMS2770.1.
Finnigan
,
J. J.
,
F.
Einaudi
, and
D.
Fua
,
1984
:
The interaction between an internal gravity wave and turbulence in the stably-stratified nocturnal boundary layer
.
J. Atmos. Sci.
,
41
,
2409
2436
, https://doi.org/10.1175/1520-0469(1984)041<2409:TIBAIG>2.0.CO;2.
Garratt
,
J. R.
,
1990
:
The internal boundary layer—A review
.
Bound.-Layer Meteor.
,
50
,
171
203
, https://doi.org/10.1007/BF00120524.
Heimann
,
M.
, and Coauthors
,
2014
:
The Zotino Tall Tower Observatory (ZOTTO): Quantifying large scale biogeochemical changes in Central Siberia
.
Nova Acta Leopold.
,
117
,
51
64
.
Howell
,
J. F.
, and
L.
Mahrt
,
1997
:
Multiresolution flux decomposition
.
Bound.-Layer Meteor.
,
83
,
117
137
, https://doi.org/10.1023/A:1000210427798.
Kaimal
,
J. C.
, and
J. E.
Gaynor
,
1983
:
The Boulder Atmospheric Observatory
.
J. Climate Appl. Meteor.
,
22
,
863
880
, https://doi.org/10.1175/1520-0450(1983)022<0863:TBAO>2.0.CO;2.
Kaimal
,
J. C.
, and
J. E.
Gaynor
,
1991
:
Another look at sonic anemometry
.
Bound.-Layer Meteor.
,
56
,
401
410
, https://doi.org/10.1007/BF00119215.
Kaimal
,
J. C.
,
J. C.
Wyngaard
,
D. A.
Haugen
,
Y.
Izumi
,
S. J.
Caughey
, and
C. J.
Readings
,
1976
:
Turbulence structure in the convective boundary layer
.
J. Atmos. Sci.
,
33
,
2152
2169
, https://doi.org/10.1175/1520-0469(1976)033<2152:TSITCB>2.0.CO;2.
Källstrand
,
B.
, and
A.-S.
Smedman
,
1997
:
A case study of the near-neutral coastal internal boundary-layer growth: Aircraft measurements compared with different model estimates
.
Bound.-Layer Meteor.
,
85
,
1
33
, https://doi.org/10.1023/A:1000475315106.
Lothon
,
M.
, and Coauthors
,
2014
:
The BLLAST field experiment: Boundary-Layer Late Afternoon and Sunset Turbulence
.
Atmos. Chem. Phys.
,
14
,
10 931
10 960
, https://doi.org/10.5194/acp-14-10931-2014.
Luhar
,
A. K.
,
B. L.
Sawford
,
J. M.
Hacker
, and
K. N.
Rayner
,
1998
:
The Kwiana coastal fumigation study: II—Growth of the thermal internal boundary layer
.
Bound.-Layer Meteor.
,
89
,
385
405
, https://doi.org/10.1023/A:1001746303967.
Mahrt
,
L.
,
2009
:
Characteristics of submeso winds in the stable boundary layer
.
Bound.-Layer Meteor.
,
130
,
1
14
, https://doi.org/10.1007/s10546-008-9336-4.
Mahrt
,
L.
,
2014
:
Stably stratified atmospheric boundary layers
.
Annu. Rev. Fluid Mech.
,
46
,
23
45
, https://doi.org/10.1146/annurev-fluid-010313-141354.
Mahrt
,
L.
,
J.
Sun
,
W.
Blumen
,
T.
Delany
, and
S.
Oncley
,
1998
:
Nocturnal boundary-layer regimes
.
Bound.-Layer Meteor.
,
88
,
255
278
, https://doi.org/10.1023/A:1001171313493.
Malhi
,
Y. S.
,
1995
:
The significance of the dual solutions for heat fluxes measured by the temperature fluctuation method in stable conditions
.
Bound.-Layer Meteor.
,
74
,
389
396
, https://doi.org/10.1007/BF00712379.
Mallat
,
S.
,
1989
:
A theory for multiresolution signal decomposition: The wavelet representation
.
IEEE Trans. Pattern Anal. Mach. Intell.
,
11
,
674
693
, https://doi.org/10.1109/34.192463.
Mason
,
P. J.
,
1989
:
Large-eddy simulation of the convective atmospheric boundary layer
.
J. Atmos. Sci.
,
46
,
1492
1516
, https://doi.org/10.1175/1520-0469(1989)046<1492:LESOTC>2.0.CO;2.
McElroy
,
J. L.
, and
T. B.
Smith
,
1991
:
Lidar descriptions of mixing-layer thickness characteristics in a complex terrain/coastal environment
.
J. Appl. Meteor.
,
30
,
585
597
, https://doi.org/10.1175/1520-0450(1991)030<0585:LDOMLT>2.0.CO;2.
Nieuwstadt
,
F. T. M.
,
1984
:
The turbulent structure of the stable, nocturnal boundary layer
.
J. Atmos. Sci.
,
41
,
2202
2216
, https://doi.org/10.1175/1520-0469(1984)041<2202:TTSOTS>2.0.CO;2.
Nieuwstadt
,
F. T. M.
,
P. J.
Mason
,
C.-H.
Moeng
, and
U
.
Schumann
,
1984
:
Large-eddy simulation of the convective boundary layer: A comparison of four computer codes
.
Turbul. Shear Flows
,
8
,
343
367
, https://doi.org/10.1007/978-3-642-77674-8_24.
Panofsky
,
H. A.
,
1973
: Tower micrometeorology. Workshop on Micrometeorology, D. A. Haugen, Ed., Amer. Meteor. Soc., 151–176.
Panofsky
,
H. A.
,
1984
:
Vertical variation of roughness length at the Boulder Atmospheric Observatory
.
Bound.-Layer Meteor.
,
28
,
305
308
, https://doi.org/10.1007/BF00121309.
Rodean
,
H. C.
,
1996
: Stochastic Lagrangian Models of Turbulent Diffusion. Meteor. Monogr., No. 48, Amer. Meteor. Soc., 84 pp.
Sandroni
,
S.
,
P.
Bacci
, and
D.
Anfossi
,
1981
:
Aircraft observations of plumes emitted from elevated sources
.
Atmos. Environ.
,
15
,
95
100
, https://doi.org/10.1016/0004-6981(81)90130-X.
Shao
,
Y.
,
H. M.
Hacker
, and
P.
Schwerdtfeger
,
1991
:
The structure of turbulence in a coastal atmospheric boundary layer
.
Quart. J. Roy. Meteor. Soc.
,
117
,
1299
1324
, https://doi.org/10.1002/qj.49711750209.
Sievering
,
H.
,
1982
:
Profile measurements of particle dry deposition velocity at an air-land interface
.
Atmos. Environ.
,
16
,
301
306
, https://doi.org/10.1016/0004-6981(82)90446-2.
Springston
,
S. R.
,
L. I.
Kleinman
,
F.
Brechtel
,
Y.-N.
Lee
,
L. J.
Nunnermacker
, and
J.
Wang
,
2005
:
Chemical evolution of an isolated power plant plume during the TexAQS 2000 study
.
Atmos. Environ.
,
39
,
3431
3443
, https://doi.org/10.1016/j.atmosenv.2005.01.060.
Sun
,
J.
,
L.
Mahrt
,
R. M.
Banta
, and
Y. L.
Pichugina
,
2012
:
Turbulence regimes and turbulence intermittency in the stable boundary layer during CASES-99
.
J. Atmos. Sci.
,
69
,
338
351
, https://doi.org/10.1175/JAS-D-11-082.1.
Sun
,
J.
,
L.
Mahrt
,
C.
Nappo
, and
D. H.
Lenschow
,
2015
:
Wind and temperature oscillations generated by wave–turbulence interactions in the stably stratified boundary layer
.
J. Atmos. Sci.
,
72
,
1484
1503
, https://doi.org/10.1175/JAS-D-14-0129.1.
Sun
,
J.
,
D. H.
Lenschow
,
M. A.
LeMone
, and
L.
Mahrt
,
2016
:
The role of large-coherent-eddy transport in the atmospheric surface layer based on CASES-99 observations
.
Bound.-Layer Meteor.
,
160
,
83
111
, https://doi.org/10.1007/s10546-016-0134-0.
Tennekes
,
H.
,
1973
:
A model for the dynamics of the inversion above a convective boundary layer
.
J. Atmos. Sci.
,
30
,
558
567
, https://doi.org/10.1175/1520-0469(1973)030<0558:AMFTDO>2.0.CO;2.
Tucker
,
S. C.
,
W. A.
Brewer
,
R. M.
Banta
,
C. J.
Senff
,
S. P.
Sandberg
,
D. C.
Law
,
A. M.
Weickmann
, and
R. M.
Hardesty
,
2009
:
Doppler lidar estimation of mixing height using turbulence, shear and aerosol profiles
.
J. Atmos. Oceanic Technol.
,
26
,
673
688
, https://doi.org/10.1175/2008JTECHA1157.1.
Van de Wiel
,
B. J. H.
,
A. F.
Moene
,
H. J. J.
Jonker
,
P.
Baas
,
S.
Basu
,
J. M. M.
Donda
,
J.
Sun
, and
A. A. M.
Holtslag
,
2012
:
The minimum wind speed for sustainable turbulence in the nocturnal boundary layer
.
J. Atmos. Sci.
,
69
,
3116
3127
, https://doi.org/10.1175/JAS-D-12-0107.1.
Van de Wiel
,
B. J. H.
, and Coauthors
,
2017
:
Regime transitions in near-surface temperature inversions: A conceptual model
.
J. Atmos. Sci.
,
74
,
1057
1073
, https://doi.org/10.1175/JAS-D-16-0180.1.
Van Heerwaarden
,
C. C.
,
B. J. H.
van Stratum
,
T.
Heus
,
J. A.
Gibbs
,
E.
Fedorovich
, and
J. P.
Mellado
,
2017
:
MicroHH 1.0: A computational fluid dynamics code for direct numerical simulation and large-eddy simulation of atmospheric boundary layer flows
.
Geosci. Model Dev.
,
10
,
3145
3165
, https://doi.org/10.5194/gmd-10-3145-2017.
Wingo
,
S. M.
, and
K. R.
Knupp
,
2015
:
Multi-platform observations characterizing the afternoon-to-evening transition of the planetary boundary layer in northern Alabama, USA
.
Bound.-Layer Meteor.
,
155
,
29
53
, https://doi.org/10.1007/s10546-014-9988-1.

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