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Sun et al. (2012) used 9 levels of observation data on a 60-m tower in the CASE-99 experiment over flat terrain to investigate the relationship between VTKE and V. Obviously different from the CASE-99 experiment, the observation data used in this paper were from a 325-m meteorological gradient tower in Beijing, located on the typical UUS. Figure 2 shows the relationship between VTKE and V at 7 levels on the 325-m tower, and Fig. 3 further shows the relationship between the bin-averaged turbulence strength VTKE and wind speed V. These analyses show that, in contrast with the relationship between VTKE and V from Sun et al. (2012), the relationship between VTKE and V for the 325-m tower can be divided into two types. At 8, 15, 47 and 80 m, the VTKE was very sensitive to the variation in V when V<VT, whereas VTKE increased relatively slowly with V when V>VT. The 8, 15, and 47 m measurement heights were located within the UCL, and 80 m was approximately the UCL height according to the average height of the buildings around the tower. VTKE at these four heights was greatly influenced by the drag shear of the buildings on the air flow in the UCL; thus, VTKE was partly enhanced when V was not high. The estimated wind speed threshold VT for each height (triangles shown in Fig. 3) was based on the largest change of the bin-averaged turbulence strength VTKE difference intervals
$ \Delta {V}_{{\rm{TKE}}}={V}_{{\rm{TKE}}}(V+0.5)-{V}_{{\rm{TKE}}}\left(V\right) $ .Figure 2. The relationship between the turbulence strength VTKE and wind speed V at seven observation levels the Beijing 325-m meteorological tower. The local shear value
$ \partial V/\partial z $ is used to denote the color of the scatter points.Figure 3. The relationship between the bin-averaged turbulence strength VTKE and wind speed V at seven observation levels on the Beijing 325-m meteorological tower. The threshold wind speed VT at each level is marked with a triangle in the color of the height.
A different pattern is noticeable for 140, 200 and 280 m, which is far above the UCL height. Plots of VTKE vs. V at these three heights were more consistent with those obtained by Sun et al. (2012) based on flat underlying surfaces and the results from Yus-Díez et al. (2019) based on complex terrain, in that VTKE was not very sensitive to V and increased slightly with V at 140, 200 and 280 m when V<VT. The variations of VTKE showed a close relationship with V and increased rapidly when V>VT.
Some scattered points obviously did not conform to the above pattern. Moderate turbulence could often be generated for relatively low values of V (regime 3). This otherwise weak turbulence mainly occurred at 140, 200 and 280 m above the canopy. For regime 3, turbulence may correlate with the upside-down structure in the SBL, in which the TKE at a higher altitude associated with strong wind shear is transported downward toward the surface (Mahrt and Vickers, 2002; Banta et al., 2006; Sun et al., 2012; Shi and Hu, 2020); therefore, the turbulence could be enhanced when V<VT. The top-down structure was a special kind of upside-down structure because the maximum TKE occurred at the top of the ABL. The higher TKE in the upper layer may be attributed to different causes, such as Kelvin–Helmholtz instabilities (Newsom and Banta, 2003), gravity waves (Udina et al., 2013), or low-level jets (Karipot et al., 2008), which could generate turbulence aloft.
The local shear value
$ \partial V/\partial z $ is used to denote the color of the data points in Fig. 2. Due to the wind shear effect of the uneven underlying surface in the UCL on the air flows, the wind shear values at 8 and 15 m were also significantly higher and$ \partial V/\partial z $ showed a close relationship with VTKE. Weak turbulence in the lower part of the UCL was always strongly affected by local wind shear when V<VT (regime 1). Figure 4a further shows a strong relationship between$ \partial V/\partial z $ and VTKE in the lower UCL, and the influence of the local wind shear still exists when V>VT. As shown in Fig. 4b, the weak turbulence regime with small eddies mostly corresponded to stable stratification with z/Λ>0.1.Figure 4. The relationship between VTKE and local shear
$ \partial V/\partial z $ (a) and the relationship between VTKE and stability parameter z/Λ at the seven observation levels of the 325-m meteorological tower.For heights above 47 m, when the VTKE was not very strong (VTKE < 1 m2 s−2), the VTKE increased synchronously with increasing local wind shear. However for strong turbulence, stratification approached near neutral (shown in Fig. 4b) as defined by
$ \left|z/\varLambda \right| $ <0.1, and the local wind shear had little effect on VTKE. When V>VT, as shown in Fig. 2 and Fig. 4a, although local shear still had an effect on the turbulence strength in the lower part of the UCL, the turbulence intensity in the upper layer had little relationship with local shear and the turbulence activities were mainly affected by bulk shear with strong winds (regime 2).Generally, for the flat area or where there was no obvious source of anthropogenic heat, the kinematic heat flux
$ \overline{{w}^{{'}}{\theta }_{v}^{{'}}} $ in the NSBL was negative, and the temperature gradient ($ \Delta \theta /\Delta z $ ) was positive. A higher$ \Delta \theta /\Delta z $ indicates a more stable stratification; thus, the generation of turbulence activities might be inhibited. However, as shown in Fig. 5, there were many thermally unstable stratification cases ($ \Delta \theta < 0 $ ) at night for the UBL, and this may be because of the existence of many anthropogenic heat sources in the urban canopy, such as residential heating in winter and emissions from traffic activities.Figure 5. The relationship between the bin-averaged turbulence strength VTKE and the wind speed V at the seven observation levels as a function of potential temperature difference intervals, defined as
$ \Delta \theta =\theta \left(z\right)-{\theta }_{z0} $ , where$ {\theta }_{z0} $ is the potential temperature of reference at 8 m, and$ \theta \left(z\right) $ is the potential temperature at each height z: (a) 280 m, (b) 200 m, (c) 140 m, (d) 80 m, (e) 47 m, and (f) 15 m. The wind speed threshold VT is marked using a black triangle for each height.This paper focuses on the NSBL, and the stable cases were classified according to the local Monin–Obukhov length Λ, that is, z/Λ greater than zero. Nevertheless, as described above, when z/Λ was greater than zero at night (namely, negative sensible heat flux) and the temperature gradient
$ \Delta \theta /\Delta z $ remained negative, it indicates the emergence of counter gradient transportation of heat in the nighttime UBL (especially in UCL). The heat was transmitted from the layer with low temperature to the layer with high temperature. Counter gradient transport may be related to multi-scale vortex motions, especially turbulent coherent structures, which are not well understood (Zhou et al., 2018; Zhang et al., 2021; Shi et al., 2022).Figure 5 shows that the nighttime strong turbulence activity in winter was commonly accompanied by thermal instability (yellow line,
$ \Delta \theta /\Delta z < 0 $ ), especially for the lower layers of the UBL, such as 15, 47 and 80 m. Obviously, the lower region of the UBL was more likely to be affected by the thermal properties within the canopy. In fact, the probability of thermal instability stratification at 15–47 m exceeded 50% (54% for 15 m, 58% for 47 m). Therefore, for nighttime turbulence of the lower layer in the UBL, in addition to the contribution of local shear (regime 1) and bulk shear (regime 2), strong turbulence was also generated by buoyancy turbulence caused by anthropogenic heat, which we refer to as regime 4 in this paper.It is interesting that VTKE vs. V under three temperature stratifications (
$ \Delta \theta > 0.5;0 < \Delta \theta < 0.5;\;\mathrm{a}\mathrm{n}\mathrm{d}\;\Delta \theta < 0 $ ) were very similar when V<VT. Indeed, external effects such as temperature stratification have impacts on the turbulence regime transitions (Van de Wiel et al., 2017; Holdsworth and Monahan, 2019). The relationship between VTKE and V under the three temperature stratifications gradually separated from each other, showing great differences when V>VT. Compared with the turbulence in regime 1, the turbulence in regime 2 showed a closer relationship with thermal stratification.The red line indicates the strong stable stratification (
$ \Delta \theta > 0.5 $ ), and the turbulence intensity in this stable stratification was obviously suppressed. However, for strong stable stratification, sporadic strong turbulence could also occur. -
The TKE upside-down phenomenon often appears in the NSBL. Sun et al. (2012) attributed this moderate turbulence generated for relatively low values of V as regime 3 where turbulence may correlate with the upside-down structure in the SBL. Different from the traditional nocturnal SBL characterized by the upward transport of turbulent energy (downside-up), the most prominent feature of upside-down SBL is that the turbulence momentum flux at the higher altitude associated with strong wind shear transports downward toward the surface (Mahrt, 1999). Three typical urban SBL structures were classified according to the vertical profile of TKE (Shi and Hu, 2020).
The selection of TKE threshold is very important for the division of three types of SBL and in our study this threshold TKE was determined based on the relationship between TKE and PM2.5 concentration. The TKE values were very small during heavy haze pollution days, basically less than 1 m2 s−2 (Han et al., 2018; Shi et al., 2019; Wang et al., 2019). At this time, the atmospheric diffusion capacity was poor and the vertical exchange of turbulence momentum between different layers was very weak (weak-transport). Previous study shows that when PM2.5 exceeded 75 μg m−3, reaching national pollution standards according to the Technical Specification for Air Quality Index (HJ633-2012), the TKE at three heights (47, 140 and 280 m) of the Beijing 325-m tower was basically less than 1m2 s−2, and during heavy pollution period, TKE was basically less than 0.5 m2 s−2. According to the three-month observation period in our study, statistical results show that when PM2.5 concentration exceeded 75 μg m−3, more than 80% of the TKE at 8 m was less than 0.5 m2 s−2. If the threshold TKE was 1 m2 s−2, the probability could exceed 80%, but the high TKE value may not be able to select a typical weak-transport type. Threshold TKE value 0.1 m2 s−2 conformed to a typical weak-transport, but observation results show that when the air quality reached the polluted level, TKE was not always less than 0.1 m2 s−2. Therefore, this paper selected 0.5 m2 s−2 as a threshold value, and a TKE less than 0.5 m2 s−2 in the whole tower layer was classified as a weak-transport type. The case in which the maximum TKE in the tower layer exceeded 0.5 m2 s−2 and the maximum value appeared at the highest layer (280 m) was divided into the upside-down type. Although this division included some non-typical cases, the occurrence of the maximum TKE at the highest layer still indicated a trend of higher TKE in the upper layer. The remaining cases were divided into the traditional urban SBL type (downside-up).
As shown in Fig. 6, in the urban SBL at night, the frequency of downside-up was highest; the probability of the weak-transport type was approximately 34%, and the upside-down type occurred the least, with a probability of approximately 16%. When an upside-down structure occurred, some moderate strength turbulence activities above 140 m (including 140 m) were observed when V<VT. This phenomenon was more obvious at higher heights, such as 200 and 280 m. Upside-down structures led to a significant enhancement of turbulence above the UCL, generating regime 3. However, the turbulence enhancement was not obvious below the UCL height.
Figure 6. The relationship between the turbulence strength VTKE and the wind speed V at (a) 80 m, (b) 140 m, (c) 200 m, and (d) 280 m. The red, green and blue circles represent three kinds of stable boundary layers according to the vertical profile of TKE: weak transport, upside-down and downside-up, respectively. The three patterns were classified according to the vertical profiles of TKE.
The horizontal TKE and vertical TKE were also compared. As shown in Fig. 7, the horizontal TKE was always considerably higher than the vertical TKE component, especially at 280 m, indicating that the atmospheric turbulence in the urban SBL was always anisotropic. The magnitude of the horizontal TKE increased significantly above 80 m for the upside-down structures; therefore, the upside-down structures had a higher downward transmission efficiency of the horizontal TKE than the vertical TKE.
Figure 7. The relationship between the horizontal TKE
$(\overline{{u}^{'2}}+\overline{{v}^{{'}2}})/2$ and vertical TKE$\overline{{w}^{{'}2}}/2$ at (a) 15 m, (b) 47 m, (c) 80 m, (d) 140 m, (e) 200 m, and (f) 280 m. The red, green and blue circles represent three kinds of stable boundary layers according to the vertical profile of TKE: weak transport, upside-down and downside-up, respectively. The three patterns were classified according to the vertical profiles of TKE.Based on the above analysis, we can infer the schematic representation VTKE vs. V applicable to the UBL. For the layers above the UCL, or more accurately, the layers having little influence from the thermodynamic properties of the urban canopy, VTKE vs. V is consistent with the HOST theory proposed by Sun et al. (2012) based on the flat underlying surface (Fig. 8a). Local shear plays a leading role when V<VT (regime 1); strong turbulence is mainly driven by the bulk shear when V>VT (regime 2); and small wind speed accompanied by moderate turbulence intensity, i.e., upside-down structure (regime 3).
Figure 8. Schematic representation of the relationship between the turbulence strength VTKE and the wind speed V with the four turbulence regimes (regimes 1, 2, 3, and 4) for the Beijing 325-m meteorological tower, located at a typical city underlying surface. (a) 140 m, 200 m, and 280 m; and (b) 8 m, 15 m, 47 m, and 80 m. The urban canopy height of the observation site is estimated to be approximately 80 m. Turbulence in regime 1 is mainly generated by local instability. Turbulence in regime 2 is mainly generated by bulk shear. Turbulence in regime 3 is mainly generated by upside-down turbulence flows. Turbulence in regime 4 is generated by buoyancy turbulence flows.
The schematic representation in Fig. 8b is more appropriate for heights within the UCL. The UCL height near Beijing 325-m meteorological tower in this paper was approximately 47 m. Fig. 8b shows the characteristics of VTKE vs. V at 8, 15, 47 and 80 m. The influence of local wind shear in the canopy was strongest, and the relationship of VTKE vs. V was much closer when V<VT (regime 1). As for the strong turbulence activities when V>VT, the generation of strong turbulence is the result of a combination of local wind shear (regime 1), bulk shear (regime 2), and anthropogenic heat (regime 4).
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The current study investigated the relationship between different turbulence regimes and the evolution of the concentration of pollutants. Figure 9 shows the time series of the concentration of the ground PM2.5 at the OSCS station from 1130 LST Jan 15 to 1130 LST January 16 as well as the corresponding SBL types. Figure 9 also demonstrates the variation in skewness-w.
Figure 9. The time series of the skewness of the vertical velocity at 8 m, 15 m, 200 m and 280 m and the concentration of PM2.5 from 1130 LST on 15 January 2018 to 1130 LST on 16 January 2018. The variation process is marked by different circle colors, representing the different boundary layer structures.
We selected 8, 15, 200 and 280 m within the tower observation layer. Figure 9 shows that skewness-w had a stratification influence behavior. Specifically, the skewness-w values of 8 and 15 m in the lower layer tended to be negative, and the turbulence exchange process was mainly affected by the sweep process. By contrast, the skewness-w at the upper layers of 200 and 280 m remained positive, demonstrating that the turbulence exchange process was mainly dominated by the ejection process and that the diurnal variation in skewness-w was not significant.
Due to the occurrence of the upside-down structure, the positive skewness-w of 200 and 280 m in the upper layer gradually decreased and gradually approached the value of the lower layer or even decreased to a negative value, indicating that the turbulence exchange process in the upper layer gradually changed from ejection to sweep.
The relationship between the SBL structure and the concentration of pollutants was not very obvious, as shown in Fig. 9. Theoretically, weak-transport is regarded as favorable to the accumulation of pollutants. The sweep exchange process is more conducive to the removal of pollutants; therefore, the decreasing trend of the concentration of pollutants often correlates with the emergence of an upside-down structure.
Figure 10 further shows the vertical distribution of V, potential temperature and TKE of the three SBLs: 2130 LST on Jan 15 was weak-transport, 2200 LST on Jan 15 was downside-up, and 0100 LST on Jan 16 and 0130 LST on Jan 16 were upside-down structures. From 2130 LST on 15 Jan to 0130 LST on 16 Jan, although the potential temperature near the ground was not the lowest, the stability of the lower atmosphere still deepened. For the wind profile, the V in the lower canopy was significantly reduced due to the blocking effects of the buildings within the UCL. The wind profile for the upside-down structure became more irregular and obviously did not conform to the logarithmic law.
Figure 10. Typical vertical profiles of wind speed (V), potential temperature and turbulence kinetic energy (TKE) at 2130 LST on 15 January 2018 for weak transport, 2200 LST on 15 January 2018 for downside-up, 0100 LST on 16 January 2018 and 0130 LST on 16 January 2018 for upside-down structures.
The evolution of V and vertical wind speed w clearly demonstrated the transformation between different turbulence regimes (Fig. 11). The data shown were the 30 s temporal average from sonic anemometers with a frequency of 10 Hz. From 2130 LST to 2200 LST on 15 Jan, the V of the whole tower layer became very small, almost less than 2 m s−1. The turbulence of the tower layer belonged to regime 1, and at this time, the concentration of ground PM2.5 gradually increased, and the skewness-w at 8 and 15 m gradually decreased (shown in Fig. 9). At approximately 2230 LST on 15 Jan, except for the relatively small V in the lower layer of the tower, V increased significantly, and V within the tower layer was relatively uniform. When V gradually increased, w also changed simultaneously, and the absolute value of the vertical velocity
$ \left|w\right| $ increased. The turbulence regime has mainly evolved into regime 2.Figure 11. The time series of the wind speed V and the vertical velocity w for the seven observation levels from 2000 LST on 15 January 2018 to 0200 LST on 16 January 2018. For vertical velocity w starting from 15 m, the value is shifted by the amount shown to the right of each time series. The data shown are the 30 s temporal average from sonic anemometers with a frequency of 10 Hz.
Generally, the decrease in V, an increase in the variability of w with height, and negative value of the skewness-w indicated the downward transport of TKE (Mahrt and Vickers, 2002; Yus-Díez et al., 2019). At approximately 0030 LST on 16 Jan, the skewness-w at 280 m decreased, changing to a negative value, and the skewness-w at 15 m was also a negative value (Fig. 9). The variation amplitude in w increased with height (Fig. 11b), and this maximum w propagated downward to lower levels with time. However, at this time, the variation in the V of each layer changed sharply, and the upside-down structure in the UBL was affected by the UCL.
From 0100 LST to 0120 LST on 16 Jan, tower observation data show that V at 200 and 280 m decreased rapidly, and V in the lower layer did not change greatly; the variability of w at 80, 140, 200 and 280 m was significantly greater than that in the lower layers at 8, 15, and 47 m. The skewness-w at 280 m changed to a negative value. Although skewness-w was not negative at 200 m, its absolute value also decreased significantly. Figure 10 shows that within the tower layer at this time, TKE gradually increased with height, indicating an obvious upside-down structure.
Figure 12 shows the power spectra of w at 2100 LST on 15 Jan 2018, 2200 LST on 15 Jan 2018 and 0000 LST on 16 Jan 2018, representing the power spectra distribution for weak-transport, downside-up and upside-down structures, respectively. The power spectra of w for three stages mainly satisfied the “–2/3” power law in the inertial subrange. At 2200 LST on 15 Jan 2018, when TKE was transmitted upward from the UCL during strong wind, the power spectra of w in the inertial subrange were more consistent. When an upside-down structure occurred (Fig. 12c), the spectral density at a low-frequency increased, suggesting the influence of the large-scale motions. However, overall, the w spectra had no prominent peak at lower frequencies, revealing that the large-scale motions were essentially horizontal near the ground (Li et al., 2007). Compared to that from flat terrain, the w spectrum showed an obvious power deficit at intermediate frequencies near the spectral peak, a feature that has been reported for spectra over complex terrain (Gallagher et al., 1988).
Figure 12. Power spectra of the w wind component at weak transport at 2100 LST on 15 January 2018 (a), downside-up at 2200 LST on 15 January 2018 (b), and upside-down at 0000 LST on 16 January 2018 (c). A 1-h data segment is used at each observation height in both panels.
We further analyzed the corresponding vertical distribution of the stability parameters of different SBLs (seen in Table 2). To make the results more obvious, stable (S), near-neutral (N) and unstable (U) refer to the z/Λ>0.1,
$ \left|z/\varLambda \right| $ <0.1, and z/Λ<–0.1 cases, respectively. The neutral cases occurred most frequently for downside-up because near-neutral stratification usually corresponded to windy days, and stronger winds were more often associated with neutral stratification. Weak-transport mostly corresponded to low wind days, and the occurrence probability of neutral stratification for weak-transport in each layer was smallest. The occurrence of stable stratification should be highest for weak transport, but this result was only available for the lower layer of the tower (8–47 m). The highest frequent stable stratification in the higher layer usually corresponded to the upside-down structure. The more stable stratification may lead to the decoupling between the lower layer and the layer above it; therefore, the mixing process between different layers was partially weakened. The momentum of the upper layer could not be transferred to the lower layer and then consumed, resulting in a relatively larger TKE in the upper layer.Height (m) 8 15 32 47 65 80 100 120 140 160 180 200 240 280 320 Meterological √ √ √ √ √ √ √ √ √ √ √ √ √ √ √ Turbulence √ √ √ √ √ √ √ Table 1. Instrument heights on the Beijing 325-m meteorological tower.
Height Downside-up Weak transport Upside-down S N U S N U S N U 8 m 35.6 62.2 2.2 72.4 16.1 11.5 62.1 31.8 6.1 15 m 39.8 57.0 3.2 70.7 14.2 15.1 62.2 27.5 10.3 47 m 29.0 57.6 13.4 51.7 8.1 40.2 47.9 30.2 21.9 80 m 29.0 52.1 18.9 44.0 8.5 47.5 50.1 26.6 23.3 140 m 38.4 30.1 31.5 46.2 3.2 50.6 56.0 15.7 28.3 200 m 61.4 14.2 24.4 53.5 2.0 44.5 70.0 7.0 23.0 280 m 63.7 10.3 26.0 52.4 1.7 45.9 67.3 7.3 25.4 Table 2. The distribution of the frequency (%) for stable (S, z/Λ>0.1), near-neutral (N,
$\left|z/\varLambda \right|$ <0.1) and unstable (U, z/Λ<–0.1) cases of the nighttime downside-up, upside-down, weak-transport cases from November 2017 to January 2018 observed by the 325-m tower.
Height (m) | |||||||||||||||
8 | 15 | 32 | 47 | 65 | 80 | 100 | 120 | 140 | 160 | 180 | 200 | 240 | 280 | 320 | |
Meterological | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ |
Turbulence | √ | √ | √ | √ | √ | √ | √ |