Estimation of the height of the turbulent mixing layer from data of Doppler lidar measurements using conical scanning by a probe beam

A method is proposed for determining the height of the turbulent mixing layer on the basis of the vertical profiles of the dissipation rate of turbulent energy, which is estimated from lidar measurements of the radial wind velocity using conical scanning by a probe beam around the vertical axis. The accuracy of the proposed method is discussed in detail. It is shown that for the estimation of the mixing layer height (MLH) with the acceptable relative error not exceeding 20 %, the signal-to-noise ratio should be no less than −16 dB, when the relative error of lidar estimation of the dissipation rate does not exceed 30 %. The method was tested in a 6 d experiment in which the wind velocity turbulence was estimated in smog conditions due to forest fires in Siberia in summer 2019. The results of the experiment reveal that the relative error of determination of the MLH time series obtained by this method does not exceed 10 % in the period of turbulence development. The estimates of the turbulent mixing layer height by the proposed method are in a qualitative agreement with the MLH estimated from the distributions of the Richardson number in height and time obtained during the comparison experiment in spring 2020.

Estimation of the height of turbulent mixing layer from data of Doppler lidar measurements using conical scanning by a probe beam

A method is proposed for determining the height of the turbulent mixing layer on the basis of the vertical profiles of the dissipation rate of turbulent energy, which is estimated from lidar measurements of the radial wind velocity using conical scanning by a probe beam around the vertical axis. The accuracy of the proposed method is discussed in detail. It is shown that for the estimation of the mixing layer height (MLH) with the acceptable relative error not exceeding 20 %, the signal-to-noise ratio should be no less than −16 dB, when the relative error of lidar estimation of the dissipation rate does not exceed 30 %. The method was tested in an experiment in which the wind velocity turbulence was estimated in smog conditions due to forest fires in Siberia in 2019. The results of the experiment reveal that the relative error of determination of the MLH time series obtained by this method does not exceed 10 % in the period of turbulence development. The estimates of the turbulent mixing layer height by the proposed method are in good agreement with the MLH estimated from the distributions of the variance of radial velocity and the Richardson number in height and time.

Determination and climatology of the diurnal cycle of the atmospheric mixing layer height over Beijing 2013–2018: lidar measurements and implications for air pollution

The atmospheric mixing layer height (MLH) determines the space in which pollutants diffuse and is thus conducive to the estimation of the pollutant concentration near the surface. The study evaluates the capability of lidar to describe the evolution of the atmospheric mixing layer and then presents a long-term observed climatology of the MLH diurnal cycle. Detection of the mixing layer heights (MLHL and MLHL′) using the wavelet method based on lidar observations was conducted from January 2013 to December 2018 in the Beijing urban area. The two dataset results are compared with radiosonde as case studies and statistical forms. MLHL shows good performance in calculating the convective layer height in the daytime and the residual layer height at night. While MLHL′ has the potential to describe the stable layer height at night, the performance is limited due to the high range gate of lidar. A nearly 6-year climatology for the diurnal cycle of the MLH is calculated for convective and stable conditions using the dataset of MLHL from lidar. The daily maximum MLHL characteristics of seasonal change in Beijing indicate that it is low in winter (1.404±0.751 km) and autumn (1.445±0.837 km) and high in spring (1.647±0.754 km) and summer (1.526±0.581 km). A significant phenomenon is found from 2014 to 2018: the magnitude of the diurnal cycle of MLHL increases year by year, with peak values of 1.291±0.646 km, 1.435±0.755 km, 1.577±0.739 km, 1.597±0.701 km and 1.629±0.751 km, respectively. It may partly benefit from the improvement of air quality. As to converting the column optical depth to surface pollution, the calculated PM2.5 using MLHL data from lidar shows better accuracy than that from radiosonde compared with observational PM2.5. Additionally, the accuracy of calculated PM2.5 using MLHL shows a diurnal cycle in the daytime, with the peak at 14:00 LST. The study provides a significant dataset of MLHL based on measurements and could be an effective reference for atmospheric models of surface air pollution calculation and analysis.

Detailed Assessment of the Effects of Meteorological Conditions on PM10 Concentrations in the Northeastern Part of the Czech Republic

This article assessed the links between PM10 pollution and meteorological conditions over the Czech-Polish border area at the Třinec-Kosmos and Věřňovice sites often burdened with high air pollution covering the years 2016–2019. For this purpose, the results of the measurements of special systems (ceilometers) that monitor the atmospheric boundary layer were used in the analysis. Meteorological conditions, including the mixing layer height (MLH), undoubtedly influence the air pollution level. Combinations of meteorological conditions and their influence on PM10 concentrations also vary, depending on the pollution sources of a certain area and the geographical conditions of the monitoring site. Gen1erally, the worst dispersion conditions for the PM10 air pollution level occur at low air temperatures, low wind speed, and low height of the mixing layer along with a wind direction from areas with a higher accumulation of pollution sources. The average PM10 concentrations at temperatures below 1 °C reach the highest values on the occurrence of a mixing layer height of up to 400 m at both sites. The influence of a rising height of the mixing layer at temperatures below 1 °C on the average PM10 concentrations at Třinec-Kosmos site is not as significant as in the case of Věřňovice, where a difference of several tens of µg·m−3 in the average PM10 concentrations was observed between levels of up to 200 m and levels of 200–300 m. The average PM10 hourly concentrations at Třinec-Kosmos were the highest at wind speeds of up to 0.5 m·s−1, at MLH levels of up to almost 600 m; at Věřňovice, the influence of wind speeds of up to 2 m·s−1 was detected. Despite the fact that the most frequent PM10 contributions come to the Třinec-Kosmos site from the SE direction, the average maximum concentration contributions come from the W–N sectors at low wind speeds and MLHs of up to 400 m. In Věřňovice, regardless of the prevailing SW wind direction, sources in the NE–E sector from the site have a crucial influence on the air pollution level caused by PM10.

On the spatial variability of the regional aerosol distribution as determined from ceilometers

Measurements of the vertical distribution of aerosol particles are typically only available at selected sites leaving the question of their representativeness for urban and regional scales unanswered. As a contribution to solve this problem we have investigated ceilometer signals from two testbeds in Munich and Berlin, Germany. For each testbed measurements of 24 months from 6 ceilometers were available. This constitutes a unique data set, in particular as the same type of instruments are deployed and the same data evaluation schemes applied. Two parameters are discussed: the mixing layer height (MLH) as an indicator for the vertical distribution and the integrated backscatter as a proxy for the amount of aerosols in the mixing layer. The MLH was determined by the COBOLT algorithm, the integrated backscatter from the Klett (backward and forward) inversion scheme. It was found that the mean difference of the MLH at two sites within a testbed typically only varies by less than 50 m, slightly increasing with the distance of the corresponding sites. Almost 60 % of all intercomparisons agree within ±100 m. MLHs are typically correlated with R > 0.9 in particular for the Berlin-testbed. With respect to the integrated backscatter the correlation is in the range of 0.7 < R < 0.9. This is expected from the diversity of local aerosol sources within a given testbed. We conclude from our data that the MLH determined from a single ceilometer is applicable for a whole metropolitan area. However, the integrated backscatter of particles within the mixing layer exhibits a variability of 15–25 % suggesting that one ceilometer is not representative, especially if atmospheric processes shall be investigated.

The interaction between urbanization and aerosols during the typical haze event

The interaction between aerosols and urbanization during the haze event was investigated using the Rapid-Refresh Multiscale Analysis and Prediction System-Short Term (RMAPS-ST). The mechanisms of the impacts of aerosols and urbanization were also analyzed and quantified. Aerosols reduce urban-related warming during the daytime, and the warming decreased by 30 to 50 % as the concentration of PM2.5 increased from 200 to 400 µg·m−3. Aerosols enhance the urban-related warming at dawn, with an increase of approximately 28 %, which is important for haze formation. Urbanization reduced the aerosol-related cooling effect by approximately 54 % during the haze event, and the strength of the impact changed little with increasing aerosol content. The impact of aerosols on urban-related warming is more significant than the impact of urbanization on aerosol-related cooling. Aerosols decreased the urban-impact on the mixing layer height by 148 % and on the sensible heat flux by 156 %. Furthermore, the aerosols decreased the latent heat flux, and the impact was reduced by 48.8 % by urbanization. The impact of urbanization on the transport of pollutants is more important than that of aerosols. The interaction between urbanization and aerosols may enhance the accumulation of pollution and weigh against diffusion.

Mesoscale variability of the aerosol distribution as determined from ceilometer measurements

&lt;p&gt;The spatial distribution of aerosol particles is relevant for studies on the radiation budget, for the verification of chemistry transport models, or for air quality studies just to name a few. As the distribution is highly variable the requirements to measurements are very demanding. As a consequence it is often assumed that the aerosol distribution is &quot;relatively homogeneous&quot;, i.e., measurements at one site are representative for a larger area.&lt;/p&gt;&lt;p&gt;By exploiting 2 years of measurements from 12 ceilometers located in the area of Munich and Berlin, Germany, we have investigated the spatial differences between locations separated between 3~km and 50~km. For this purpose we have used the mixing layer height (MLH), a quantity often used when the vertical aerosol distribution should be described by a single parameter. The MLH was determined by the COBOLT-algorithm (Gei&amp;#223; et al., 2017). It was found that the MLHs at different locations inside the two cities are highly correlated and agree within a few tens of meters. However, the maximum extension of the mixing layer from April to September was found to be significantly larger in Berlin compared to Munich.&lt;/p&gt;&lt;p&gt;&lt;br&gt;Gei&amp;#223;, A., Wiegner, M., Bonn, B., Sch&amp;#228;fer, K., Forkel, R., von Schneidemesser, E., M&amp;#252;nkel, C., Chan, K. L., and Nothard, R. (2017): Mixing layer height as an indicator for urban air quality?&amp;#160; Atmos. Meas. Tech., 10, 2969-2988, https://doi.org/10.5194/amt-10-2969-2017, 2017.&lt;/p&gt;