Relationship analysis of PM&lt;sub&gt;2.5&lt;/sub&gt; and boundary layer height using an aerosol and turbulence detection lidar

Abstract. The atmospheric boundary layer height (BLH) is a key parameter in weather forecasting and air quality prediction. To investigate the relationship between BLH and air pollution under different conditions, a compact micro-pulse lidar integrating both direct-detection lidar (DDL) and coherent Doppler wind lidar (CDWL) has been built. This hybrid lidar is operated at 1.5 µm, which is eye-safe and made of all-fibre components. The BLH can be determined from aerosol density and vertical wind independently. During a 45 h continuous observation in June 2018, the stable boundary layer, residual layer and convective boundary layer are identified. The fine structure of the aerosol layers, drizzles and vertical wind near the cloud base are also detected. In comparison, the standard deviation between BLH values derived from DDL and CDWL is 0.06 km, indicating the accuracy of this work. The retrieved convective BLH is a little higher than that from ERA5 reanalysis due to different retrieval methods. Correlation between different BLH and PM2.5 is strongly negative before a precipitation event and becomes much weaker after the precipitation. Different relationships between PM2.5 and BLH may result from different BLH retrieval methods, pollutant sources and meteorological conditions.

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Convective Boundary Layer Height Measurement with Wind Profilers and Comparison to Cloud Base

Journal of Atmospheric and Oceanic Technology ◽

10.1175/1520-0426(1998)015<1331:cblhmw>2.0.co;2 ◽

1998 ◽

Vol 15 (6) ◽

pp. 1331-1338 ◽

Cited By ~ 51

Author(s):

Alison W. Grimsdell ◽

Wayne M. Angevine

Keyword(s):

Boundary Layer ◽

Convective Boundary Layer ◽

Cloud Base ◽

Height Measurement ◽

Convective Boundary ◽

Layer Height ◽

Boundary Layer Height ◽

Wind Profilers

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Relationship Analysis of PM<sub>2.5</sub> and BLH using Aerosol and Turbulence Detection Lidar

10.5194/amt-2018-406 ◽

2019 ◽

Author(s):

Chong Wang ◽

Mingjiao Jia ◽

Haiyun Xia ◽

Yunbin Wu ◽

Tianwen Wei ◽

...

Keyword(s):

Boundary Layer ◽

Convective Boundary Layer ◽

Direct Detection ◽

Weather Forecast ◽

Residual Layer ◽

Vertical Wind ◽

Convective Boundary ◽

Relationship Analysis ◽

Air Quality Prediction ◽

The Relationship

Abstract. The atmospheric boundary layer height (BLH) is a key parameter in weather forecast and air quality prediction. To investigate the relationship between BLH and air pollution under different conditions, a compact micro-pulse lidar integrated both direct detection lidar (DDL) and coherent Doppler wind lidar (CDWL) is built. Then the BLH can be determined from aerosol density or vertical wind independently. During a 45-hour continuous observation in June 2018, stable boundary layer, residual layer and convective boundary layer are identified. Fine structure of aerosol layers, drizzles and vertical wind near cloudbase are also detected. In comparison, the standard deviation between BLH values derived from DDL and CDWL is 60 m, indicating the accuracy of this work. The retrieved convective BLH is a little higher than that from ERA5 reanalysis due to different retrieval methods. Negative correlation between BLH and PM2.5 is analyzed before and after a precipitation. A criterion is proposed to classify the residual layer and convective boundary layer. Different trends show that the relationship between PM2.5 and BLH should be considered in different boundary layer categories.

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Assimilation of lidar planetary boundary layer height observations

10.5194/amt-2020-238 ◽

2020 ◽

Author(s):

Andrew Tangborn ◽

Belay Demoz ◽

Brian J. Carroll ◽

Joseph Santanello ◽

Jeffrey L. Anderson

Keyword(s):

Boundary Layer ◽

Planetary Boundary Layer ◽

Forecast Error ◽

State Variables ◽

Planetary Boundary Layer Height ◽

Error Statistics ◽

Convective Boundary ◽

Layer Height ◽

Late Afternoon ◽

Boundary Layer Height

Abstract. Lidar backscatter and wind retrievals of the planetary boundary layer height (PBLH) are assimilated into 22 hourly forecasts from the NASA Unified – Weather and Research Forecast (NU-WRF) model during the Plains Elevated Convection Convection at Night (PECAN) campaign on 11 July 2015 in Greensburg, Kansas, using error statistics collected from the model profiles to compute the necessary covariance matrices. Two separate forecast runs using different PBL physics schemes were employed, and comparisons with 5 independent sonde profiles were made for each run. Both of the forecast runs accurately predicted the PBLH and the state variable profiles within the planetary boundary layer during the early morning, and the assimilation had little impact during this time. In the late afternoon, the forecast runs showed decreased accuracy as the convective boundary layer developed. However, assimilation of the doppler lidar PBLH observations were found to improve the temperature, water vapor and velocity profiles relative to independent sonde profiles. The computed forecast error covariances between the PBLH and state variables were found to rise in the late afternoon, leading to the larger improvements in the afternoon. This work represents the first effort to assimilate PBLH into forecast states using ensemble methods.

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Assimilation of lidar planetary boundary layer height observations

Atmospheric Measurement Techniques ◽

10.5194/amt-14-1099-2021 ◽

2021 ◽

Vol 14 (2) ◽

pp. 1099-1110

Author(s):

Andrew Tangborn ◽

Belay Demoz ◽

Brian J. Carroll ◽

Joseph Santanello ◽

Jeffrey L. Anderson

Keyword(s):

Boundary Layer ◽

Planetary Boundary Layer ◽

Forecast Error ◽

State Variables ◽

Planetary Boundary Layer Height ◽

Error Statistics ◽

Convective Boundary ◽

Layer Height ◽

Late Afternoon ◽

Boundary Layer Height

Abstract. Lidar backscatter and wind retrievals of the planetary boundary layer height (PBLH) are assimilated into 22-hourly forecasts from the NASA Unified – Weather and Research Forecast (NU-WRF) model during the Plains Elevated Convection at Night (PECAN) campaign on 11 July 2015 in Greensburg, Kansas, using error statistics collected from the model profiles to compute the necessary covariance matrices. Two separate forecast runs using different PBL physics schemes were employed, and comparisons with six independent radiosonde profiles were made for each run. Both of the forecast runs accurately predicted the PBLH and the state variable profiles within the planetary boundary layer during the early morning, and the assimilation had a small impact during this time. In the late afternoon, the forecast runs showed decreased accuracy as the convective boundary layer developed. However, assimilation of the Doppler lidar PBLH observations was found to improve the temperature and V-velocity profiles relative to independent radiosonde profiles. Water vapor was overcorrected, leading to increased differences with independent data. Errors in the U velocity were made slightly larger. The computed forecast error covariances between the PBLH and state variables were found to rise in the late afternoon, leading to the larger improvements in the afternoon. This work represents the first effort to assimilate PBLH into forecast states using ensemble methods.

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Random Sample Fitting Method to Determine the Planetary Boundary Layer Height Using Satellite-Based Lidar Backscatter Profiles

Remote Sensing ◽

10.3390/rs12234006 ◽

2020 ◽

Vol 12 (23) ◽

pp. 4006

Author(s):

Lin Du ◽

Ya’ni Pan ◽

Wei Wang

Keyword(s):

Boundary Layer ◽

Random Sample ◽

Planetary Boundary Layer ◽

Weather Forecasting ◽

Cloud Layer ◽

Superior Performance ◽

Planetary Boundary Layer Height ◽

Layer Height ◽

Boundary Layer Height ◽

Fitting Method

The planetary boundary layer height (PBLH) is the atmospheric region closest to the earth’s surface and has important implications on weather forecasting, air quality, and climate research. However, lidar-based methods traditionally used to determine PBLH—such as the ideal profile fitting method (IPF), maximum gradient method, and wavelet covariance transform—are not only heavily influenced by cloud layers, but also rely heavily on a low signal-to-noise ratio (SNR). Therefore, a random sample fitting (RANSAF) method was proposed for PBLH detection based on combining the random sampling consensus and IPF methods. According to radiosonde measurements, the testing of simulated and satellite-based signals shows that the proposed RANSAF method can reduce the effects of the cloud layer and significantly fluctuating noise on lidar-based PBLH detection better than traditional algorithms. The low PBLH bias derived by the RANSAF method indicates that the improved algorithm has a superior performance in measuring PBLH under a low SNR or when a cloud layer exists where the traditional methods are mostly ineffective. The RANSAF method has the potential to determine regional PBLH on the basis of satellite-based lidar backscatter profiles.

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Atmosphere Boundary Layer Height (ABLH) Determination under Multiple-Layer Conditions Using Micro-Pulse Lidar

Remote Sensing ◽

10.3390/rs11030263 ◽

2019 ◽

Vol 11 (3) ◽

pp. 263 ◽

Cited By ~ 14

Author(s):

Ruijun Dang ◽

Yi Yang ◽

Hong Li ◽

Xiao-Ming Hu ◽

Zhiting Wang ◽

...

Keyword(s):

Boundary Layer ◽

Correlation Coefficient ◽

Cloud Layer ◽

Horizontal Wind ◽

Cloud Base ◽

Accurate Estimation ◽

Lidar Measurement ◽

Height Distribution ◽

Layer Height ◽

Boundary Layer Height

Accurate estimation of the atmospheric boundary layer height (ABLH) is critically important and it mainly relies on the detection of the vertical profiles of atmosphere variables (temperature, humidity,’ and horizontal wind speed) or aerosols. Aerosol Lidar is a powerful remote sensing instrument frequently used to retrieve ABLH through the detection of the vertical distribution of aerosol concentration. A challenge is that cloud, residual layer (RL), and local signal structure seriously interfere with the lidar measurement of ABLH. A new objective technique presenting as giving a top limiter altitude is introduced to reduce the interference of RL and cloud layer on ABLH determination. Cloud layers are identified by looking for the rapid increase and sharp attenuation of the signal combined with the relative increase in the signal. The cloud layers weather overlay are classified or are decoupled from the ABL by analyzing the continuity of the signal below the cloud base. For cloud layer capping of the ABL, the limiter is determined to be the altitude where a positive signal gradient first occurs above the cloud upper edge. For a cloud that is decoupled from the ABL, the cloud base is considered to be the altitude limiter. For RL in the morning, the altitude limiter is the greatest positive gradient altitude below the RL top. The ABLH will be determined below the top limiter altitude using Haar wavelet (HM) and the curve fitting method (CFM). Besides, the interference of local signal noise is eliminated through consideration of the temporal continuity. While comparing the lidar-determined ABLH by HM (or CFM) and nearby radiosonde measurements of the ABLH, a reasonable concordance is found with a correlation coefficient of 0.94 (or 0.96) and 0.79 (or 0.74), presenting a mean of the relative absolute differences with respect to radiosonde measurements of 10.5% (or 12.3%) and 22.3% (or 17.2%) for cloud-free and cloudy situations, respectively. The diurnal variations in the ABLH determined from HM and CFM on four selected cases show good agreement with a mean correlation coefficient higher than 0.99 and a mean absolute bias of 0.22 km. Also, the determined diurnal ABLH are consistent with surface turbulent kinetic energy (TKE) combined with the time-height distribution of the equivalent potential temperature.

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Turbulent and boundary layer characteristics during VOCALS-REx

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-1937-2021 ◽

2021 ◽

Vol 21 (3) ◽

pp. 1937-1961

Author(s):

Dillon S. Dodson ◽

Jennifer D. Small Griswold

Keyword(s):

Boundary Layer ◽

Heat Flux ◽

Kinetic Energy ◽

Turbulent Kinetic Energy ◽

Sensible Heat Flux ◽

Cloud Layer ◽

Cloud Base ◽

Layer Height ◽

Boundary Layer Height ◽

Turbulent Characteristics

Abstract. Boundary layer and turbulent characteristics (surface fluxes, turbulent kinetic energy – TKE, turbulent kinetic energy dissipation rate – ϵ), along with synoptic-scale changes in these properties over time, are examined using data collected from 18 research flights made with the CIRPAS Twin Otter Aircraft. Data were collected during the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) at Point Alpha (20∘ S, 72∘ W) in October and November 2008 off the coast of South America. The average boundary layer depth is found to be 1148 m, with 28 % of the boundary layer profiles analyzed displaying decoupling. Analysis of correlation coefficients indicates that as atmospheric pressure decreases, the boundary layer height (zi) increases. As has been shown previously, the increase in zi is accompanied by a decrease in turbulence within the boundary layer. As zi increases, cooling near cloud top cannot sustain mixing over the entire depth of the boundary layer, resulting in less turbulence and boundary layer decoupling. As the latent heat flux (LHF) and sensible heat flux (SHF) increase, zi increases, along with the cloud thickness decreasing with increasing LHF. This suggests that an enhanced LHF results in enhanced entrainment, which acts to thin the cloud layer while deepening the boundary layer. A maximum in TKE on 1 November (both overall average and largest single value measured) is due to sub-cloud precipitation acting to destabilize the sub-cloud layer while acting to stabilize the cloud layer (through evaporation occurring away from the surface, primarily confined between a normalized boundary layer height, z/zi, of 0.40 to 0.60). Enhanced moisture above cloud top from a passing synoptic system also acts to reduce cloud-top cooling, reducing the potential for mixing of the cloud layer. This is observed in both the vertical profiles of the TKE and ϵ, in which it is found that the distributions of turbulence for the sub-cloud and in-cloud layer are completely offset from one another (i.e., the range of turbulent values measured have slight or no overlap for the in-cloud and sub-cloud regions), with the TKE in the sub-cloud layer maximizing for the analysis period, while the TKE in the in-cloud layer is below the average in-cloud value for the analysis period. Measures of vertical velocity variance, TKE, and the buoyancy flux averaged over all 18 flights display a maximum near cloud middle (between normalized in-cloud height, Z*, values of 0.25 and 0.75). A total of 10 of the 18 flights display two peaks in TKE within the cloud layer, one near cloud base and another near cloud top, signifying evaporative and radiational cooling near cloud top and latent heating near cloud base. Decoupled boundary layers tend to have a maximum in turbulence in the sub-cloud layer, with only a single peak in turbulence within the cloud layer.

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Evaluation of convective boundary layer height estimates using radars operating at different frequency bands

Atmospheric Measurement Techniques ◽

10.5194/amt-14-7341-2021 ◽

2021 ◽

Vol 14 (11) ◽

pp. 7341-7353

Author(s):

Anna Franck ◽

Dmitri Moisseev ◽

Ville Vakkari ◽

Matti Leskinen ◽

Janne Lampilahti ◽

...

Keyword(s):

Boundary Layer ◽

Potential Temperature ◽

Convective Boundary ◽

Data Set ◽

Layer Height ◽

Frequency Bands ◽

Boundary Layer Height ◽

W Band ◽

Water Vapour Concentration ◽

5 Ghz

Abstract. Knowledge of the atmospheric boundary layer state and evolution is important for understanding air pollution and low-level cloud development, among other things. There are a number of instruments and methods that are currently used to estimate boundary layer height (BLH). However, no single instrument is capable of providing BLH measurements in all weather conditions. We proposed a method to derive a daytime convective BLH using clear air echoes in radar observations and investigated the consistency of these retrievals between different radar frequencies. We utilized data from three vertically pointing radars that are available at the SMEAR II station in Finland, i.e. the C band (5 GHz), Ka band (35 GHz) and W band (94 GHz). The Ka- or W-band cloud radars are an integral part of cloud profiling stations of pan-European Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS). Our method will be utilized at ACTRIS stations to serve as an additional estimate of the BLH during summer months. During this period, insects and Bragg scatter are often responsible for clear air echoes recorded by weather and cloud radars. To retrieve a BLH, we suggested a mechanism to separate passive and independently flying insects that works for all analysed frequency bands. At the lower frequency (the C band) insect scattering has been separated from Bragg scattering using a combination of the radar reflectivity factor and linear depolarization ratio. Retrieved values of the BLH from all radars are in a good agreement when compared to the BLH obtained with the co-located HALO Doppler lidar and ERA5 reanalysis data set. Our method showed some underestimation of the BLH after nighttime heavy precipitation yet demonstrated a potential to serve as a reliable method to obtain a BLH during clear-sky days. Additionally, the entrainment zone was observed by the C-band radar above the CBL in the form of a Bragg scatter layer. Aircraft observations of vertical profiles of potential temperature and water vapour concentration, collected in the vicinity of the radar, demonstrated some agreement with the Bragg scatter layer.

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Evaluation of convective boundary layer height estimates using radars operating at different frequency bands

10.5194/amt-2021-142 ◽

2021 ◽

Author(s):

Anna Franck ◽

Dmitri Moisseev ◽

Ville Vakkari ◽

Matti Leskinen ◽

Janne Lampilahti ◽

...

Keyword(s):

Boundary Layer ◽

Potential Temperature ◽

Night Time ◽

Convective Boundary ◽

Reanalysis Dataset ◽

Layer Height ◽

Frequency Bands ◽

Boundary Layer Height ◽

W Band ◽

5 Ghz

Abstract. Knowledge of atmospheric boundary layer state and evolution is important for understanding air pollution and low level cloud development, among other things. There are a number of instruments and methods that are currently used to estimate boundary layer height (BLH). However, no single instrument is capable of providing BLH measurements in all weather conditions. We proposed a method to derive a daytime convective BLH using radar observations and investigated the consistency of these retrievals between different radars. We utilized data from three vertically-pointing radars that are available at the measurement station in Southern Finland: the C-band (5 GHz), Ka-band (35 GHz) and W-band (94 GHz). The Ka- or W- band cloud radars are an integral part of cloud profiling stations of pan-European Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS). Our method will be utilized at ACTRIS stations to serve as an additional estimate of the BLH during summer months. During this period, echoes from insects and Bragg scatter are often recorded by radars. To retrieve a BLH, we suggested a mechanism to separate small insects that follow air motion and independently flying insects that works for all analyzed frequency bands. At the lower frequency (the C-band) insect scattering was separated from Bragg scattering using a combination of radar reflectivity factor and linear depolarization ratio. Retrieved values of the BLH from all radars are in a good agreement when compared to the BLH obtained with the co-located lidar and reanalysis dataset. Our method showed some underestimation of the BLH after night-time heavy precipitation yet demonstrated a potential to serve as a reliable method to obtain a BLH during clear-sky days. Additionally, the entrainment zone was observed by the C-band radar above the CBL in a form of a Bragg scatter layer. Aircraft observations of vertical profiles of potential temperature and water vapor mixing ratio, collected in the vicinity of the radar, demonstrated some agreement with the Bragg scatter layer.

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