Detection by Space-Borne and Ground-Based Lidar Observations of Air Pollution on the Example of the Hefei Area

2022 ◽  
Author(s):  
H. Yang ◽  
Zh. Fang ◽  
X. Deng ◽  
Y. Cao ◽  
Ch. Xie
Keyword(s):  
Air Pollution ◽  
Ground Based Lidar ◽  
Lidar Observations

scholarly journals Assimilation of ground versus lidar observations for PM<sub>10</sub> forecasting

2013 ◽  
Vol 13 (1) ◽  
pp. 269-283 ◽  
Author(s):  
Y. Wang ◽  
K. N. Sartelet ◽  
M. Bocquet ◽  
P. Chazette
Keyword(s):  
Data Assimilation ◽  
Western Europe ◽  
Sensitivity Study ◽  
Optimal Interpolation ◽  
Temporal Influence ◽  
Potential Impact ◽  
Ground Based Lidar ◽  
Observing System Simulation Experiment ◽  
Lidar Observations ◽  
Do So

Abstract. This article investigates the potential impact of future ground-based lidar networks on analysis and short-term forecasts of particulate matter with a diameter smaller than 10 μm (PM10). To do so, an Observing System Simulation Experiment (OSSE) is built for PM10 data assimilation (DA) using optimal interpolation (OI) over Europe for one month from 15 July to 15 August 2001. First, using a lidar network with 12 stations and representing the "true" atmosphere by a simulation called "nature run", we estimate the efficiency of assimilating the lidar network measurements in improving PM10 concentration for analysis and forecast. It is compared to the efficiency of assimilating concentration measurements from the AirBase ground network, which includes about 500 stations in western Europe. It is found that assimilating the lidar observations decreases by about 54% the root mean square error (RMSE) of PM10 concentrations after 12 h of assimilation and during the first forecast day, against 59% for the assimilation of AirBase measurements. However, the assimilation of lidar observations leads to similar scores as AirBase's during the second forecast day. The RMSE of the second forecast day is improved on average over the summer month by 57% by the lidar DA, against 56% by the AirBase DA. Moreover, the spatial and temporal influence of the assimilation of lidar observations is larger and longer. The results show a potentially powerful impact of the future lidar networks. Secondly, since a lidar is a costly instrument, a sensitivity study on the number and location of required lidars is performed to help define an optimal lidar network for PM10 forecasts. With 12 lidar stations, an efficient network in improving PM10 forecast over Europe is obtained by regularly spacing the lidars. Data assimilation with a lidar network of 26 or 76 stations is compared to DA with the previously-used lidar network. During the first forecast day, the assimilation of 76 lidar stations' measurements leads to a better score (the RMSE decreased by about 65%) than AirBase's (the RMSE decreased by about 59%).

scholarly journals Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects

2018 ◽  
Vol 11 (3) ◽  
pp. 1639-1651 ◽  
Author(s):  
Simone Lolli ◽  
Fabio Madonna ◽  
Marco Rosoldi ◽  
James R. Campbell ◽  
Ellsworth J. Welton ◽  
...  
Keyword(s):  
Data Processing ◽  
Measurement Techniques ◽  
Cirrus Clouds ◽  
Lidar Measurement ◽  
Radiative Effect ◽  
Radiative Effects ◽  
Lidar Ratio ◽  
Ground Based Lidar ◽  
Processing Techniques ◽  
Lidar Observations

Abstract. In the past 2 decades, ground-based lidar networks have drastically increased in scope and relevance, thanks primarily to the advent of lidar observations from space and their need for validation. Lidar observations of aerosol and cloud geometrical, optical and microphysical atmospheric properties are subsequently used to evaluate their direct radiative effects on climate. However, the retrievals are strongly dependent on the lidar instrument measurement technique and subsequent data processing methodologies. In this paper, we evaluate the discrepancies between the use of Raman and elastic lidar measurement techniques and corresponding data processing methods for two aerosol layers in the free troposphere and for two cirrus clouds with different optical depths. Results show that the different lidar techniques are responsible for discrepancies in the model-derived direct radiative effects for biomass burning (0.05 W m−2 at surface and 0.007 W m−2 at top of the atmosphere) and dust aerosol layers (0.7 W m−2 at surface and 0.85 W m−2 at top of the atmosphere). Data processing is further responsible for discrepancies in both thin (0.55 W m−2 at surface and 2.7 W m−2 at top of the atmosphere) and opaque (7.7 W m−2 at surface and 11.8 W m−2 at top of the atmosphere) cirrus clouds. Direct radiative effect discrepancies can be attributed to the larger variability of the lidar ratio for aerosols (20–150 sr) than for clouds (20–35 sr). For this reason, the influence of the applied lidar technique plays a more fundamental role in aerosol monitoring because the lidar ratio must be retrieved with relatively high accuracy. In contrast, for cirrus clouds, with the lidar ratio being much less variable, the data processing is critical because smoothing it modifies the aerosol and cloud vertically resolved extinction profile that is used as input to compute direct radiative effect calculations.

scholarly journals Simultaneous observations of a Mesospheric Inversion Layer and turbulence during the ECOMA-2010 rocket campaign

2013 ◽  
Vol 31 (5) ◽  
pp. 775-785 ◽  
Author(s):  
A. Szewczyk ◽  
B. Strelnikov ◽  
M. Rapp ◽  
I. Strelnikova ◽  
G. Baumgarten ◽  
...  
Keyword(s):  
Energy Dissipation ◽  
Inversion Layer ◽  
Turbulent Energy ◽  
Northern Norway ◽  
Rocket Launch ◽  
Air Turbulence ◽  
Measurement Results ◽  
Ground Based Lidar ◽  
Lidar Observations

Abstract. From 19 November to 19 December 2010 the fourth and final ECOMA rocket campaign was conducted at Andøya Rocket Range (69° N, 16° E) in northern Norway. We present and discuss measurement results obtained during the last rocket launch labelled ECOMA09 when simultaneous and true common volume in situ measurements of temperature and turbulence supported by ground-based lidar observations reveal two Mesospheric Inversion Layers (MIL) at heights between 71 and 73 km and between 86 and 89 km. Strong turbulence was measured in the region of the upper inversion layer, with the turbulent energy dissipation rates maximising at 2 W kg−1. This upper MIL was observed by the ALOMAR Weber Na lidar over the period of several hours. The spatial extension of this MIL as observed by the MLS instrument onboard AURA satellite was found to be more than two thousand kilometres. Our analysis suggests that both observed MILs could possibly have been produced by neutral air turbulence.

scholarly journals Assimilation of ground versus lidar observations for PM<sub>10</sub> forecasting

2012 ◽  
Vol 12 (9) ◽  
pp. 23291-23331
Author(s):  
Y. Wang ◽  
K. N. Sartelet ◽  
M. Bocquet ◽  
P. Chazette
Keyword(s):  
Western Europe ◽  
Sensitivity Study ◽  
Optimal Interpolation ◽  
Short Term ◽  
Temporal Influence ◽  
Potential Impact ◽  
Ground Based Lidar ◽  
Observing System Simulation Experiment ◽  
Lidar Observations ◽  
Do So

Abstract. This article investigates the potential impact of future ground-based lidar networks on analysis and short-term forecasts of particulate matter with a diameter smaller than 10 μg m−3 (PM10). To do so, an Observing System Simulation Experiment (OSSE) is built for PM10 data assimilation (DA) using optimal interpolation (OI) over Europe for one month in 2001. First, using a lidar network with 12 stations, we estimate the efficiency of assimilating the lidar network measurements in improving PM10 concentration analysis and forecast. It is compared to the efficiency of assimilating concentration measurements from the AirBase ground network, which includes about 500 stations in Western Europe. It is found that assimilating the lidar observations decreases by about 54% the root mean square error (RMSE) of PM10 concentrations after 12 h of assimilation and during the first forecast day, against 59% for the assimilation of AirBase measurements. However, the assimilation of lidar observations leads to similar scores as AirBase's during the second forecast day. The RMSE of the second forecast day is improved on average over the summer month by 57% by the lidar DA, against 56% by the AirBase DA. Moreover, the spatial and temporal influence of the assimilation of lidar observations is larger and longer. The results show a potentially powerful impact of the future lidar networks. Secondly, since a lidar is a costly instrument, a sensitivity study on the number and location of required lidars is performed to help defining an optimal lidar network for PM10 forecast. With 12 lidar stations, an efficient network in improving PM10 forecast over Europe is obtained by regularly spacing the lidars. DA with a lidar network of 26 or 76 stations is compared to DA with the previously-used lidar network. The assimilation of 76 lidar stations' measurements leads to a better score than AirBase's during the forecast days.

Comparison of polar stratospheric cloud detection and composition as observed by ground-based lidar and CALIOP at Dome C.

2021 ◽  
Author(s):  
Marcel Snels ◽  
Francesco Colao ◽  
Francesco Cairo ◽  
Ilir Shuli ◽  
Andrea Scoccione ◽  
...  
Keyword(s):  
Data Analysis ◽  
Detection Efficiency ◽  
Cloud Detection ◽  
Polar Stratospheric Cloud ◽  
Ground Based Lidar ◽  
Stratospheric Clouds ◽  
Observation Geometry ◽  
The Impact ◽  
Lidar Observations

&lt;p&gt;Polar stratospheric clouds have been observed at Dome C by a ground-based lidar from 2014 up to the present, possibly in coincidence with nearby overpasses of the CALIPSO satellite, with the CALIOP lidar on board.&lt;/p&gt;&lt;p&gt;A thorough study has been made in terms of detection efficiency and composition classification of near coincident lidar observations, with the goal to identify the main biases between the two lidars.&lt;/p&gt;&lt;p&gt;When comparing ground-based lidar observations with nearby CALIOP overpasses, several biases might occur, due to the distance between ground-based lidar and nearest overpass, observation geometry and integration times and different algorithms used for data analysis.&lt;/p&gt;&lt;p&gt;The bias resulting from different data analysis has been reduced by applying an algorithm for PSC detection and composition classification to the ground-based data which is very similar to the V2 algorithm used for CALIOP.&lt;/p&gt;&lt;p&gt;By comparing 5 years of PSC observations at Dome C, considering both detection efficiency and composition of the observed PSCs, the impact of all biases will be discussed and possibly quantified.&amp;#160;&lt;/p&gt;

On the best locations for ground-based PSC observations

2021 ◽  
Author(s):  
Matthias Tesche ◽  
Peggy Achtert ◽  
Michael Pitts
Keyword(s):  
Signal To Noise Ratio ◽  
The Arctic ◽  
Orthogonal Polarization ◽  
Microphysical Properties ◽  
Inhibiting Factors ◽  
Comprehensive Picture ◽  
Ground Based Lidar ◽  
Stratospheric Clouds ◽  
The Antarctic ◽  
Lidar Observations

&lt;p&gt;Spaceborne observations of Polar Stratospheric Clouds (PSCs) with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite provide a comprehensive picture of the occurrence of Arctic and Antarctic PSCs as well as their microphysical properties. However, advances in understanding PSC microphysics also require measurements with ground-based instruments, which are often superior to CALIOP in terms of, e.g. time resolution, measured parameters, and signal-to-noise ratio. This advantage is balanced by the location of ground-based PSC observations and their dependence on tropospheric cloudiness. CALIPSO observations during the boreal winters from December 2006 to February 2018 and the austral winters 2012 and 2015 are used to assess the effect of tropospheric cloudiness and other measurement-inhibiting factors on the representativeness of ground-based PSC observations with lidar in the Arctic and Antarctic, respectively. Information on tropospheric and stratospheric clouds from the CALIPSO Cloud Profile product (05kmCPro version 4.10) and the PSC mask version 2, respectively, is combined on a profile-by-profile basis to identify conditions under which a ground-based lidar is likely to perform useful measurements for the analysis of PSC occurrence. It is found that the location of a ground-based measurement together with the related tropospheric cloudiness can have a profound impact on the derived PSC statistics and that these findings are rarely in agreement with polar-wide results from CALIOP observations. Considering the current polar research infrastructure, it is concluded that the most suitable sites for the expansion of capabilities for ground-based lidar observations of PSCs are Summit and Villum in the Arctic and Mawson, Troll, and Vostok in the Antarctic.&lt;/p&gt;

scholarly journals The structure of the haze plume over the Indian Ocean during INDOEX: tracer simulations and LIDAR observations

2006 ◽  
Vol 6 (4) ◽  
pp. 907-923 ◽  
Author(s):  
G. Forêt ◽  
C. Flamant ◽  
S. Cautenet ◽  
J. Pelon ◽  
F. Minvielle ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Indian Ocean ◽  
Arabian Sea ◽  
Vertical Structure ◽  
Atmospheric Modeling ◽  
Airborne Lidar ◽  
Layer Depth ◽  
The Indian Ocean ◽  
Ground Based Lidar ◽  
Lidar Observations

Abstract. Three-dimensional, nested tracer simulations of a pollution plume originating from the Indian sub-continent over the Indian Ocean, in the framework of the Indian Ocean Experiment (INDOEX), between 5 and 9 March 1999, were performed with the Regional Atmospheric Modeling System (RAMS), to provide insight into the transport patterns of the pollutants, as well as to investigate the dynamical mechanisms controlling the vertical structure of the plume and its evolution in the vicinity of the Maldives Islands. Airborne and ground-based LIDAR observations of the structure of the haze plume made on 7 March 1999 were used to assess the quality of the simulations, as well as the impact of grid resolution on the vertical structure of the simulated plume. It is shown that, over the Arabian Sea, in the vicinity of the Maldives Islands, the pollutants composing the plume observed by the airborne LIDAR essentially originated from the city of Madras and that the vertical structure of the plume was controlled by the diurnal cycle of the continental boundary layer depth. A combination of tracer simulations and remote sensing observations (airborne LIDAR, ship-borne photometer, ground-based LIDAR in Goa) was used to analyse the diurnal evolution of the haze plume over the sea. We find evidence that the sea breeze circulation and orographic lifting taking place in the southern part of the Indian sub-continent during the daytime play a crucial role in the modulation of the continental boundary layer depth, and in turn, the haze plume depth. The eastward shift of the subtropical high from central India to the Bay of Bengal after 6 March lead to an increase in the tracer concentrations simulated over the Arabian Sea, in the region of intensive observations north of the Maldives, as transport pathways form Hyderabad and Madras were modified significantly. The nesting of a high horizontal resolution domain (5 km, with 39 vertical levels below 4000 m above mean seal level) allows for a better representation of local dynamics, the circulation of sea and mountains breezes, and therefore a noticeable improvement in the representation of the pollutants' plume in the simulation.

scholarly journals Location controls the findings of ground-based PSC observations

2020 ◽  
Author(s):  
Matthias Tesche ◽  
Peggy Achtert ◽  
Michael C. Pitts
Keyword(s):  
Signal To Noise Ratio ◽  
The Arctic ◽  
Orthogonal Polarization ◽  
Microphysical Properties ◽  
Polar Stratospheric Cloud ◽  
Comprehensive Picture ◽  
Ground Based Lidar ◽  
Stratospheric Clouds ◽  
The Antarctic ◽  
Lidar Observations

Abstract. Spaceborne observations of Polar Stratospheric Clouds (PSCs) with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite provide a comprehensive picture of the occurrence of Arctic and Antarctic PSCs as well as their microphysical properties. However, advances in understanding PSC microphysics also require measurements with ground-based instruments, which are often superior to CALIOP in terms of, e.g. time resolution, measured parameters, and signal-to-noise ratio. This advantage is balanced by the location of ground-based PSC observations and their dependence on tropospheric cloudiness. CALIPSO observations during the boreal winters from December 2006 to February 2018 and the austral winters 2012 and 2015 are used to assess the representativeness of ground-based PSC observations with lidar in the Arctic and Antarctic, respectively. Information on tropospheric and stratospheric clouds from the CALIPSO Cloud Profile product (05kmCPro version 4.10) and the Polar Stratospheric Cloud (PSC) mask version 2, respectively, is combined on a profile-by-profile basis to identify conditions under which a ground-based lidar is likely to perform useful measurements for the analysis of PSC occurrence. It is found that the location of a ground-based measurement together with the related tropospheric cloudiness can have a profound impact on the derived PSC statistics and that these findings are rarely in agreement with polar-wide results from CALIOP observations. Considering the current polar research infrastructure, it is concluded that the most suitable sites for the expansion of capabilities for ground-based lidar observations of PSCs are Summit and Villum in the Arctic and Concordia, Troll, and Vostok in the Antarctic.

scholarly journals First validation of GOME-2/MetOp absorbing aerosol height using EARLINET lidar observations

2021 ◽  
Vol 21 (4) ◽  
pp. 3193-3213
Author(s):  
Konstantinos Michailidis ◽  
Maria-Elissavet Koukouli ◽  
Nikolaos Siomos ◽  
Dimitris Balis ◽  
Olaf Tuinder ◽  
...  
Keyword(s):  
Saharan Dust ◽  
Aerosol Layer ◽  
Pixel Size ◽  
Geometrical Features ◽  
Depth Analysis ◽  
Satellite Sensors ◽  
The Mean ◽  
The Difference ◽  
Ground Based Lidar ◽  
Lidar Observations

Abstract. The aim of this study is to investigate the potential of the Global Ozone Monitoring Experiment-2 (GOME-2) instruments, aboard the Meteorological Operational (MetOp)-A, MetOp-B and MetOp-C satellite programme platforms, to deliver accurate geometrical features of lofted aerosol layers. For this purpose, we use archived ground-based lidar data from stations available from the European Aerosol Research Lidar Network (EARLINET) database. The data are post-processed using the wavelet covariance transform (WCT) method in order to extract geometrical features such as the planetary boundary layer (PBL) height and the cloud boundaries. To obtain a significant number of collocated and coincident GOME-2 – EARLINET cases for the period between January 2007 and September 2019, 13 lidar stations, distributed over different European latitudes, contributed to this validation. For the 172 carefully screened collocations, the mean bias was found to be −0.18 ± 1.68 km, with a near-Gaussian distribution. On a station basis, and with a couple of exceptions where very few collocations were found, their mean biases fall in the ± 1 km range with an associated standard deviation between 0.5 and 1.5 km. Considering the differences, mainly due to the temporal collocation and the difference, between the satellite pixel size and the point view of the ground-based observations, these results can be quite promising and demonstrate that stable and extended aerosol layers as captured by the satellite sensors are verified by the ground-based data. We further present an in-depth analysis of a strong and long-lasting Saharan dust intrusion over the Iberian Peninsula. We show that, for this well-developed and spatially well-spread aerosol layer, most GOME-2 retrievals fall within 1 km of the exact temporally collocated lidar observation for the entire range of 0 to 150 km radii. This finding further testifies for the capabilities of the MetOp-borne instruments to sense the atmospheric aerosol layer heights.

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