Compared with ground-based lidar, airborne lidar has a wider observation area, which is useful for studying aerosol distribution and transportation. A dual-wavelength high spectral resolution Lidar (HSRL) was developed for the validation and calibration of an upcoming satellite payload. The HSRL was installed on an airplane, and field campaigns were conducted in Qinhuangdao, China. Meanwhile, four observation sites were established at different locations on the ground to verify the results of the airborne lidar. This article compares the HSRL measurements with those from ground-based micro-pulse lidar (MPL), Mie-scattering lidar, sun photometer, and spaceborne cloud-aerosol Lidar and infrared pathfinder satellite observations (CALIPSO), and Moderate Resolution Imaging Spectroradiometer (MODIS). The stability and reliability of the HSRL system were fully verified. The flight area covered several surface types, including ocean, town, mountain, and forest, which strongly affect the AOD above them. The boundary layer AOD was analyzed in different regions, based on the impact of human activities. The results demonstrated that the AOD in urban area was the largest, and smallest in marine areas, a result ascribed to the influence of industrial activities.
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Aerosols play a key role in the Earth's radiation budget and can affect the radiation balance of the Earth–air system [1–5]. M. Gharibzad studied the radiative effects and optical properties of aerosol during two dust events, the high values of aerosol optical depth (AOD) and low values of Ångström exponent (AE) during dusty days illustrate that coarse mode particles like dust are dominant. The results show that dominant aerosol types are dust particles which have a cooling effect on the earth's surface during the study periods [6–7]. A. Bayat researched the relationship of polarized phase function, AE and single scattering albedo. The result show that polarized phase function has a strong positive correlation with AE, and polarized phase function has a negative correlation with single scattering albedo .
Lidar is considered one of the most powerful tools for detecting atmospheric aerosols . The high spectral resolution lidar (HSRL) are increasingly being developed for atmospheric aerosol remote sensing. HSRL is independent to calculate the aerosol extinction and backscatter coefficient without reliance on assumptions about lidar ratio [10–17]. In HSRL technique, spectral discrimination between scattering from molecules and aerosol particles is one of the most critical processes, which needs to be accomplished by means of a narrowband spectroscopic filter. Common narrowband filters include iodine molecular absorption cell filter, Fabry-Perot interferometer (FPI) and Mach-Zehnder interferometer (MZI), but these interferometric filters have the disadvantage of small acceptable field of view (FOV), thus the photon efficiency of the instrument is not so satisfactory . The NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL-2) was the first dual-wavelength HSRL system using field widened Michelson interferometer (FWMI) developed by Liu , which verified that multi-wavelength HSRL is a powerful tool for obtaining comprehensive atmospheric characteristics. A new type spectral discriminator for multiple-wavelength lidar is tested with a series of work about FWMI, which demonstrated its feasibility and stability and contributed to the development of multi-wavelength HSRL [18,20]. D. Liu et al.  developed a polarized HSRL based on FWMI in Zhejiang University, China, which is intended to profile various atmospheric aerosol optical properties simultaneously, such as the backscatter coefficient, the extinction coefficient, depolarization ratio, lidar ratio, etc. The HSRL system developed by Zhejiang University is the first new generation of lidar which employs the FWMI spectroscopic filter in China, and great potential will be shown with the gradually improved engineering design in near future.
Ground-based lidar can detect the vertical distribution and time variation characteristics of atmospheric aerosols and clouds. However, ground-based lidar can only measure them over a fixed position. Furthermore, there are still many problems regarding the consistency and comparability of the processing methods applied to ground-based lidar data. Compared with ground-based lidar, airborne lidar has high temporal resolution, high vertical resolution, and high measurement accuracy. It can detect the optical and morphological characteristics of atmospheric aerosols quickly and continuously in the experimental area, and obtain information about aerosols, clouds, and boundary layers . Airborne HSRL lidar can make direct measurements of aerosol intensive properties, including the lidar ratio, that provide information on aerosol type. From July 26 to August 14, 2006, McGil et al. conducted airborne verification experiments on the spatial characteristics of aerosols and clouds measured by the CALIPSO lidar. Their study demonstrated that the cloud top heights measured by the CALIPSO satellite and the heights measured by the airborne lidar CPL exhibited good consistency . In 2008, Esselborn et al. carried out an airborne lidar experiment using a high spectral resolution lidar based on iodine molecules and studied the optical characteristics of dust aerosols in the Sahara Desert. They compared the HSRL measurements with those from the ground-based Raman lidar and solar photometer and demonstrated good agreement . In 2009, Hair et al. conducted an airborne HSRL experiment during the MILAGRO campaign. In the experiment, the aerosol optical depth (AOD) retrieved by the HSRL was verified with the AOD measured by a ground-based solar photometer. The difference in measured data was less than 3% (0.01 km-1) at 532 nm [25,26]. Muller, D.  developed an automated, unsupervised inversion algorithm. They present measurements acquired by the world’s first airborne 3 backscatter (β) + 2 extinction (α) high dpectral resolution lidar (HSRL-2). HSRL-2 measures particle backscatter coefficients at 355, 532, and 1064 nm, and particle extinction coefficients at 355 and 532 nm. They observed pollution outflow from the northeastern coast of the US out over the western Atlantic Ocean. Lidar ratios were 50-60 sr at 355 nm and 60–70 sr at 532 nm. Extinction-related Ångström exponents were on average 1.2-1.7, indicating comparably small particles. Their novel automated, unsupervised data inversion algorithm retrieved particle effective radii of approximately 0.2 μm, which is in agreement with the large Ångström exponents. They find good agreement with particle size parameters obtained from coincident in situ measurements carried out with the DOE Gulfstream-1 aircraft. For spaceborne lidar, airborne observations can verify satellite inversion algorithms and provide a reference for the design of key parameters of spaceborne lidar. In addition, after the launch of the satellite, flight experiments with the same orbit can be conducted with airborne lidar to calibrate satellite data. Before and after the launch of the CALIPSO satellite, NASA Langley Research Center (NASA LaRC) conducted long-term airborne observation experiments with more than 240 flights, and the total flight time exceeded 800 h. Including day and night flight experiments, many flights were undertaken under different aerosol and cloud conditions . In summary, carrying out airborne lidar observations is of great significance to the development of lidar research.
In this study, a dual-wavelength HSRL was installed on an airborne platform to conduct experiments over Qinhuangdao, China. A total of 7 flights were undertaken and the total flight time was approximately 28 h. The flight area included ocean, town, mountain, forest, and other land types. In this study, the flight area was divided into three regions that differed by land class. The distribution of aerosol optical properties in the boundary layer of the three regions was analyzed according to the influence of human activity across the three regions. During the campaign, four observation sites were installed at different locations on the ground to compare and verify the airborne lidar results. This article mainly introduces the results from a flight on March 16, 2019. Compared the results of the airborne HSRL with results from ground-based MPL, Mie scattering lidar, and sun photometer. At the same time, measurements of the airborne HSRL were compared with the results of spaceborne CALIPSO and MODIS. The comparison of results exhibited good agreement, which verified the stability and reliability of the airborne HSRL system.
The receiving system of our high spectral resolution lidar, which is based on an iodine molecular absorption cell, can be simplified into a three-detection channel structure, as shown in Fig. 1.
The echo signal passes through a 532 nm band-pass filter and then passes through a narrow-band FP. The central wavelength of the FP is selected to be the same as that of the iodine absorption line wavelength. If the polarization direction of the backscattered signal is changed, there will be a vertical polarization component and a parallel polarization component. The vertical polarization component of the echo signal is reflected by the polarization beam splitter prism at 45° after passing through the first polarization beam splitter prism (PBS1), and then focused into a vertical channel detector. The depolarized echo signal or the parallel polarization component of the depolarized echo signal is transmitted through the first polarization beam splitting prism, and then passes through a 1/2 wave plate and the second polarization beam splitting prism (PBS2). Part of the echo signal light passes through the iodine molecular absorption cell and enters the hyperspectral molecular channel detector through the focusing lens. The remainder of the signal passes through the focusing lens and enters into the parallel reference channel detector. By changing the angle of the 1/2 wave plate, the spectral ratio of the hyperspectral molecular channel to the parallel reference channel can be changed.
The equation of the high spectral resolution polarized lidar based on the iodine molecular absorption cell can be described by the following three equations :
According to Eq. (5), the extinction coefficient αa of the atmospheric aerosol can be obtained as follows:
The aerosol lidar ratio Sa is the ratio of the aerosol extinction coefficient αa to the backscatter coefficient βa. The airborne 1064 nm channel and ground lidar data inversion uses the Fernald forward integration algorithm .
3. Flight campaigns
The working wavelengths of the HSRL were 532 nm and 1064 nm. The 532 nm channel was used to detect the optical characteristics of aerosols and clouds, and the 1064 nm channel was used for ranging and Mie scattering inversion. The laser repetition frequency was 30 Hz, the horizontal resolution was 600 m (aircraft flight speed was 150 m/s), and the vertical distance resolution was 30 m. The experimental arrangement is shown in Table 1. The flight experiment accurately detected the AOD distribution and optical characteristics of the boundary layer in spring over Qinhuangdao, China.
This article mainly reports on analyses of the flight results obtained on March 16. Figure 2 shows a schematic diagram of the aircraft’s flight height over time. The horizontal flight altitude of the aircraft was 7.8 km on March 16. The aircraft made a downward spiral flight at 12:45. This flight path can accurately obtain the vertical profile distribution of atmospheric temperature, atmospheric pressure, and relative humidity, which were used to calculate atmospheric molecular optical parameters. Figure 3 shows the flight trajectory of the aircraft. The flight area contains a variety of land surfaces, including oceans, towns, mountains, and forests.
The layout of the ground stations is shown in Table 2. The comparison and verification equipment of the ground station included the MPL, Mie scattering lidar, and sun photometer.
4.1 Results of airborne lidar measurements
The airborne HSRL emits laser pulses with wavelengths of 532 nm and 1064 nm vertically. The following data products were obtained during the flight experiment: original backscatter signal, aerosol backscatter coefficient, aerosol extinction coefficient, optical depth of the cloud and boundary layer. Table 3 shows the atmospheric conditions of the Qinhuangdao area released by the Meteorological Station of Qinhuangdao City on March 16, and there was no pollution on that day.
Figure 4 shows the results of comparisons of the aerosol backscatter coefficients detected by the airborne HSRL at 532 nm and 1064 nm channels. The results were both averaged for 10 min from 12: 35-12: 45. The two channel detection results exhibited good consistency. They can detect clouds at a height of 3 km, and even the fine vertical structure of the cloud.
4.2 Ground validation
The plane passed near the Funing surface station at 11:38 am on March 16, and the closest distance was approximately 35 km. The results of the airborne lidar were compared with those measured by the MPL and sun photometer at the Funing surface station. MPL profiles are 30-min averaged from 11:23-11:53 and the HSRL 532 nm channel profiles are 1-min averaged from 11:37:39-11:38:41 time period. The results of the comparison of the backscatter coefficients are shown in Fig. 5.
The results of the airborne lidar and the MPL were in good agreement. The correlation coefficient of the aerosol backscatter coefficient measured by the two devices was 0.8. In addition, we also compared the AOD measured by the airborne lidar with those measured by the sun photometer at Funing Station. The aircraft passed the vicinity of the Funing surface station twice at 11:30 and 12:14. At 12:14, the aircraft was closest to the ground station (approximately 12.8 km). The AOD measured by the 500 nm and 1020 nm bands of the sun photometer were compared with the results of the airborne lidar 532 nm and 1064 nm channels. Table 4 shows the measured values of the AOD and the results of the comparison are shown in Fig. 6. Values derived from the sun photometer always exceeded the values derived from the airborne HSRL. This was because of differences in their working principles.
The results of the airborne lidar were also compared with those from the Mie scattering lidar located at the Beidaihe surface station. The comparison results are shown in Fig. 7.
At 12:39 on March 16, the aircraft route was closest to the Beidaihe surface station, and the closest distance was 1.2 km. Mie scattering lidar profiles are a 20-min averaged from the 12: 30-12:50 time period. The Fernald method is used to inverse the data of the Mie scattering lidar, and the boundary value of the Mie scattering lidar in Fig. 7 is provided by the HSRL at 6 km. By comparing the backscatter coefficient results, the detection results of the Mie scattering lidar and the airborne HSRL were in good agreement. The correlation coefficient was 0.77. Because the aircraft route is far away from the ground station and the data inversion methods are different, the results are less relevant.
4.3 Satellite validation
In addition to comparing the data of the airborne HSRL with the ground stations, the results of the airborne HSRL were also compared with the spaceborne CALIPSO and MODIS. Since the CALIPSO satellite had no data on March 16, there were fewer valid data on March 15, the data at 11:41:20 on March 16, 2019 of the airborne HSRL 532 nm hyperspectral channel were selected for comparison with the data of three time periods of the CALIPSO satellite on March 15, 2019. The results of the comparison are shown in Fig. 8.
The surface type of the airborne lidar at 11:41 was mountain, and the surface altitude was 90 m, so there were no data near the surface. The closest distance between the airborne lidar and CALIPSO orbit at this time was 148 km, and the time interval was approximately 22 h. Consequently, the data were partially different because of this time lag. The airborne HSRL can detect the aerosol layer at a height of 120 m from the surface. The weather was fine on March 15-16, 2019 and atmospheric conditions were stable. There was no significant transmission or diffusion of local aerosols. The maximum correlation coefficient between the detection results of the airborne HSRL and CALIPSO satellite was 0.76.
The AOD observed by the 532 nm channel of the airborne lidar was also compared with the 550 nm band of the MODIS (Aqua) satellite, and compared with the results of the 500 nm band of the sun photometer at Funing and Beidaihe ground stations. Table 5 shows the observation results of the aerosol optical depth. The comparison results are shown in Fig. 9. MODIS (Aqua) has no data on March 9, Funing ground station has no data on March 4, and Beidaihe ground station has no data on March 4/16/18/19.
The AOD detected by the airborne lidar were in good agreement with those obtained by the MODIS, Funing, and Beidaihe ground stations. The correlation coefficient of aerosol optical depth detected by airborne lidar and MODIS reaches 0.9926, and 0.936 with the sun photometer of Funing ground station. The observation results from Table 5 show that the AOD value was the smallest on March 14, when atmospheric conditions were good, the AQI index was 30, and the average value of the AOD observed by each device was 0.146. From March 14 to March 18, the concentration of pollutants gradually increased. On March 18, the AOD reached its maximum value because of the slight pollution on that day. On March 18, the AQI index was 103, and the average value of the AOD was 1.102. The HYSPLIT backward trajectory mode was used to analyze the first 36 hours of air mass trajectory at Funing station at 08:00 on March 18. The orbital results are shown in Fig. 10. Pollutants over Funing on March 18 mainly came from central China, located to the southwest of Funing ground station.
4.4 Boundary layer aerosol optical depth analysis
The data products of the airborne HSRL during the horizontal flight on March 16, 2019, are shown in Fig. 11. The horizontal flight height of the aircraft was 7.8 km and there were many scattered clouds at a height of 3 to 4 km. During the flight we needed to adjust the instrument’s parameters so that some data are missing. The aircraft flew over ocean, towns and mountains, alternating between each land class, as indicated in Fig. 11. The entire flight was divided into seven stages, A-G, as a function of land class. A significant aerosol layer was apparent when flying over towns due to the influence of human activities. During the flight stages of C and G, the plane passed near a power plant, and this area contained obvious pollutants due to industrial production activities. In contrast, when the land class of the flight area was ocean (flight stages A and F) the aerosol content was minimal because of the absence of nearby industrial activity.
The boundary layer AOD was directly related to the land class and human activities below the flight path. To accurately analyze the distribution of AOD in the boundary layer of the flight path, the flight area was divided into three sectors according to land class and human activities, as shown in Fig. 12.
Figure 13 shows the distribution of the boundary layer AOD measured by the 532 nm and 1064 nm channels of the airborne lidar during horizontal flight. Each point was averaged for 40 s, and cloud data were excluded. The atmospheric conditions were good and no pollution was apparent on March 16, so the AOD values were generally small on this day. The maximum value of the AOD detected by the 1064 nm channel was 0.07 and the 532 nm channel was 0.35. It can be seen from Fig. 13 that the values of the boundary layer AOD measured by 532 nm and 1064 nm channel are largest in sector 2 and smallest in sector 3. Sector 1 to sector 3 is defined in Fig. 12.
In order to quantify the distribution of the boundary layer AOD in the three sectors defined in Fig. 12, (a) histogram was used to display the boundary layer AOD distribution of the two channels in Fig. 13. The AOD increment was set to 0.01 and results are shown in Figs. 14 and 15.
The histogram distribution of the boundary layer AOD in the three sectors, derived from the 532 nm channel, is shown in Fig. 14. Most values of the boundary layer AOD measured by the 532 nm channel were distributed in interval of 0.21-0.22 in sector 1, interval 0.27-0.28 in sector 2, and interval 0.22-0.23 in sector 3. Figure 15 shows the histogram distribution of the boundary layer AOD in the three sectors derived from the 1064 nm channel. Compared with the distribution results of the 532 nm channel, the difference in the boundary layer AOD detected by the 1064 nm channel was more apparent. Most values of the boundary layer AOD in sector 1 were distributed in the interval 0.02-0.04, and interval 0.01-0.15 in sector 2, and most values of the boundary layer AOD in sector 3 were distributed in the interval 0.01- 0.02. The value of the boundary layer AOD in sector 3 was the smallest.
A dual-wavelength high spectral resolution lidar (HSRL) was developed for the validation and calibration of an upcoming satellite payload. The HSRL was installed on an airplane, and field campaigns were conducted in Qinhuangdao in March 2019. A total of 7 flights were undertaken, with a total flight time of 28 h. Meanwhile, four cooperative observation sites were installed at different locations on the ground to verify the results of the airborne lidar. First, we compared the results of the airborne HSRL with those derived from the ground station equipment, including the MPL, Mie scattering lidar, and sun photometer at Funing and Beidaihe surface stations. The results of the airborne HSRL were also compared with the spaceborne CALIPSO and MODIS. The results of the comparison demonstrated good agreement. The correlation coefficients of AOD between the airborne lidar and MODIS, sun photometer of Funing ground station were 0.9926, and 0.936. The stability and reliability of the HSRL system were fully verified. These flights accurately detected the distribution of boundary layer AOD and aerosol optical characteristics in spring in the Qinhuangdao area. The flight path covered several land types, including ocean, town, mountain, and forest. Boundary layer AOD was directly related to the land class and human activities. To accurately analyze the distribution of AOD in the boundary layer of the flight path, the flight area was divided into three sectors according to land class and human activities. The results show that AOD was largest above the town and coastal areas. Most values of the boundary layer AOD detected by the 532 nm channel were distributed in interval of 0.27-0.28, and 0.01-0.15 detected by the 1064 nm channel. AOD in the mountainous area was the second largest and values were distributed in intervals of 0.21-0.22 detected by the 532 nm channel, and 0.02-0.04 detected by the 1064 nm channel. AOD in the marine area was the smallest, with most values detected by the 532 nm channel distributed in interval of 0.22-0.23, and 0.01-0.02 detected by the 1064 nm channel.
National Natural Science Foundation of China (41675133).
Thanks for the support of Shanghai Institute of Satellite Engineering for this experiment. Thanks to the Institute of Remote Sensing of the Chinese Academy of Sciences for providing the data of the Mie scattering lidar and the sun photometer at Beidaihe surface station. Thanks to Zhejiang University, Wuhan University and Ocean University of China for their collaborative experiments. We also would like to thank Editage for English language editing. Thanks to Farhan Mustafa for revising the wording and grammar of the article.
The authors declare no conflicts of interest.
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