Abstract
There is compelling evidence that the incomplete laser beam receiver field-of-view overlap (i.e., partial overlap) of ground-based vertically-pointing aerosol LiDAR restricts the observational range for detecting aerosol layer boundaries to a certain height above the LiDAR. This height varies from one to few hundreds of meters, depending on the transceiver geometry. The range, or height of full overlap, is defined as the minimum distance at which the laser beam is completely imaged onto the detector through the field stop in the receiver optics. Thus, the LiDAR signal below the height of full overlap remains erroneous. In effect, it is not possible to derive the atmospheric boundary layer (ABL) top (zi) below the height of full overlap using lidar measurements alone. This problem makes determination of the nocturnal zi almost impossible, as the nocturnal zi is often lower than the minimum possible retrieved height due to incomplete overlap of lidar. Detailed studies of the nocturnal boundary layer or of variability of low zi would require changes in the LiDAR configuration such that a complete transceiver overlap could be achieved at a much lower height. Otherwise, improvements in the system configuration or deployment (e.g., scanning LiDAR) are needed. However, these improvements are challenging due to the instrument configuration and the need for Raman channel signal, eye-safe laser transmitter for scanning deployment, etc. This paper presents a brief review of some of the challenges and opportunities in overcoming the partial overlap of the LiDAR transceiver to determine zi below the height of full-overlap using complementary approaches to derive low zi. A comprehensive discussion focusing on four different techniques is presented. These are based on the combined (1) ceilometer and LiDAR; (2) tower-based trace gas (e.g., CO2) concentration profiles and LiDAR measurements; (3) 222Rn budget approach and LiDAR-derived results; and (4) encroachment model and LiDAR observations.
Highlights
The atmospheric boundary layer (ABL) and the entrainment zone primarily govern the mixing of pollutants into the upper troposphere, which influences air quality and climate simulation [1].The depth of the ABL and the growth rate of the ABL in the morning are important parameters for characterizing many atmospheric processes, including land-atmosphere exchange processes and the dispersion of air pollutants and the formation of clouds [2,3,4]
The overlap function O(R) describes the competency in performance of a LiDAR with which light is coupled into its detectors as a function of range
The water vapor DIAL system developed by Behrendt et al [47] is a unique system but due to its complexity this type of LiDAR system requires high expenditure, significant amount of maintenance, advanced and high power laser technology, etc. We suggest that this system or any other two-telescope bi-axial LiDAR system is not a suitable candidate for operational monitoring of zi though it is an excellent instrument for field deployments (e.g., [48])
Summary
The atmospheric boundary layer (ABL) and the entrainment zone primarily govern the mixing of pollutants into the upper troposphere, which influences air quality and climate simulation [1].The depth of the ABL and the growth rate of the ABL in the morning are important parameters for characterizing many atmospheric processes, including land-atmosphere exchange processes and the dispersion of air pollutants and the formation of clouds [2,3,4]. Numerous studies have been performed to determine daytime convective boundary layer (CBL) topped by the clean, free atmosphere (FA). These studies used different techniques, namely threshold detection (e.g., [18]), the gradient-based method (e.g., [19]), the inflection point method (e.g., [20]), the variance analysis (e.g., [21]), the Haar wavelet approach (e.g., [14]), the combined wavelet and image processing method [22], the ideal profile method (e.g., [23]), and the 2-D gradient approach [24] to derive zi using aerosol LiDAR measurements
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